Patients often report various symptoms after recovery from acute COVID-19. Previous studies on post-COVID-19 condition have not corrected for the prevalence and severity of these common symptoms before COVID-19 and in populations without SARS-CoV-2 infection. We aimed to analyse the nature, prevalence, and severity of long-term symptoms related to COVID-19, while correcting for symptoms present before SARS-CoV-2 infection and controlling for the symptom dynamics in the population without infection.
Methods
This study is based on data collected within Lifelines, a multidisciplinary, prospective, population-based, observational cohort study examining the health and health-related behaviours of people living in the north of the Netherlands. All Lifelines participants aged 18 years or older received invitations to digital COVID-19 questionnaires. Longitudinal dynamics of 23 somatic symptoms surrounding COVID-19 diagnoses (due to SARS-CoV-2 alpha [B.1.1.7] variant or previous variants) were assessed using 24 repeated measurements between March 31, 2020, and Aug 2, 2021. Participants with COVID-19 (a positive SARS-CoV-2 test or a physician’s diagnosis of COVID-19) were matched by age, sex, and time to COVID-19-negative controls. We recorded symptom severity before and after COVID-19 in participants with COVID-19 and compared that with matched controls.
Findings
76 422 participants (mean age 53·7 years [SD 12·9], 46 329 [60·8%] were female) completed a total of 883 973 questionnaires. Of these, 4231 (5·5%) participants had COVID-19 and were matched to 8462 controls. Persistent symptoms in COVID-19-positive participants at 90–150 days after COVID-19 compared with before COVID-19 and compared with matched controls included chest pain, difficulties with breathing, pain when breathing, painful muscles, ageusia or anosmia, tingling extremities, lump in throat, feeling hot and cold alternately, heavy arms or legs, and general tiredness. In 12·7% of patients, these symptoms could be attributed to COVID-19, as 381 (21·4%) of 1782 COVID-19-positive participants versus 361 (8·7%) of 4130 COVID-19-negative controls had at least one of these core symptoms substantially increased to at least moderate severity at 90–150 days after COVID-19 diagnosis or matched timepoint.
Interpretation
To our knowledge, this is the first study to report the nature and prevalence of post-COVID-19 condition, while correcting for individual symptoms present before COVID-19 and the symptom dynamics in the population without SARS-CoV-2 infection during the pandemic. Further research that distinguishes potential mechanisms driving post-COVID-19-related symptomatology is required.
Funding
ZonMw; Dutch Ministry of Health, Welfare, and Sport; Dutch Ministry of Economic Affairs; University Medical Center Groningen, University of Groningen; Provinces of Drenthe, Friesland, and Groningen.
Introduction
After recovery from acute COVID-19, a substantial proportion of patients continue to experience symptoms of a physical, psychological, or cognitive nature.
1
How and why patients made long COVID.
These long-term sequelae of COVID-19 have been described as the next public health disaster in the making, and there is an urgent need for empirical data informing on the scale and scope of the problem to support the development of an adequate health-care response.
2
Confronting our next national health disaster—long-haul COVID.
,
3
Crook H
Raza S
Nowell J
Young M
Edison P
Long COVID—mechanisms, risk factors, and management.
Research has been hampered by an absence of a consensus on the prevalence and nature of the post-COVID-19 condition.
2
Confronting our next national health disaster—long-haul COVID.
A systematic review examining the frequency and variety of persistent symptoms after COVID-19 reported that the median proportion of patients with at least one persistent symptom was 72·5%.
4
Nasserie T
Hittle M
Goodman SN
Assessment of the frequency and variety of persistent symptoms among patients with COVID-19: a systematic review.
However, this estimated prevalence largely depends on the timeframe, population, and symptoms used to define post-COVID-19 condition. The timeframe used varies from 4 weeks to more than 6 months after a COVID-19 diagnosis, with 3 months being the most commonly used.
5
Long COVID or post-COVID-19 syndrome: putative pathophysiology, risk factors, and treatments.
Furthermore, most studies have relied on follow-up of hospitalised patients with COVID-19.
4
Nasserie T
Hittle M
Goodman SN
Assessment of the frequency and variety of persistent symptoms among patients with COVID-19: a systematic review.
The vast majority of people with COVID-19, however, have mild disease and are not hospitalised,
6
Ballering AV
Oertelt-Prigione S
olde Hartman TC
et al.
Sex and gender-related differences in COVID-19 diagnoses and SARS-CoV-2 testing practices during the first wave of the pandemic: the Dutch Lifelines COVID-19 cohort study.
and hospitalisation itself is associated with somatic symptoms.
7
High-dimensional characterization of post-acute sequelae of COVID-19.
Another complicating factor is that there is no consensus on the nature of the symptoms that can be attributed to COVID-19. Selection of the symptoms is crucial for charting the scale and scope of post-COVID-19 condition. However, frequently reported post-COVID-19 symptoms are also common in the general population.
4
Nasserie T
Hittle M
Goodman SN
Assessment of the frequency and variety of persistent symptoms among patients with COVID-19: a systematic review.
,
8
Fernández-de-Las-Peñas C
Palacios-Ceña D
Gómez-Mayordomo V
Cuadrado ML
Florencio LL
Defining post-COVID symptoms (post-acute COVID, long COVID, persistent post-COVID): an integrative classification.
,
9
Acevedo-Mesa A
Tendeiro JN
Roest A
Rosmalen JGM
Monden R
Improving the measurement of functional somatic symptoms with item response theory.
Symptoms such as fatigue and headaches might be worsened during the pandemic also in people without COVID-19, for example, due to anxiety-induced stress or the combination of work and homeschooling.
10
Bekhuis E
Schoevers RA
van Borkulo CD
Rosmalen JG
Boschloo L
The network structure of major depressive disorder, generalized anxiety disorder and somatic symptomatology.
,
11
Janssens KAM
Rosmalen JGM
Ormel J
van Oort FV
Oldehinkel AJ
Anxiety and depression are risk factors rather than consequences of functional somatic symptoms in a general population of adolescents: the TRAILS study.
An additional complication is that some of the symptoms reported after COVID-19 might already have been present before COVID-19 and might even reflect a pre-existing susceptibility to COVID-19 itself, rather than being a consequence of SARS-CoV-2 infection.
Research in context
Evidence before this study
We searched PubMed, Google Scholar, and preprint repositories from November, 2019, to February, 2022, for studies published in Dutch or English that investigated the course of post-COVID-19 condition (ie, long COVID) over time, the symptoms associated with post-COVID-19 condition, and the prevalence of post-COVID-19 condition. Furthermore, we searched for studies and policy documents from (global) public health institutes (eg, WHO) that aimed to clinically define post-COVID-19 condition. A formal systematic review was not conducted. Most previous research that assessed the prevalence and symptoms associated with post-COVID-19 condition did not include an adequate control group, and so no adjustments for the prevalence of somatic symptoms in the population without COVID-19 could be made. Additionally, we found no studies that included patients’ symptom prevalence before COVID-19 diagnosis; therefore, the previous studies were unable to assess whether somatic symptoms reported after a COVID-19 diagnosis were already present before SARS-CoV-2 infection. Most research was conducted in a clinical setting, disregarding post-COVID-19 condition in the general population. In the context of these shortcomings, a systematic review estimated that the median proportion of patients with at least one somatic symptom after COVID-19 was 72·5%.
Added value of this study
To our knowledge, this study is the first to include a control group matched for age, sex, and time, enabling us to adjust for symptom presence in the general population and changes herein due to public health measures and seasonal influences. Additionally, the repeated-measures nature of this study enabled us to assess symptom severity in patients with COVID-19 before they had SARS-CoV-2 infection. Therefore, we could assess whether symptom severity was truly increased after a COVID-19 diagnosis, or whether symptoms were a continuation of pre-existing symptoms. Our approach allowed for identification of core symptoms that define post-COVID-19 condition, as these are increased in severity 90–150 days after a COVID-19 diagnosis compared with patient’s pre-existing symptom severity.
Implications of all the available evidence
Our unique approach allows us to present the core symptoms, namely chest pain, difficulties with breathing, pain when breathing, painful muscles, ageusia or anosmia, tingling extremities, lump in throat, feeling hot and cold alternately, heavy arms or legs, and general tiredness, which could define post-COVID-19 condition. Additionally, we offer an improved working definition of post-COVID-19 condition and provide a reliable prevalence estimate in the general population corrected for pre-existing symptoms, and symptoms in COVID-19-negative controls. Taking into account the symptoms that increased in severity and could be attributed to COVID-19, while correcting for seasonal fluctuations and non-infectious health aspects of the pandemic on symptom dynamics, we estimated that 12·7% of patients with COVID-19 in the general population will experience persistent somatic symptoms after COVID-19. Additionally, these core symptoms have major implications for future research, as these symptoms have the highest discriminative ability to distinguish between post-COVID-19 condition and non-COVID-19-related symptoms.
Therefore, detailed information about symptom dynamics before and after SARS-CoV-2 infection in the general population is needed to provide insight into the scale and scope of post-COVID-19 condition. However, such data—requiring repetitive measurements of symptom scores before and after SARS-CoV-2 infection—have not yet been reported. Furthermore, symptom dynamics need to be compared between people affected by COVID-19 and a matched sample of people without infection to be able to separate the effects of the SARS-CoV-2 infection from the effects of the pandemic, associated social restrictions, and public health measures on symptom dynamics in the general population.
12
Amin-Chowdhury Z
Ladhani SN
Causation or confounding: why controls are critical for characterizing long COVID.
We aimed to analyse the nature, prevalence, and severity of long-term symptoms related to COVID-19, while correcting for symptoms present before SARS-CoV-2 infection and controlling for the symptom dynamics in the population without infection.
Results
76 422 participants (mean age 53·7 years [SD 12·9], 46 329 [60·8%] were female) completed a total of 883 973 questionnaires. Of these, 4231 (5·5%) participants were COVID-19 positive (mean age 52·4 years [SD 11·7], 2779 [65·7%] were female; table 1; appendix p 4); they completed 62 224 questionnaires (appendix p 5). Female COVID-19-positive participants completed a median of 17 questionnaires (IQR 8–23), male COVID-19-positive participants completed a median of 18 (9–23). The maximum follow-up time was 484 days after COVID-19 diagnosis (median 101 days [IQR 43–199]). COVID-19-positive participants were matched to 8462 COVID-19-negative controls who together completed 140 810 questionnaires (appendix p 4). Both male and female control participants completed a median of 20 questionnaires (IQR 12–24) each. The maximum follow-up time of control participants was 481 days after their matched timepoint (median 104 days [IQR 46–201]). The sex-stratified 28-day moving average of control participants’ mean sum score of all 23 assessed symptoms is shown in the appendix (p 3). Men were more frequently hospitalised due to COVID-19 than women (5·0% of male vs 2·5% of female COVID-19-positive participants).
Table 1Characteristics of the COVID-19-positive participants
Data are mean (SD) or n (%).
Visual inspection of symptom dynamics over time indicated that almost all assessed symptoms showed an increase in severity in COVID-19-positive participants compared with controls during the acute phase of COVID-19 (Figure 1, Figure 2, Figure 3). Diarrhoea and stomach pain, as well as cold-like symptoms including sneezing, wet and dry cough, runny nose, fever, and sore throat on average returned to pre-COVID-19 severity within 50 days of a COVID-19 diagnosis, which suggests that these symptoms were predominantly present during the acute phase of the disease (figure 1).
Symptoms that were more severe in COVID-19-positive participants 90–150 days after COVID-19 compared with symptom scores before COVID-19 and compared with matched controls (ie, the core symptoms of post-COVID-19 condition) included: cardiopulmonary symptoms (chest pain, difficulties with breathing, and pain when breathing), musculoskeletal symptoms (painful muscles), sensory symptoms (ageusia or anosmia, tingling extremities, lump in throat, and feeling hot and cold alternately), and general symptoms (heavy arms or legs, and general tiredness; figure 2). These symptoms differed based on both visual inspection of symptom dynamics and on the significance of the difference in distribution of symptoms that increased substantially to at least moderate severity in COVID-19-positive participants and control participants (table 2). Mean severity for these symptoms appeared to have reached a plateau at 3 months, with no further decline in mean severity thereafter. Symptoms that were not significantly increased in mean severity at 90–150 days after a COVID-19 diagnosis included headache, itchy eyes, dizziness, back pain, and nausea (figure 3).
Table 2Frequencies of participants who had presence of, or a substantial increase to, symptoms of at least moderate severity at 90–150 days after COVID-19 diagnosis or matched timepoint
Data are n (%). Symptoms are ordered according to their relative increase in frequency in COVID-19-positive participants compared with controls. A substantial increase in severity was defined as an increase in symptom severity of at least 1 point on the 5-point scale.
Visual inspection of the core symptoms suggests that in many of these symptoms, including lump in throat, heavy arms or legs, general tiredness, and feeling hot and cold alternately, sex differences were present. Female COVID-19-positive participants showed a longer persistence of increased symptom severity after COVID-19 than male COVID-19-positive participants (figure 2). A similar pattern was observed in acute symptoms, such as dry cough, stomach pain, and diarrhoea (figure 1), and in all symptoms that were not significantly increased in severity at 90–150 days after a COVID-19 diagnosis, except for back pain. Table 2 shows the frequencies of COVID-19-positive participants and controls that had symptoms of at least moderate severity at 90–150 days after COVID-19 or matched timepoint. In total, 790 (40·7%) of 1942 COVID-19-positive participants had at least one symptom of moderate severity at 90–150 days, compared with 1275 (29·3%) of 4353 controls. Painful muscles and back pain were the most frequent symptoms in both COVID-19-positive participants (13·5% and 10·8%, respectively) and controls (8·7% and 9·5%, respectively). This analysis, however, did not consider symptom severity before COVID-19.
A greater proportion of COVID-19-positive participants had a substantial increase in symptom severity resulting in moderate symptom severity of at least one symptom at 90–150 days after COVID-19 diagnosis than control participants during the same period (526 [29·6%] of 1782 participants vs 749 [18·1%] of 4130; table 2). Ageusia or anosmia (135 [7·6%] of 1782 participants), painful muscles (130 [7·3%]) and general tiredness (88 [4·9%]) were most frequently increased to moderate severity in COVID-19-positive participants, while they were increased in 17 (0·4%), 134 (3·2%), and 87 (2·1%) control participants, respectively. The prevalence of ageusia or anosmia of increased severity (7·6%) was 19 times greater in COVID-19-positive participants than in controls (0·4%). Sensitivity analyses in which participants with a physician’s diagnosis of COVID-19 were excluded (including only those with a positive SARS-CoV-2 test) showed similar results (appendix pp 6–7).
Restricting the definition of post-COVID-19 condition to core symptoms (figure 2) showed that 381 (21·4%) of 1782 COVID-19-positive participants versus 361 (8·7%) of 4130 controls had at least one symptom substantially increased to at least moderate severity (χ2 [df 1] 181·1; p<0·0001; denominators based on participants with data available for at least 7 days before their SARS-CoV-2 infection or matched timepoint and 90–150 days after their COVID-19 diagnosis or matched timepoint). This finding implies that in 12·7% of patients with COVID-19, the increased core symptoms with moderate severity at 3 months after COVID-19 could be attributed to SARS-CoV-2 infection. Including all assessed symptoms in the definition decreased the prevalence of participants with an increase in symptom severity only slightly (to 11·5%), but resulted in a loss of sensitivity for symptoms that can be attributed to SARS-CoV-2 (ie, the ratio between patients with symptoms due to SARS-CoV-2 infection and those with unrelated symptoms was 2·5 for the core set of symptoms vs 1·6 when including all symptoms).
Discussion
This study shows post-COVID-19 condition might occur in about one out of eight people with COVID-19 in the general population. Core symptoms of post-COVID-19 condition include chest pain, difficulties with breathing, lump in throat, pain when breathing, painful muscles, heavy arms or legs, ageusia or anosmia, feeling hot and cold alternately, tingling extremities, and general tiredness. To our knowledge, this is the first study to provide a reliable assessment of the prevalence of post-COVID-19 condition, while correcting for individual symptoms present before SARS-CoV-2 infection and for the dynamics of symptoms reported by sex-matched and age-matched controls without infection in the same period during the pandemic. This corrected prevalence remained nearly unaltered irrespective of the use of the core symptoms versus a broader range of symptoms as a definition of post-COVID-19 condition. However, when including a broader range of symptoms, the ratio between patients with symptoms due to SARS-CoV-2 infection and those with unrelated symptoms decreased. Increased knowledge on both the nature of the core symptoms and the prevalence of post-COVID-19 condition in the general population represents a major step forward in our ability to design studies that ultimately inform an adequate health-care response to the long-term sequelae of COVID-19.
The major strengths of this study are the large sample size of COVID-19-positive participants identified in a general population cohort, as well as the multiple repeated measurements of symptom severity in the participants. This allowed for the calculation of pre-COVID-19 symptom severity in each participant. In addition, we were able to compare COVID-19-positive participants’ symptom severity with controls matched by sex and age who provided measurements at the same time period as the cases. Finally, the SCL-90 SOM subscale is a validated instrument, suitable for assessing symptoms in large-scale cohort studies. The addition of other COVID-19-related symptoms allowed for detailed insights into participants’ symptom dynamics.
Before interpreting the results, some limitations of this study should be acknowledged. First, COVID-19 cases can be asymptomatic and remain undetected.
8
Fernández-de-Las-Peñas C
Palacios-Ceña D
Gómez-Mayordomo V
Cuadrado ML
Florencio LL
Defining post-COVID symptoms (post-acute COVID, long COVID, persistent post-COVID): an integrative classification.
Therefore, the prevalence of COVID-19 in this study might have been underestimated. Second, the assessed symptoms were included in the Lifelines COVID-19 cohort study at the beginning of the pandemic. Although at that time these symptoms were considered to be related to COVID-19, other symptoms such as cognitive symptoms (eg, brain fog) and post-exertional malaise were identified later during the pandemic as potentially relevant for a working definition of post-COVID-19 condition.
7
High-dimensional characterization of post-acute sequelae of COVID-19.
Third, as all participants in the Lifelines COVID-19 cohort study were aged 18 years or older, we could not assess paediatric post-COVID-19 condition. Fourth, the exact date of COVID-19 diagnosis was unknown; we therefore used the date of the first questionnaire in which COVID-19 positivity was indicated as date of diagnosis. This might have led to an underestimation of post-COVID-19 time. Lastly, as this study was conducted in the northern region of the Netherlands, these results might not be generalisable to other areas.
Multiple studies have assessed the persistence of somatic symptoms after COVID-19, with timeframes of follow-up varying from 21 days to 6 months.
4
Nasserie T
Hittle M
Goodman SN
Assessment of the frequency and variety of persistent symptoms among patients with COVID-19: a systematic review.
,
19
Nguyen NN
Hoang VT
Dao TL
Dudouet P
Eldin C
Gautret P
Clinical patterns of somatic symptoms in patients suffering from post-acute long COVID: a systematic review.
Some studies included participants from post-COVID-19 support groups or predominantly patients who were hospitalised, leading to biased results.
20
Davis HE
Assaf GS
McCorkell L
et al.
Characterizing long COVID in an international cohort: 7 months of symptoms and their impact.
,
21
Goërtz YMJ
Van Herck M
Delbressine JM
et al.
Persistent symptoms 3 months after a SARS-CoV-2 infection: the post-COVID-19 syndrome?.
A systematic review analysed 11 studies that assessed the persistence of symptoms 90–180 days after COVID-19 in outpatients.
19
Nguyen NN
Hoang VT
Dao TL
Dudouet P
Eldin C
Gautret P
Clinical patterns of somatic symptoms in patients suffering from post-acute long COVID: a systematic review.
The sample sizes ranged from 59 to 2915 patients with COVID-19 and the number of assessed symptoms ranged from six to 21. The most prevalent symptom was fatigue (11–42% of patients), followed by dyspnoea (8–37%), painful muscles (7–24%), and ageusia or anosmia (3–24%). Thoracic pain was reported in 3–14% of patients at 90–180 days after COVID-19. Although we found similar prevalence rates for some of these symptoms, we also showed that these rates were lower when patients’ symptom severity before COVID-19 was taken into account. Additionally, we showed that the most prevalent symptoms are not the most distinctive symptoms for post-COVID-19 condition. Furthermore, many studies with clinical cohorts did not include a matched control group and were therefore unable to distinguish between effects of SARS-CoV-2 infection and those of the pandemic on symptoms.
12
Amin-Chowdhury Z
Ladhani SN
Causation or confounding: why controls are critical for characterizing long COVID.
Studies that included a control group could not distinguish between symptoms resulting from a SARS-CoV-2 infection and pre-existing symptoms. A large study that included 106 578 patients with COVID-19 and matched controls with influenza, which assessed the persistence of seven somatic symptoms at 90–180 days after diagnosis, found that somatic symptoms, such as headache, chest pain, and fatigue, were more frequently present in patients with COVID-19 than in the controls.
22
Taquet M
Dercon Q
Luciano S
Geddes JR
Husain M
Harrison PJ
Incidence, co-occurrence, and evolution of long-COVID features: a 6-month retrospective cohort study of 273,618 survivors of COVID-19.
The study found higher prevalence rates for most assessed somatic symptoms than our study—for example, breathing difficulties occurred in 7·9% of patients with COVID-19 and chest pain occurred in 5·7%. Painful muscles was the only symptom that was less frequently reported (1·5% of patients). The difference in observed prevalence rates might be explained by the previous study only including patients with COVID-19 who sought help for their persistent symptoms from a health-care provider, and not adjusting for patients’ symptoms before COVID-19.
Additionally, a study in France that included 1091 SARS-CoV-2-positive participants and 25 732 controls suggested that the belief of being infected with SARS-CoV-2 was more strongly associated with the severity of symptoms 8 weeks after SARS-CoV-2 infection than laboratory confirmed COVID-19 diagnosis.
23
Matta J
Wiernik E
Robineau O
et al.
Association of self-reported COVID-19 infection and SARS-CoV-2 serology test results with persistent physical symptoms among French adults during the COVID-19 pandemic.
This conclusion is potentially stigmatising,
24
Ballering A
olde Hartman T
Rosmalen J
Long COVID-19, persistent somatic symptoms and social stigmatisation.
and the study has some limitations. First, serological assays were used to detect SARS-CoV-2 infection, but patients affected by post-COVID-19 condition might have lower antibody responses.
25
García-Abellán J
Padilla S
Fernández-González M
et al.
Antibody response to SARS-CoV-2 is associated with long-term clinical outcome in patients with COVID-19: a longitudinal study.
Second, the cross-sectional nature of the study with retrospective assessments is problematic, as persistent physical symptoms might have confounded recall of past illness and thus the belief in having been infected. Third, confounding by other viruses might have occurred, which might have caused both the belief of having been infected with SARS-CoV-2 and the persistent symptoms. Our study overcame these limitations by performing sensitivity analyses restricted to participants with a COVID-19 diagnosis based on a positive SARS-CoV-2 test and by the study’s prospective design. Nevertheless, our study cannot provide definitive information on the underlying mechanisms driving post-COVID-19-related symptoms. Therefore, additional research assessing the causes of post-COVID-19-related symptoms is required.
To our knowledge, this is the first study that is able to identify which persistent symptoms are particularly related to SARS-CoV-2 infection, and we used these core symptoms of post-COVID-19 condition for an empirically based working definition of the condition. Notably, in the absence of adequate control data, case definitions might be biased towards highly prevalent symptoms. Experts in a WHO Delphi procedure constructed a case definition that identified fatigue and dyspnoea as the most important symptoms of post-COVID-19 condition (78% of the panel agreed on their importance for the case definition).
26
Soriano JB
Murthy S
Marshall JC
Relan P
Diaz JV
A clinical case definition of post-COVID-19 condition by a Delphi consensus.
Our empirical analyses showed that these were among the core symptoms, but the most distinctive symptoms also included chest pain and ageusia or anosmia (considered important for the case definition by 55% and 57% of the Delphi panel, respectively). Additionally, tingling extremities were considered important by merely 39% of the experts, while 56% considered headache to be important for the case definition. Our results, however, suggest that tingling extremities is a core symptom whereas headache is not related to SARS-CoV-2 infection. These differences clearly show the importance of longitudinal cohort studies in the general population with pre-infection data and controls without infection to study the scale and scope of post-COVID-19 condition.
Furthermore, although sex differences are known to be present in persistent somatic symptoms of COVID-19, this is the first study of our knowledge to stratify symptom dynamics by sex both before and after COVID-19. Multiple somatic symptoms—for example, feeling hot and cold alternately, lump in throat, and general tiredness—were shown to be more severe after COVID-19 in women than in men, compared with controls. Research has shown that women report more severe common somatic symptoms than men and that these symptoms are more frequently persistent.
27
Ballering AV
Wardenaar KJ
olde Hartman TC
Rosmalen JGM
Female sex and femininity independently associate with common somatic symptom trajectories.
,
28
Ballering AV
Bonvanie IJ
olde Hartman TC
Monden R
Rosmalen JGM
Gender and sex independently associate with common somatic symptoms and lifetime prevalence of chronic disease.
,
29
Barsky AJ
Peekna HM
Borus JF
Somatic symptom reporting in women and men.
Multiple explanations have been proposed for this phenomenon. First, women are thought to have a heightened sensitivity to pain compared with men, due to biological differences rooted in, among others, sex hormones and genotype.
30
Sex differences in pain: a brief review of clinical and experimental findings.
Second, women might be more aware of bodily sensations than men, allowing for an easier and earlier perception of somatic symptoms in women than in men.
29
Barsky AJ
Peekna HM
Borus JF
Somatic symptom reporting in women and men.
However, the female preponderance in symptom experience is not only due to differences in biology (ie, sex), but also in societal expectations of women and men (ie, gender roles).
27
Ballering AV
Wardenaar KJ
olde Hartman TC
Rosmalen JGM
Female sex and femininity independently associate with common somatic symptom trajectories.
,
28
Ballering AV
Bonvanie IJ
olde Hartman TC
Monden R
Rosmalen JGM
Gender and sex independently associate with common somatic symptoms and lifetime prevalence of chronic disease.
Feminine gender roles, for example, are thought to be associated with poorer access to health care, which might also explain health-related gender differences.
31
Pelletier R
Humphries KH
Shimony A
et al.
Sex-related differences in access to care among patients with premature acute coronary syndrome.
A list of empirically validated core symptoms of post-COVID-19 condition, used for a working definition of the condition, is essential to adequately study pathophysiological mechanisms,
2
Confronting our next national health disaster—long-haul COVID.
which is especially important given the risk of simple psychogenic explanations and the resulting consequences for patients.
24
Ballering A
olde Hartman T
Rosmalen J
Long COVID-19, persistent somatic symptoms and social stigmatisation.
Our results support a working definition at least based on the core symptoms, given the improved sensitivity ratio between cases and controls compared with a broader definition. These core symptoms were increased at 3–5 months after COVID-19, and are likely to limit functioning, prompt help-seeking, and have plausible underlying pathophysiological mechanisms. Nevertheless, research shows that COVID-19 might also affect brain functioning and mental health.
32
Santomauro DF
Mantilla Herrera AM
Shadid J
et al.
Global prevalence and burden of depressive and anxiety disorders in 204 countries and territories in 2020 due to the COVID-19 pandemic.
,
33
Douaud G
Lee S
Alfaro-Almagro F
et al.
SARS-CoV-2 is associated with changes in brain structure in UK Biobank.
Therefore, future research should not overlook mental health symptoms (eg, depression and anxiety symptoms), nor additional post-infectious symptoms that were not assessed in this study (eg, brain fog, insomnia, and post-exertional malaise). Additionally, future intersectional research should assess how ethnicity, gender, age, socioeconomic status, other social identities, and the presence of underlying chronic diseases are associated with symptom dynamics surrounding COVID-19 and risk of post-COVID-19 condition. Further research will focus on the clustering of COVID-19 symptoms in participants, and whether symptom clusters are associated with subtypes and distinct pathophysiological mechanisms underlying post-COVID-19 condition. We will also study genetic and environmental risk factors, and how post-COVID-19 condition affects (work) functioning and wellbeing. Additionally, as research suggests that vaccination before SARS-CoV-2 infection only partly mitigates the risk of long-term symptom sequelae 6 months after COVID-19,
34
Long COVID after breakthrough SARS-CoV-2 infection.
further studies should assess the effect of SARS-CoV-2 vaccination and the timing thereof, and the effect of SARS-CoV-2 variants, on symptom dynamics in both adults and children.
In conclusion, we present a starting point for core symptoms that could define post-COVID-19 condition, offer an improved working definition of post-COVID-19 condition, and provide a reliable prevalence estimate in the general population of the northern region of the Netherlands corrected for pre-existing symptoms and symptoms in participants without infection. Taking into account those symptoms that increased in severity and could be attributed to COVID-19, while correcting for seasonal fluctuations and non-infectious health aspects of the pandemic on symptom dynamics,
2
Confronting our next national health disaster—long-haul COVID.
,
5
Long COVID or post-COVID-19 syndrome: putative pathophysiology, risk factors, and treatments.
,
12
Amin-Chowdhury Z
Ladhani SN
Causation or confounding: why controls are critical for characterizing long COVID.
we found that about one in every eight patients are affected by persistent symptoms after COVID-19. This finding shows that post-COVID-19 condition is an urgent problem with a mounting human toll.
AVB analysed the data, conceptualised the analyses, and wrote the first version of the manuscript. SKRvZ and TCoH helped with conceptualising the analyses, interpreting the results, and critically revised the manuscript. AVB and SKRvZ accessed and verified the reported underlying data. JGMR conceived the study’s design, helped conceptualise the analyses, interpreted the results, and critically revised the manuscript. The Lifelines Corona Research Initiative collected the data.
No effective pharmacological or non-pharmacological interventions exist for patients with long COVID. We aimed to describe recovery 1 year after hospital discharge for COVID-19, identify factors associated with patient-perceived recovery, and identify potential therapeutic targets by describing the underlying inflammatory profiles of the previously described recovery clusters at 5 months after hospital discharge.
Methods
The Post-hospitalisation COVID-19 study (PHOSP-COVID) is a prospective, longitudinal cohort study recruiting adults (aged ≥18 years) discharged from hospital with COVID-19 across the UK. Recovery was assessed using patient-reported outcome measures, physical performance, and organ function at 5 months and 1 year after hospital discharge, and stratified by both patient-perceived recovery and recovery cluster. Hierarchical logistic regression modelling was performed for patient-perceived recovery at 1 year. Cluster analysis was done using the clustering large applications k-medoids approach using clinical outcomes at 5 months. Inflammatory protein profiling was analysed from plasma at the 5-month visit. This study is registered on the ISRCTN Registry, ISRCTN10980107, and recruitment is ongoing.
Findings
2320 participants discharged from hospital between March 7, 2020, and April 18, 2021, were assessed at 5 months after discharge and 807 (32·7%) participants completed both the 5-month and 1-year visits. 279 (35·6%) of these 807 patients were women and 505 (64·4%) were men, with a mean age of 58·7 (SD 12·5) years, and 224 (27·8%) had received invasive mechanical ventilation (WHO class 7–9). The proportion of patients reporting full recovery was unchanged between 5 months (501 [25·5%] of 1965) and 1 year (232 [28·9%] of 804). Factors associated with being less likely to report full recovery at 1 year were female sex (odds ratio 0·68 [95% CI 0·46–0·99]), obesity (0·50 [0·34–0·74]) and invasive mechanical ventilation (0·42 [0·23–0·76]). Cluster analysis (n=1636) corroborated the previously reported four clusters: very severe, severe, moderate with cognitive impairment, and mild, relating to the severity of physical health, mental health, and cognitive impairment at 5 months. We found increased inflammatory mediators of tissue damage and repair in both the very severe and the moderate with cognitive impairment clusters compared with the mild cluster, including IL-6 concentration, which was increased in both comparisons (n=626 participants). We found a substantial deficit in median EQ-5D-5L utility index from before COVID-19 (retrospective assessment; 0·88 [IQR 0·74–1·00]), at 5 months (0·74 [0·64–0·88]) to 1 year (0·75 [0·62–0·88]), with minimal improvements across all outcome measures at 1 year after discharge in the whole cohort and within each of the four clusters.
Interpretation
The sequelae of a hospital admission with COVID-19 were substantial 1 year after discharge across a range of health domains, with the minority in our cohort feeling fully recovered. Patient-perceived health-related quality of life was reduced at 1 year compared with before hospital admission. Systematic inflammation and obesity are potential treatable traits that warrant further investigation in clinical trials.
Funding
UK Research and Innovation and National Institute for Health Research.
Introduction
As of April, 2022, more than 500 million cases of SARS-CoV-2 infection have been reported worldwide,
1
Johns Hopkins University Coronavirus resource centre.
with 21·7 million cases in the UK
2
UK Government Coronavirus (COVID-19) in the UK.
and over 820 000 patients in the UK admitted to hospital for COVID-19. This population is at high risk of persisting health impairments 6 months after discharge associated with reduced physical function and health-related quality of life.
3
Evans RA
McAuley H
Harrison EM
et al.
Physical, cognitive, and mental health impacts of COVID-19 after hospitalisation (PHOSP-COVID): a UK multicentre, prospective cohort study.
,
4
Huang C
Huang L
Wang Y
et al.
6-month consequences of COVID-19 in patients discharged from hospital: a cohort study.
It is essential to understand both the longer-term trajectory of recovery to identify ongoing health-care needs and the required response by health-care systems and policy makers for this already large and ever-increasing population.
Much remains unknown about the longer-term sequelae of COVID-19. In the largest cohort study to date from Wuhan, China, nearly half of patients had persistent symptoms 12 months after discharge from hospital for COVID-19.
5
Huang L
Yao Q
Gu X
et al.
1-year outcomes in hospital survivors with COVID-19: a longitudinal cohort study.
6–12 months after discharge, patients had no change in 6-min walk distance, but had some improvement in the results of pulmonary imaging.
5
Huang L
Yao Q
Gu X
et al.
1-year outcomes in hospital survivors with COVID-19: a longitudinal cohort study.
Research in context
Evidence before this study
We systematically searched PubMed and Embase databases for large studies (>1000 participants) reporting 1-year follow-up data for patients admitted to hospital with COVID-19, published between Jan 1, 2021, and Nov 7, 2021, without language restrictions. Search terms related to COVID-19 (“COVID-19”, “COVID-2019”, “SARS-CoV-2”, “2019-nCoV”, “2019-SARS-CoV-2”), hospitalisation (“hospital*”), and long-term follow-up (“survivor*”, “recover*”, “persistent”, “follow up”, “long term”, “sequela*”, “long Covid”) were used. A large prospective cohort study from Wuhan, China (n=1276), showed that 49% of patients reported at least one persistent symptom during a follow-up clinic visit at 12 months after discharge from hospital with COVID-19; no significant improvement in exercise capacity was observed between 6-month and 12-month visits. Another two large cohort studies in China (n=2433) and Spain (n=1950) with 1-year follow-up data from telephone interviews showed that 45% (China study) and 81% (Spain study) of patients reported at least one residual COVID-19 symptom. However, no previous studies have compared the trajectories of COVID-19 recovery in patients classified by different clinical phenotypes, and we found no large studies investigating the association between systemic inflammation and ongoing health impairments after COVID-19 with or without hospitalisation.
Added value of this study
In a diverse population of adults following hospital admission with COVID-19, our large UK prospective, multicentre study reports several novel findings: the minority felt fully recovered at 1 year with minimal recovery from 5 months across any health domain; female sex and obesity were associated with being less likely to feel fully recovered at 1 year; several inflammatory mediators were increased in individuals with the most severe physical, mental health, and cognitive impairments compared with individuals with milder ongoing impairments.
Implications of all the available evidence
Both pharmacological and non-pharmacological interventions are urgently needed to improve the ongoing burden following hospitalisation for COVID-19 both for individuals and health-care systems. Our findings support the use of a precision-medicine approach with potential treatable traits of systemic inflammation and obesity.
The mechanisms underlying long-term persistence of symptoms are unknown. A potential hypothesis is that the hyperinflammation associated with acute COVID-19 leads to a persistent inflammatory state following COVID-19, associated with dysregulated immunity and multiorgan dysfunction. Although multiple studies have highlighted increased inflammatory markers, including interleukin-6 (IL-6), associated with severity of acute illness,
6
Filbin MR
Mehta A
Schneider AM
et al.
Longitudinal proteomic analysis of severe COVID-19 reveals survival-associated signatures, tissue-specific cell death, and cell-cell interactions.
,
7
Thwaites RS
Sanchez Sevilla Uruchurtu A
Siggins MK
et al.
Inflammatory profiles across the spectrum of disease reveal a distinct role for GM-CSF in severe COVID-19.
no large studies have investigated the association between systemic inflammation and ongoing health impairments after COVID-19.
No effective treatments exist for long COVID or post-COVID-19 condition. Long COVID is defined by the National Institute for Health and Care Excellence (NICE) as ongoing symptoms beyond 4–12 weeks after COVID-19 and post-COVID-19 condition by WHO as occurring “in individuals with a history of probable or confirmed SARS CoV-2 infection, usually 3 months from the onset of COVID-19 with symptoms and that last for at least 2 months and cannot be explained by an alternative diagnosis”.
8
National Institute for Health and Care Excellence COVID-19 rapid guideline: managing the long-term effects of COVID-19.
,
9
WHO A clinical case definition of post COVID-19 condition by a Delphi consensus.
Improved characterisation of this population with an emphasis on elucidating underlying mechanisms is needed to identify potential therapeutic targets. We previously described four clusters of patients according to clinical recovery (very severe, severe, moderate with cognitive impairment, and mild) defined by severity of ongoing physical health, mental health, and cognitive impairment 5 months after a hospital admission with COVID-19.
3
Evans RA
McAuley H
Harrison EM
et al.
Physical, cognitive, and mental health impacts of COVID-19 after hospitalisation (PHOSP-COVID): a UK multicentre, prospective cohort study.
We sought to answer the following questions using the ongoing post-hospitalisation COVID-19 study (PHOSP-COVID) longitudinal study cohort: first, what proportion of patients discharged from hospital with COVID-19 felt fully recovered 1 year later and what are the characteristics associated with non-recovery? Second, are there inflammatory mediators associated with severity of ongoing health impairments and therefore potential therapeutic targets? Third, are there differences in the trajectory of recovery at 1 year after discharge across different health domains and between our previously described clusters?
Methods
Study design and participants
Recruitment in the PHOSP-COVID multicentre, prospective cohort study has been described previously.
3
Evans RA
McAuley H
Harrison EM
et al.
Physical, cognitive, and mental health impacts of COVID-19 after hospitalisation (PHOSP-COVID): a UK multicentre, prospective cohort study.
In brief, we recruited patients aged 18 years and older who were discharged from 83 National Health Service (NHS) hospitals across the four UK nations following admission to a medical assessment unit or ward for confirmed or clinician-diagnosed COVID-19 before March 31, 2021. The current analysis involves participants who consented to attend two additional in-person research visits (tier 2, 39 sites; appendix p 16) within 1 year after discharge alongside routine clinical care.
Written informed consent was obtained from all study participants. The study was approved by the Leeds West Research Ethics Committee (20/YH/0225) and is registered on the ISRCTN Registry (ISRCTN10980107).
Procedures
Participants were invited to attend research visits at 2–7 months after discharge (5-month visit) and at 10–14 months (1-year visit). Participants were also able to attend a 1-year visit only if they were outside the time period for a 5-month visit at the time of consent and were discharged before Nov 30, 2020. The core set of data variables collected at each visit and included in this study are listed in the appendix (pp 17–18). These variables included baseline demographics, information about disease severity and treatment during their hospital admission, as well as symptoms using a bespoke study-specific questionnaire and other patient-reported outcome measures for anxiety (Generalised Anxiety Disorder 7-item scale [GAD-7]), depression (Patient Health Questionnaire-9 [PHQ-9]), post-traumatic stress disorder (Post-Traumatic Stress Disorder Checklist for the Diagnostic and Statistical Manual of Mental Disorders [PCL-5]), fatigue (Functional Assessment of Chronic Illness Therapy—Fatigue [FACIT-Fatigue]), breathlessness (Dyspnoea-12), and health-related quality of life (EQ-5D-5L), physical performance measures including the short physical performance battery (SPPB) and the incremental shuttle walk test (ISWT), cognitive impairment using the Montreal Cognitive Assessment (MoCA), and pulmonary function tests and blood test results reflecting multiorgan function and systemic inflammation obtained at clinical and research visits (appendix p 17). Patients were also asked to complete the EQ-5D-5L, Washington Group Short Set Functioning (WG-SS) scale, and visual analogue scale for breathlessness and fatigue retrospectively to assess their perceived pre-COVID-19 health (appendix pp 17–18). Plasma samples obtained at the 5-month visit were analysed using the Olink Explore 384 Inflammation panel (Uppsala, Sweden). Sample processing and assay details are provided in the appendix (p 13).
The primary outcome for this analysis was patient-perceived recovery, assessed using a study-specific questionnaire and the question “Do you feel fully recovered?”; participants could answer “yes”, “no”, or “not sure”. Other secondary outcomes included symptoms since COVID-19 hospital admission that were collected on the bespoke study-specific questionnaire, validated patient-reported outcome questionnaires, and physiological measures (including physical performance and spirometry; appendix p 17).
Statistical analysis
Continuous variables were presented as median (IQR) or mean (SD). Binary and categorical variables were presented as n (%; by row or by column as indicated in table legends). Participants were stratified by patient-perceived recovery: yes (recovered), not sure, or no (not recovered).
Missing data were reported within each variable and per category. Within visit, a χ2 test was used to identify differences in proportions across multiple categories. To test differences across categories, ANOVA was used for normally distributed continuous data and Kruskal Wallis test for non-normally distributed continuous data. For paired data between the 5-month and 1-year visit, a McNemar’s χ2 test with continuity correction was used for binary variables and a McNemar’s χ2 test was used for variables with more than two levels. We used a paired t test for normally distributed continuous data and a Wilcoxon signed-rank test for non-normally distributed continuous data. As previously described,
3
Evans RA
McAuley H
Harrison EM
et al.
Physical, cognitive, and mental health impacts of COVID-19 after hospitalisation (PHOSP-COVID): a UK multicentre, prospective cohort study.
univariable and hierarchical multivariable logistic regression models (admission hospital included as random effect) were used to explore risk factors associated with patient-perceived recovery. Missing data were addressed using multiple imputation (ten datasets, ten iterations, and final models combined using Rubin’s Rules), with the outcome used in imputation models, but not itself imputed.
To assess any potential bias as a result of patients not yet attending their 1-year visit at the time of analysis (Oct 6, 2021), we compared characteristics and patient-perceived recovery between those who attended a 1-year visit with those who had not yet attended but were discharged from hospital during the same range of dates. Multiple imputation was used to complete missing outcomes for participants who had not yet attended their 1-year follow-up. The imputation model used age, sex, ethnicity, index of multiple deprivation, and WHO clinical progression scale and all comorbidity variables. Ten datasets with ten iterations were created and combined using Rubin’s rules.
In this cohort, we repeated our previous unsupervised cluster analysis
3
Evans RA
McAuley H
Harrison EM
et al.
Physical, cognitive, and mental health impacts of COVID-19 after hospitalisation (PHOSP-COVID): a UK multicentre, prospective cohort study.
of patient recovery, which was measured using symptom questionnaires (patient-reported outcome measures) and physical performance and cognitive assessment data (Dyspnoea-12, FACIT-Fatigue, GAD-7, PHQ-9, PCL-5, SPPB, and MoCA as continuous variables) from the 5-month visit (discharge dates March 7, 2020, to April 18, 2021) using the clustering large applications k-medoids approach.
10
Clustering large applications (Program CLARA).
Scores were centred, normalised, and transformed so that higher burden of disease represented higher values. A Euclidean distance metric was used and the optimal number of clusters chosen using a silhouette plot. Cluster membership was determined for each individual using 5-month visit data. Characteristics at 1 year and change in characteristics between 5 months and 12 months are presented as cluster-stratified tables. All tests were two-tailed and p values of less than 0·05 were considered statistically significant. We did not adjust for multiple testing.
Plasma protein concentrations were compared between clusters using the mildest recovery cluster as baseline and using multinomial regression with age, body-mass index (BMI), and number of comorbidities as covariates (appendix p 14). Significance was defined as a p value of less than 0·1 after false discovery rate adjustment for multiple testing.
We used R (version 3.6.3) with the finalfit, tidyverse, mice, cluster, ggplot2, ggalluvial, radiant, dabestr, and recipes packages for all statistical analyses.
Role of the funding source
The funder of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report.
Results
At the time of analysis (Oct 6, 2021), 2468 participants (discharged from hospital between March 7, 2020, and April 18, 2021) had attended a 5-month visit (median 5 months [IQR 4-6] after discharge, 148 [6·0%] of whom were excluded; figure 1). 924 (37·4%) participants (discharged Feb 28, 2020, to Nov 28, 2020) returned for a 1-year visit (13 months [12–13] after discharge) and 807 (32·7%) participants attended both visits (figure 1). The individual and hospital admission characteristics including severity of acute illness were similar between those who attended the 5 five-month visit, 1-year visit, and both visits, except for the proportion of patients who received acute treatment with corticosteroids (table 1).
Table 1Characteristics of participants who had a 5-month visit, a 1-year visit, and both visits
Data are n (%), mean (SD), or median (IQR). Percentages are calculated by category after exclusion of missing data for that variable.
At 5 months, 1965 (84·7%) of 2320 patients, and at 1 year 804 (34·7%) patients, had both attended a research visit and answered whether or not they felt fully recovered (figure 1). At 5 months, 501 (25·5%) of 1965 patients felt fully recovered, with 385 (19·6%) feeling not sure and 1079 (54·9%) not recovered (figure 2A; appendix p 19). At 1 year, 232 (28·9%) of 804 patients felt fully recovered, 180 (22·4%) were not sure, and 392 (48·8%) were not recovered (figure 2A; appendix p 19). Similar proportions were observed in those with paired data (appendix p 22). The individual responses were also similar between 5 months and 1 year (appendix p 39).
Figure 2Patient-perceived recovery at 1 year
Show full caption
(A) Compared with patient-perceived recovery at 5 months. (B) Risk factors for being less likely to recover. (C) Compared according to the four clusters. (D) Compared with health-related quality of life (assessed by the EQ-5D-5L utility index). WHO clinical progression scale classes are as follows: 3–4 indicates no continuous supplemental oxygen needed; 5 indicates continuous supplemental oxygen only; 6 indicates continuous positive airway pressure or bi-level positive pressure ventilation or high-flow nasal oxygen; and 7–9 indicates invasive mechanical ventilation or other organ support. The forest plot of the patient and admission characteristics associated with patient-perceived recovery at 1 year used multivariable logistic regression and multiple imputation. EQ-5D-5L score before COVID-19 was retrospectively completed by participants. BMI=body-mass index.
In multivariable analysis, female sex (odds ratio [OR] 0·68 [95% CI 0·46–0·99]), BMI 30 kg/m2 or greater (0·50 [0·34–0·74]), and receiving invasive mechanical ventilation (WHO category 7–9; 0·42 [0·23–0·76]) were all independent factors associated with being less likely to recover at 1 year (figure 2B; appendix p 25). We found no effect of receiving systemic corticosteroids (1·05 [0·66–1·65]) during the acute admission on patient-perceived recovery at 1 year for the whole cohort (figure 2B; appendix p 26). We also found no effect of time from discharge to the research visit (1·00 [1·00–1·01]).
751 participants discharged between Feb 28, 2020, and Nov 28, 2020, did not return for a 1-year visit but had similar characteristics and 5-month recovery status to the 924 participants who had attended (appendix p 27). The proportion of recovered patients was similar after imputation for outcome (499 [29·8%] of 1675).
For the 5-month dataset, the previously identified four clusters
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Evans RA
McAuley H
Harrison EM
et al.
Physical, cognitive, and mental health impacts of COVID-19 after hospitalisation (PHOSP-COVID): a UK multicentre, prospective cohort study.
were confirmed using participants with complete data for the cluster analysis (n=1636; figure 1). The distribution of the four clusters was very severe physical and mental health impairment (n=319 [19·5%]), severe physical and mental health impairment (n=493 [30·1%]), moderate physical health impairment with cognitive impairment (n=179 [10·9%]), and mild mental and physical health impairment (n=645 [39·4%]; appendix p 29). 664 (86·7%) of 766 individuals included in the previous study
3
Evans RA
McAuley H
Harrison EM
et al.
Physical, cognitive, and mental health impacts of COVID-19 after hospitalisation (PHOSP-COVID): a UK multicentre, prospective cohort study.
were reassigned to the same recovery cluster as before; the cluster of moderate with cognitive impairment had the most assignment alterations (60 [47·2%] of 127). Characteristics of individuals in each recovery cluster are shown in the appendix (p 30). Compared with the mild cluster, the very severe cluster had a higher proportion of women (165 [53·9%] of 306 vs 177 [28·4%] of 624) and obesity (BMI ≥30 kg/m2; 204 [70·8%] of 288 vs 288 [50·2%] of 568).
After quality control, plasma proteome data for 296 protein features and complete clinical data for cluster assignment were available at 5 months for 626 participants: 111 (17·7%) in the very severe cluster, 173 (27·6%) in the severe cluster, 73 (11·7%) in the cluster moderate with cognitive impairment, and 269 (43·0%) in the mild cluster. Age, BMI, and two or more comorbidities were associated with cluster membership, whereas receiving invasive mechanical ventilation during the acute illness was not (analysis done in participants with plasma proteome data and a cluster assignment; appendix p 32). After adjustment for age, BMI, and comorbidity count, 13 proteins were significantly increased in participants in the very severe recovery cluster compared with those in the mild cluster (appendix p 33; figure 3). These proteins were trefoil factor 2 (TFF2), transforming growth factor α (TGFA), lysosomal associated membrane protein 3 (LAMP3), CD83 molecule (CD83), galectin-9 (LGALS9), urokinase plasminogen activator surface receptor (PLAUR), interleukin-6 (IL-6), erythropoietin (EPO), FMS-related receptor tyrosine kinase 3 ligand (FLT3LG), agrin (AGRN), secretoglobin family 3A member 2 (SCGB3A2), follistatin (FST), and C-type lectin domain family 4 member D (CLEC4D; appendix p 33). Additionally, IL-6 and CD70 molecule were significantly increased in the moderate with cognitive impairment cluster compared with the mild cluster (appendix p 34).
Figure 3Volcano plots representing multinomial regression association results for comparison of 296 proteins between the four clinical phenotypes
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Results corrected for age, body-mass index, and number of comorbidities, comparing 296 proteins between very severe physical and mental health impairment and mild physical and mental health impairment clusters (A), severe physical and mental health impairment and mild physical and mental health impairment clusters (B), and moderate physical health impairment with cognitive impairment and mild physical and mental health impairment clusters (C). The red horizontal line represents an unadjusted p<0·05 threshold. Proteins that were significantly differentially expressed (compared with the reference mild cluster) after FDR adjustment are indicated in red; FDR cutoff used was 0·1. FDR=false detection rate.
The ten most common persistent symptoms at 1 year after discharge were fatigue (463 [60·1%] of 770 patients), aching muscles (442 [54·6%] of 809), physically slowing down (429 [52·9%] of 811), poor sleep (402 [52·3%] of 769), breathlessness (395 [51·4%] of 769), joint pain or swelling (382 [47·6%] of 803), slowing down in thinking (377 [46·7%] of 808), pain (359 [46·6%] of 770), short-term memory loss (360 [44·6%] of 808), and limb weakness (341 [41·9%] of 813; appendix p 35). Overall, symptoms were unchanged in prevalence from 5 months to 1 year, with small reductions in rates of limb weakness (47·6% at 5 months vs 41·7% at 1 year; p=0·010), paraesthesia (40·6% vs 35·2%; p=0·014), and balance problems (34·9% vs 30·0; p=0·0076). We found either no or minimal improvement in patient-reported outcome measures, physical function, cognitive impairment, or organ function at 1 year compared with 5 months after discharge (paired data in table 2 and presented stratified by patient-perceived recovery in appendix p 19). At 1 year, 147 [21·5%] of 684 patients had clinically relevant symptoms of anxiety, 169 (24·9%) of 680 participants had clinically relevant symptoms of depression, 68 (10·0%) of 680 had post-traumatic stress disorder, and 55 (8·8%) of 623 had significant cognitive impairment (table 2). Measures of symptoms and physical function were significantly different across participants who reported being fully recovered, not sure, or not fully recovered at 5 months and 1 year, but cognitive impairment and measures of organ function were not (except for forced vital capacity; table 2). Health-related quality of life was significantly different across participants who reported being fully recovered, not sure, or not recovered at both 5 months and 1 year (figure 2D; appendix p 19).
Table 2Patient-reported outcome measures, physical function, and organ function at 5 months, stratified by patient-perceived recovery and compared with outcome 1 year after hospital discharge
Data are n, n (%), mean (SD), or median (IQR). Percentages are calculated by category after exclusion of missing data for that variable. BNP=brain natriuretic peptide. DCCT/NGSP=Diabetes Control and Complications Trial and National Glycohemoglobin Standardization Program criteria. eGFR=estimated glomerular filtration rate. FACIT=Functional Assessment of Chronic Illness Therapy. FVC=forced vital capacity. GAD-7=Generalized Anxiety Disorder 7-item scale. ISWT=incremental shuttle walk test. MoCA=Montreal Cognitive Assessment. NA=not applicable. NT-BNP=N-terminal brain natriuretic peptide. PCL-5=Post-Traumatic Stress Disorder Checklist for theDiagnostic and Statistical Manual of Mental Disorders. PHQ-9=Patient Health Questionnaire-9. SPPB=short physical performance battery. VAS=visual analogue scale. WG-SS-SCo=Washington Group Short Set of Functioning Severity Continuum.
In addition to higher proportions of women and obesity (appendix p 30), at 1 year the very severe cluster was associated with a lower proportion of patients who reported feeling fully recovered (4 [4·7%] of 86 vs 107 [49·1%] of 218; figure 2C; reduced exercise capacity [ISWT 44·4% predicted vs 72·4% predicted]; greater number of symptoms [20 vs 4]; and greater proportion of patients with increased C-reactive protein concentration >5 mg/L [38·4% vs 14·5%]) compared with the mild cluster (table 3; figure 4A). A comparison of health outcomes across the four clusters between the 5-month and 1 year timepoints (n=602) showed minimal change across the two timepoints for the four clusters (table 3). In the very severe cluster, symptoms of anxiety, depression, breathlessness, and fatigue significantly improved between 5 months and 1 year, but with minimal change in physical performance and no overall change in systemic inflammation measured by C-reactive protein concentration (table 3). Cognitive impairment significantly improved at 1 year in the moderate with cognitive impairment cluster and was unchanged in the other clusters (table 3). Compared with patient-perceived health before COVID-19, decrements were seen at 5 months and sustained at 1 year across health-related quality of life (EQ-5D-5L; figure 4B), disability (WG-SS), and severity of breathlessness and fatigue experienced in the past 24 h (appendix p 43).
Table 3Comparison of the change in patient-reported outcome measures between 5 months and 1 year
Data are n, n (%), mean (SD), or median (IQR). Missing data are not included in %. FACIT=Functional Assessment of Chronic Illness Therapy. FVC=forced vital capacity. GAD-7=Generalized Anxiety Disorder 7-item scale. ISWT=incremental shuttle walk test. MoCA=Montreal Cognitive Assessment. NA=not applicable. PCL-5=Post-Traumatic Stress Disorder Checklist for theDiagnostic and Statistical Manual of Mental Disorders. PHQ-9=Patient Health Questionnaire-9. SPPB=short physical performance battery.
Figure 4Characteristics associated with the four recovery clusters
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(A) Patient characteristics, CRP concentration, exercise performance, and symptom count across the four clusters (error bars indicate IQR). (B) Health-related quality of life across the four clusters assessed before hospitalisation (patient estimate), and at 5 months and 1 year after discharge. EQ-5D-5L utility index stratified by cluster and pre-hospital health status assessed retrospectively. Very severe indicates the very severe physical and mental health impairment cluster, severe indicates the severe physical and mental health impairment cluster, moderate with cognitive indicates the moderate physical health impairment with cognitive impairment cluster, and mild indicates the mild physical and mental health impairment cluster. BMI=body-mass index. CRP=mean C-reactive protein concentration assessed at 1 year. IMV=invasive mechanical ventilation. ISWT=incremental shuttle walk test distance percentage predicted assessed at 1 year. *Median number of symptoms at 1 year.
Discussion
In adults admitted to hospital with COVID-19 in the UK, we found that a minority of participants felt fully recovered 1 year after hospital discharge, with minimal improvement after a 5-month assessment. The most common ongoing symptoms were fatigue, muscle pain, physically slowing down, poor sleep, and breathlessness. The major risk factors for not feeling fully recovered at 1 year were female sex, obesity, and receiving invasive mechanical ventilation during the acute illness. We found substantial impairments in health-related quality of life at 5 months and 1 year compared with retrospective self-reported scores before COVID-19. Cluster analysis using the 5-month assessments corroborated four different clusters: very severe, severe, moderate with cognitive impairment, and mild, which were based on the severity of physical, mental, and cognitive impairments with similar characteristics to those previously reported.
3
Evans RA
McAuley H
Harrison EM
et al.
Physical, cognitive, and mental health impacts of COVID-19 after hospitalisation (PHOSP-COVID): a UK multicentre, prospective cohort study.
We showed that obesity, reduced exercise capacity, a greater number of symptoms, and increased serum C-reactive protein concentration were associated with the more severe clusters.
3
Evans RA
McAuley H
Harrison EM
et al.
Physical, cognitive, and mental health impacts of COVID-19 after hospitalisation (PHOSP-COVID): a UK multicentre, prospective cohort study.
In the largest post-hospital cohort with systemic inflammatory profiling to date, inflammatory mediators consistent with persistent lung and systemic inflammation were increased in the very severe, moderate with cognitive impairment, and mild clusters. We therefore highlight traits to identify individuals at high risk of non-recovery and potential targetable pathways for interventions.
Comparing the systemic inflammatory profiling at 5 months after discharge between the very severe and mild cluster, the most increased protein concentration, TFF2, is a protein released with mucin from mucosal epithelium including lung and gastric mucosa. TFF2 has postulated roles in repair of damaged epithelium
11
An open-label, randomized trial of the combination of IFN-κ plus TFF2 with standard care in the treatment of patients with moderate COVID-19.
and, in combination with interferon-κ, reduced duration of infection in a small open-label randomised controlled trial of patients with acute COVID-19.
11
An open-label, randomized trial of the combination of IFN-κ plus TFF2 with standard care in the treatment of patients with moderate COVID-19.
In a study
6
Filbin MR
Mehta A
Schneider AM
et al.
Longitudinal proteomic analysis of severe COVID-19 reveals survival-associated signatures, tissue-specific cell death, and cell-cell interactions.
of patients during acute illness with COVID-19 using Olink Proteomics, IL-6 was the most upregulated protein at day 7 among patients who developed acute respiratory distress syndrome (ARDS) and subsequently died. Similarly, other proteins that we identified such as LAMP3, Gal-9, and CD83 are involved in T-cell macrophage and dendritic cell activation and were associated with increased morbidity and mortality during acute COVID-19 infection.
12
Tserel L
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Unbiased analysis of temporal changes in immune serum markers in acute COVID-19 infection with emphasis on organ failure, anti-viral treatment, and demographic characteristics.
These changes suggest persistent mucosal epithelial abnormalities and inflammatory cell activation. Increased serum concentrations of the C-terminal fragment of agrin have been reported in older adults (aged age 65–87 years) with sarcopenia, possibly related to breakdown of the neuromuscular junction.
15
Hettwer S
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Kucsera S
et al.
Elevated levels of a C-terminal agrin fragment identifies a new subset of sarcopenia patients.
The increased agrin concentrations seen here might therefore have contributed to the high prevalence of physical impairment. Interestingly, in the moderate with cognitive impairment cluster versus the mild cluster, IL-6 and CD70 concentrations were increased, suggesting possible neuroinflammation contributing to the cognitive impairment because CD70 has been implicated in inflammation in the CNS
16
Dhaeze T
Tremblay L
Lachance C
et al.
CD70 defines a subset of proinflammatory and CNS-pathogenic TH1/TH17 lymphocytes and is overexpressed in multiple sclerosis.
via a role in differentiation of proinflammatory pathogenic lymphocytes. We found small improvements at 1 year in cognition in the moderate with cognitive impairment cluster, indicating that some of this deficit was not pre-existing and is potentially modifiable; however, considerable deficit persisted at 1 year. The associations with the inflammatory mediators remained after adjusting for age, BMI, and number of comorbidities, and the proportion having received invasive mechanical ventilation was similar across the clusters—all factors known to be associated with systemic inflammation.
17
Griffith DM
Vale ME
Campbell C
Lewis S
Walsh TS
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Taken together, the increased mediators provide biological plausibility for the persistent severe impairments seen in physical health, mental health, and cognitive impairment after COVID-19.
The limited recovery from 5 months to 1 year after hospitalisation in our study across symptoms, mental health, exercise capacity, organ impairment, and quality-of-life is striking. There are few similar detailed, prospective, longitudinal studies for patients hospitalised with COVID-19, but in this larger cohort we support those findings of minimal recovery.
18
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Although the large-scale study from Wuhan, China, suggests a greater magnitude of recovery compared with our findings, new-onset symptoms persisted in half of the patients (620 of 1272).
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Notably, the Wuhan cohort included a smaller proportion of patients with severe acute illness than ours did, with only 1% requiring invasive mechanical ventilation and 7% requiring high flow nasal oxygen or continuous positive airway pressure. The Wuhan cohort also had fewer pre-existing comorbidities and a higher proportion of never-smokers compared with patients in our study. In patients with non-COVID-19-related ARDS, little recovery in health-related quality of life is observed beyond 6 months after hospital discharge, but larger improvements in walking distance have been found
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than we report following COVID-19 in our cohort, over 70% of whom did not receive invasive mechanical ventilation. In non-hospitalised patients after COVID-19, the proportion that develop long COVID appears to be lower than in those admitted to hospital with COVID-19.
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The responses for patient-perceived recovery were discriminatory across all the patient-reported outcome measures and exercise measures, providing additional validity for this outcome measure. We found female sex and obesity were major risk factors for not recovering at 1 year, supporting results from smaller cohorts
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Female sex was similarly associated with worse recovery for fatigue, mental health, and lung function at 12 months in the Wuhan cohort.
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In our clusters, female sex and obesity were also associated with more severe ongoing health impairments, including reduced exercise performance and health-related quality of life at 1 year, potentially highlighting a group that might need higher-intensity interventions such as supervised rehabilitation. Health-related quality of life before COVID-19 was substantially greater than at 5 months after discharge across all four clusters, indicating that the persistent burden of impaired physical and mental health is not simply explained by pre-existing morbidity. The total number and range of ongoing symptoms at 1 year was striking, positively associated with the severity of long COVID, and emphasises the multisystem nature of long COVID. Other studies have shown that the number of symptoms during the acute illness was associated with the likelihood of developing long COVID.
29
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Whether the number of ongoing symptoms—a simple, widely available measure—could underpin a future risk score deserves further attention. Taken together, we suggest that our data will help to inform decisions about patient stratification for follow-up after hospital discharge. We advocate a proactive approach because of the high proportion of patients who do not recover, highlighting the usefulness of a screening questionnaire to assess whether patients feel fully recovered; the total number of symptoms might be a guide to the intensity or complexity of care required. Similar to our 5-month data
3
Evans RA
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Physical, cognitive, and mental health impacts of COVID-19 after hospitalisation (PHOSP-COVID): a UK multicentre, prospective cohort study.
, we highlight the need for a holistic assessment including mental health, physical function, and cognitive impairment. Any assessment of ongoing organ impairment will need to be further individualised.
No specific therapeutics exist for long COVID and our data highlight that effective interventions are urgently required. Our findings of persistent systemic inflammation, particularly in those in the very severe and moderate with cognitive impairment clusters, suggest that these groups might respond to anti-inflammatory strategies. The upregulation of IL-6 suggests that anti-IL-6 biologics that were successful for patients admitted to hospital with COVID-19
30
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might also have a place in the treatment of long COVID. Similarly, activation of the urokinase-type plasminogen activator receptor pathway suggests that IL-1 activation might play a role, with soluble uPAR a biomarker in acute COVID-19 associated with good response to the recombinant IL-1 receptor antagonist anakinra.
31
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Impaired exercise capacity was also associated with the more severe clusters and showed minimal improvement at 1 year (below the minimum clinically important difference for other long-term conditions).
32
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34
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Available therapies for some adults with long COVID include rehabilitation,
35
Spruit MA
Holland AE
Singh SJ
Tonia T
Wilson KC
Troosters T
COVID-19: interim guidance on rehabilitation in the hospital and post-hospital phase from a European Respiratory Society and American Thoracic Society-coordinated international task force.
but the optimal exercise prescription is contentious because of concerns of post-exertional symptom exacerbation. Our data suggest a high prevalence of musculoskeletal symptoms including muscle ache, fatigue, breathlessness, physically slowing down, and limb weakness.
5
Huang L
Yao Q
Gu X
et al.
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,
16
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This finding supports the need to investigate rehabilitation in combination with other therapies to improve skeletal muscle function, such as mitochondrial energetics, mitophagy enhancers, and drugs to combat cell senescence (associated with ageing).
The concordance of the severity of physical and mental health impairment in long COVID highlights the need not only for close integration between physical and mental health care for patients with long COVID, including assessment and interventions, but also for knowledge transfer between health-care professionals to improve patient care. The finding also suggests the need for complex interventions that target both physical and mental health impairments to ameliorate symptoms. However, specific therapeutic approaches to manage post-traumatic stress disorder might be needed.
36
Martin A
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Peterson G
Thomas J
Christenson JK
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With obesity being associated with both non-recovery and severity of long COVID, whether weight reduction using combined pharmacological and non-pharmacological approaches can ameliorate long COVID warrants further investigation. Beyond diet and lifestyle interventions, GLP-1 analogues have been reported to achieve clinically important weight reduction in adults.
37
Wilding JPH
Batterham RL
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et al.
Once-weekly semaglutide in adults with overweight or obesity.
Our cohort study is ongoing, and we report these 1-year findings to help direct clinical care and further investigation. However, there are limitations. There will be selection bias for participants returning for a 1-year visit, although we have not found overt differences between the demographics or 5-month recovery status between attendees and non-attendees of the 1-year visit. Our cohort has a higher proportion of patients with COVID-19 requiring invasive mechanical ventilation than is typically seen in UK hospitals,
38
Docherty AB
Mulholland RH
Lone NI
et al.
Changes in in-hospital mortality in the first wave of COVID-19: a multicentre prospective observational cohort study using the WHO Clinical Characterisation Protocol UK.
and therefore our results might not be directly generalisable to the wider population. We also had a lower-than-expected proportion of women, which might mean that the wider population have worse outcomes than we report because women appear to have worse recovery. To reduce uncertainty of the effect of pre-existing illness, we asked participants whether they felt fully recovered (ie, back to their normal selves). We also asked participants retrospectively to estimate their pre-COVID-19 health status, including the most prevalent symptoms, disability, and health-related quality of life; we recognise that there might be recall bias. Data linkage to electronic patient records is in process but not currently available; therefore, in the current report, pre-existing comorbidities were self-reported and data regarding hospital admissions and mortality in the first year are unavailable. Our study suggests that persistent inflammation might underlie ongoing impairment in some participants; the specific mechanisms underlying this signal require further investigation and replication. We described several associations with more severe health impairments at 1 year. Our findings cannot confirm causality but suggest that these associations should be further investigated as part of mechanistic studies and clinical trials. Our results require interpretation in the context of the COVID-19 pandemic. Our 1-year findings included patients discharged from hospital in 2020 and therefore would not include those infected with newer SARS-CoV-2 variants such as B.1.1.529 (omicron) and included patients who would not have been vaccinated before contracting COVID-19. Although our data are relevant to patients discharged under similar conditions, further research is needed to understand the effect of current acute care, newer SARS-CoV-2 variants, and vaccination status before and after contracting COVID-19.
In summary, our study highlights an urgent need for health-care services to support this large and rapidly increasing patient population in whom a substantial burden of symptoms exists, including reduced exercise capacity and large decrements in health-related quality of life 1 year after hospital discharge. Without effective treatments, long COVID could become a highly prevalent new long-term condition. Our study also provides a rationale for investigating treatment strategies for long COVID with a precision-medicine approach to target treatments to the relevant phenotype to restore health-related quality of life.
Writing group (on behalf of the PHOSP-COVID Collaborative Group)
Rachael A Evans*, Olivia C Leavy, Matthew Richardson, Omer Elneima, Hamish J C McAuley, Aarti Shikotra, Amisha Singapuri, Marco Sereno, Ruth M Saunders, Victoria C Harris, Linzy Houchen-Wolloff, Raminder Aul, Paul Beirne, Charlotte E Bolton, Jeremy S Brown, Gourab Choudhury, Nawar Diar Bakerly, Nicholas Easom, Carlos Echevarria, Jonathan Fuld, Nick Har, John R Hurst, Mark G Jones, Dhruv Parekh, Paul Pfeffer, Najib M Rahman, Sarah L Rowland-Jones, Ajay M Shah, Dan G Wootton, Trudie Chalder, Melanie J Davies, Anthony De Soyza, John R Geddes, William Greenhalf, Neil J Greening, Liam G Heaney, Simon Heller, Luke S Howard, Joseph Jacob, R Gisli Jenkins, Janet M Lord, William D-C Man, Gerry P McCann, Stefan Neubauer, Peter J M Openshaw, Joanna C Porter, Matthew J Rowland, Janet T Scott, Malcolm G Semple, Sally J Singh, David Thomas, Mark Toshner, Keir E Lewis, Ryan S Thwaites, Andrew Briggs, Annemarie B Docherty, Steven Kerr, Nazir I Lone, Jennifer Quint, Aziz Sheikh, Mathew Thorpe, Bang Zheng, James D Chalmers, Ling-Pei Ho, Alex Horsley, Michael Marks, Krisnah Poinasamy, Betty Raman, Ewen M Harrison, Louise V Wain*, Christopher E Brightling*.
*Joint first and last authors and contributed equally.
Contributors
The manuscript was initially drafted by RAE, CEBr, and LVW, and further developed by the writing committee. CEBr, RAE, LVW, OE, HJCM, AShi, ASi, MJD, ABD, NIL, AShe, JDC, L-PH, AH, MM, KP, and BR made substantial contributions to the conception and design of the work. RAE, ASi, MS, RMS, VCH, RA, PB, CEBo, JSB, GC, NDB, NE, CE, JF, NH, JRH, MGJ, DP, PP, NMR, SLR-J, AMS, DGW, JDC, L-PH, AH, MM, and WD-CM made substantial contributions to the acquisition of data. CEBr, RAE, LVW, OCL, MR, OE, HJCM, MS, TC, MJD, ADS, JRG, WG, NJG, LGH, SH, LSH, JJ, RGJ, JML, WD-CM, GPM, SN, PJMO, JCP, JQ, MJR, JTS, MGS, SJS, MTo, KEL, RST, AB, ABD, SK, NIL, AShe, MTh, BZ, JDC, L-PH, AH, MM, KP, BR, EMH, LH-W, and DT made contributions to the analysis, or interpretation of data for the work. All authors contributed to data interpretation, critical review and revision of the manuscript, and final approval of the version to be published. RAE, HJCM, and OCL have accessed and verified the data. RAE, CEBr, and LVW were responsible for the decision to submit the manuscript, and are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.
Declaration of interests
AB declares that their institute was awarded a grant from the UK National Institute for Health Research (NIHR) to complete this work and receives consulting fees from Roche, Merck, and GlaxoSmithKline. ADS declares grants to their institutes from GlaxoSmithKline, US COPD Foundation, Pfizer, and AstraZeneca; consulting fees were provided to their institute from 30T and personal consultations fees were received from AstraZeneca and Gilead; payments for lectures and presentations were received from GlaxoSmithKline, AstraZeneca, and Gilead; travel support to attend meetings was provided by GlaxoSmithKline and AstraZeneca; personal and institutional payments were received for participation on a data safety monitoring board/advisory board from Bayer. AH declares that their institute was awarded a grant from UK Research and Innovation (UKRI) and NIHR to complete this work, and from NIHR Manchester Clinical Research Facility to support study delivery and NIHR Manchester Biomedical Research Centre (BRC) for personal funding and institutional payments to support grant-funded research from NIHR, UK Medical Research Council (MRC), Cystic Fibrosis Trust, Cystic Fibrosis Foundation, North West Lung Centre Charity, and Moulton Trust; the author declares consulting fees from Mylan Pharmaceuticals for advisory board participation and payment from Vertex Pharmaceuticals for educational presentation, participation on a clinical trials advisory board, and writing a review article. AH’s non-paid roles include chair of the Cystic Fibrosis Clinical Trials Accelerator Program, deputy chair of the NIHR Respiratory Translational Research Collaboration, and director of a university spin-out company (Mi-trial). AMS declares a grant to their institute from UKRI/NIHR to complete this work, and research grants from the British Heart Foundation, MRC, and NIHR-BRC. AShe declares a grant to their institute from UKRI, and unremunerated participation on AstraZeneca Thrombotic Thrombocytopenic Taskforce and Scottish and UK Governments COVID-19 advisory groups. BR declares payments from the British Heart Foundation Oxford Centre of Research Excellence, NIHR Oxford BRC, and UKRI for grants and contracts; and consulting fees from Axcella Therapeutics. CE declares funding from GlaxoSmithKline for an investigator-led research project. CEBr declares that their institute was awarded a grant from UKRI/NIHR to complete this work; the author reports grants from GlaxoSmithKline, AstraZeneca, Sanofi, Boehringer Ingelheim, Chiesi, Novartis, Roche, Genentech, Mologic, and 4DPharma; and consultancy fees paid to their institution from GlaxoSmithKline, AstraZeneca, Sanofi, BI, Chiesi, Novartis, Roche, Genentech, Mologic, 4DPharma, and Teva. CEBo declares that their institute was awarded a grant from UKRI/NIHR and institutional support from NIHR Nottingham BRC to complete this work; the author reports grants to support the Dynamo Study (DYNamic Assessment of Multi Organ level dysfunction in patients recovering from Covid-19) and The Nottingham Recovery from COVID-19 Research Platform (NoRCoRP) post-COVID project from NIHR Nottingham BRC and Nottingham University Hospitals Research and Innovation Department and Nottingham Hospitals Charity. DGW declares support from an Advanced Fellowship from NIHR. DP declares that their institute was awarded a grant from NIHR and MRC, and holds leadership roles within the British Thoracic Society. GC declares grants to their institution from GlaxoSmithKline, AstraZeneca, British Lung Foundation, Mereo, and Arrowhead Pharmaceutials; personal payments from GlaxoSmithKline and AstraZeneca for educational meetings and presentations; conference registration fees paid for by GlaxoSmithKline; and unpaid participation as chair of the Lothian Respiratory Managed Clinical Network and Act on COPD Group in Scotland for AstraZeneca. GPM declares a grant to their institute from UKRI/NIHR to complete this work; grants from the British Heart Foundation and MRC; support for attending meetings from the British and Irish Society for Minimally Invasive Cardiac Surgery; leadership in the British Society for Cardiovascular MRI; and receipt of research software from Circle CVi. JRH declares consultancy fees from AstraZeneca; speaker fees from Boehringer Ingelheim and Takeda; travel grants from AstraZeneca; participation on an advisory board for AstraZeneca; an unpaid leadership role with the British Thoracic Society; and a donation of oximeters from Nonin. JCP declares grants to their institution from UKRI, LifeArc, and MRC; payment fees from The Limbic; and advisory board membership at Carrick Therapeutics and AstraZeneca. JDC declares grants from AstraZeneca, Boehringer Ingelheim, Insmed, Novartis, Gilead Sciences, and Genentech; and consulting fees from AstraZeneca, Boehringer Ingelheim, Insmed, Novartis, Gilead Sciences, Chiesi, Zambon, and Genentech. JJ declares consulting fees from Boehringer Ingelheim, Roche, GlaxoSmithKline, and National Health Service X (NHSX, a joint organisation for digital data and technology); speaker fees from Boehringer Ingelheim, Roche, GlaxoSmithKline, and Takeda; support for meeting attendance from Boehringer Ingelheim; participation on advisory boards at Boehringer Ingelheim and Roche; and UK patent application number 2113765.8 (a patent for a computer algorithm for medical image analysis). LH-W declares a grant from NIHR unrelated to the submitted work; acting as independent chair of the NIHR HTA Committee for Colour COPD trial; and membership of the American Thoracic Society Pulmonary Rehabilitation Assembly Web and Planning Committees. L-PH declares that their institution received grants from UKRI, Regenerative Medicine Platform, Celgene, British Lung Foundation, and Oxford Boehringer Ingleheim; the author is on the advisory board for the CATALYST trial and acts as chair of the Respiratory Translational Research Collaboration. LVW declares research funding unrelated to the submitted work from GlaxoSmithKline and Orion; consulting fees unrelated to the submitted work from Galapagos; a Wellcome Conference speaker honorarium; travel support from Genentech; advisory board participation for Galapagos; and an associate editor role for the European Respiratory Journal. MGJ declares that their institute was awarded a grant from Boehringer Ingelheim. MGS declares that their institute was awarded a grant from NIHR, MRC, and Health Protection Research Unit in Emerging and Zoonotic Infections, University of Liverpool, to complete this work; the author is an independent external and non-remunerated member of Pfizer’s external data monitoring committee for their mRNA vaccine programme; chair of the Infectious Disease Scientific Advisory Board for Integrum Scientific; minority share owner in Integrum Scientific; and a non-remunerated independent member of HMG Scientific Group for Emergencies and the UK New Emerging Respiratory Virus Threats Advisory Group (NERVTAG). MJD declares payments to their institution from AstraZeneca, Novo Nordisk, Boehringer Ingelheim, and Janssen, outside the submitted work; consulting fees from Novo Nordisk, Eli Lilly, and Boehringer Ingelheim; personal fees for lectures and presentations from Novo Nordisk, Sanofi-Aventis, Eli Lilly, Boehringer Ingelheim, AstraZeneca, and Napp Pharmaceuticals; and acting as a member of RESiliENT Trial Steering Committee and Chair of the European Association for the Study of Diabetes writing group. MJR declares a grant from NIHR for the HTA SOS Trial and NIHE EME Programme study (OSMOTIC); and current employment by Roche on a 1-year academic/industry senior clinical fellowship. NE received donations of COVID-19 lateral flow tests for a pilot project from Mologics. NIL declares acting as director of research at the Intensive Care Society UK. PJMO declares co-funding from MRC and GlaxoSmithKline (INFLAMMAGE), part of the EMINENT consortium to promote inflammation research; consulting fees from Janssen, Seqiris, and Valneva; payments for speaking from Janssen and Seqirus; and acting as member and vice-chair of NERVTAG. PP declares grants from NIHR to the institute to support remote rehabilitation after COVID-19. RGJ declares a commercial contract with PatientMPower to provide an app and spirometers with no payments by PatientMPower for the study; payments to their institution from AstraZeneca, Biogen, Galecto, GlaxoSmithKline, RedX, and Pliant; consulting fees from Bristol Myers Squibb, Daewoong, Veracyte, Resolution Therapeutics, and Pliant; payments for lectures from Chiesi, Roche, PatientMPower, and AstraZeneca; participation on advisory boards at Boehringer Ingelheim, Galapagos, and Vicore; a leadership role at NuMedii; and acting as a trustee for Action for Pulmonary Fibrosis. RAE declares that their institute was awarded a grant from UKRI/NIHR to complete this work; the author declares speaker fees from Boehringer Ingelheim and unpaid roles with European Respiratory Society Assembly 01.02 Pulmonary Rehabilitation secretary and American Thoracic Society Pulmonary Rehabilitation Assembly programme committee. SH declares grants from the European Commission and NIHR; consulting fees from Eli Lilly, Zealand Pharma, Novo Nordisk, and Mylan; honorary payments from Novo Nordisk; and payment for expert testimony from the Crown Prosecution Service. SN declares research grant from Axcella. SLR-J declares a grant to their institute from UKRI/NIHR and salary support from Clinical Research Network to complete this work; grants from UKRI, NIHR, Global Challenges Research Fund, and European and Developing Countries Clinical Trials Partnership (EDCTP) for unrelated studies; participation on a data safety monitoring board for two trials (Bexero for gonococcal infection in Kenya and inactivated COVID-19 vaccine trial in Zimbabwe); and previously acting as president of the Royal Society of Tropical Medicine and Hygiene. TC declares a grant to their institute from NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust to complete this work; a grant from NIHR for the CLOCK study; speaker fees from Hello Self, the British Association for Behavioural and Cognitive Psychotherapies, and UK Department of Health; unpaid participation on the National Institute for Health and Care Excellence guideline committee on Post/Long COVID; leading the Persistent Physical Symptom service as part of their paid employment; and having authored a published self-help book on fatigue for which he received payments. WD-CM declares grants from NIHR, British Lung Foundation, and NHSX; payments for lectures from Munipharma, Novartis, and European Conference and Incentive Services DMC; participation on a monitoring board for Jazz Pharmaceuticals; and funds for blood analysis from GlaxoSmithKline. AShi, ASi, JML, MM, and NDB declare that their institute was awarded a grant from UKRI/NIHR to complete this work. LGH declares grants for acting as an academic lead for the UK MRC Consortium for Stratified Medicine in Severe Asthma; industrial pharma partners incude Amgen, AstraZeneca, Medimmune, Janssen, Novartis, Roche/Genentech, GlaxoSmithKline, and Boehringer Ingelheim; project grant funding was received from Medimmune, Novartis UK, Roche/Genentech, and GlaxoSmithKline. All other authors declare no competing interests.
Data sharing
The protocol, consent form, definition and derivation of clinical characteristics and outcomes, training materials, regulatory documents, requests for data access and other relevant study materials are available online at https://www.phosp.org.
Acknowledgments
This study would not be possible without all the participants who have given their time and support. We thank all the participants and their families. We thank the many research administrators and health-care and social-care professionals who contributed to setting up and delivering the study at all of the 69 NHS trusts and 25 research institutions across the UK, as well as all the supporting staff at the NIHR Clinical Research Network, Health Research Authority, Research Ethics Committee, Department of Health and Social Care Public Health Scotland, Public Health England, and support from the ISARIC Coronavirus Clinical Characterisation Consortium. At the NIHR Office for Clinical Research Infrastructure, we thank Kate Holmes for her support in coordinating the charities group. We are very grateful to all the charities that have provided insight to the study—Action Pulmonary Fibrosis, Alzheimer’s Research UK, Asthma UK, British Lung Foundation UK, British Heart Foundation, Diabetes UK, Cystic Fibrosis Trust, Kidney Research UK, MQ Mental Health, Muscular Dystrophy UK, Stroke Association Blood Cancer UK, McPin Foundations, and Versus Arthritis. We thank the NIHR Leicester Biomedical Research Centre patient and public involvement group and the Long Covid Support Group. This research used the SPECTRE High Performance Computing Facility at the University of Leicester, Leicester, UK. PHOSP-COVID is supported by a grant from MRC Research and Innovation and the Department of Health and Social Care through the NIHR rapid response panel to tackle COVID-19 (MR/V027859/1 and COV0319). Core funding was provided by NIHR Leicester Biomedical Research Centre to support the PHOSP-COVID coordination team and NIHR biomedical research centres, clinical research facilities, NIHR health protection research unit, and translational research collaborations network across the country. The institutional funding that supports the outbreak labs that process the PHOSP samples are from the NIHR Health Protection Research Unit in Emerging and Zoonotic Infections, University of Liverpool, Liverpool, UK, in partnership with Public Health England and Liverpool Experimental Cancer Medicine Centre (C18616/A25153). ABD is funded by a Wellcome Trust grant (216606/Z/19/Z); RAE holds an NIHR clinician scientist fellowship (CS-2016-16-020); NJG holds an NIHR post-doctoral fellowship (PDF-2017-10-052); JJ was supported by a Wellcome Trust Clinical Research Career Development Fellowship (209553/Z/17/Z) and by the NIHR University College London Hospital Biomedical Research Centre, UK; LVW was supported by a GlaxoSmithKline and British Lung Foundation chair in respiratory research (C17-1); and DGW is supported by an NIHR advanced fellowship (NIHR300669). The views expressed in this publication are those of the author(s) and not necessarily those of the MRC, NIHR, or the UK Department of Health and Social Care. No form of payment was given to anyone to produce the manuscript.
Supplementary Material
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Long COVID: systemic inflammation and obesity as therapeutic targets
Management of the post-COVID-19 condition—often referred to as long COVID—is a challenge for health-care professionals because of the heterogeneity and complexity of its clinical manifestations and the probable need for multidisciplinary management approaches.1 Identification and understanding of modifiable determinants associated with manifestations of long COVID would help in the adaptation of treatment pathways for particular phenotypes.1 In The Lancet Respiratory Medicine, the PHOSP-COVID Collaborative Group2 report the latest results from the UK-based, multicentre, prospective Post-hospitalisation COVID-19 (PHOSP-COVID) study, in which the investigators identified systemic inflammation and obesity as factors that might be associated with long COVID, representing potentially treatable traits in people with more severe post-COVID-19 symptoms.
In December, 2020, two mRNA-based COVID-19 vaccines were authorised for use in the USA. We aimed to describe US surveillance data collected through the Vaccine Adverse Event Reporting System (VAERS), a passive system, and v-safe, a new active system, during the first 6 months of the US COVID-19 vaccination programme.
Methods
In this observational study, we analysed data reported to VAERS and v-safe during Dec 14, 2020, to June 14, 2021. VAERS reports were categorised as non-serious, serious, or death. Reporting rates were calculated using numbers of COVID-19 doses administered as the denominator. We analysed v-safe survey reports from days 0–7 after vaccination for reactogenicity, severity (mild, moderate, or severe), and health impacts (ie, unable to perform normal daily activities, unable to work, or received care from a medical professional).
Findings
During the study period, 298 792 852 doses of mRNA vaccines were administered in the USA. VAERS processed 340 522 reports: 313 499 (92·1%) were non-serious, 22 527 (6·6%) were serious (non-death), and 4496 (1·3%) were deaths. Over half of 7 914 583 v-safe participants self-reported local and systemic reactogenicity, more frequently after dose two (4 068 447 [71·7%] of 5 674 420 participants for local reactogenicity and 4 018 920 [70·8%] for systemic) than after dose one (4 644 989 [68·6%] of 6 775 515 participants for local reactogenicity and 3 573 429 [52·7%] for systemic). Injection-site pain (4 488 402 [66·2%] of 6 775 515 participants after dose one and 3 890 848 [68·6%] of 5 674 420 participants after dose two), fatigue (2 295 205 [33·9%] participants after dose one and 3 158 299 participants [55·7%] after dose two), and headache (1 831 471 [27·0%] participants after dose one and 2 623 721 [46·2%] participants after dose two) were commonly reported during days 0–7 following vaccination. Reactogenicity was reported most frequently the day after vaccination; most reactions were mild. More reports of being unable to work, do normal activities, or of seeking medical care occurred after dose two (1 821 421 [32·1%]) than after dose one (808 963 [11·9%]); less than 1% of participants reported seeking medical care after vaccination (56 647 [0·8%] after dose one and 53 077 [0·9%] after dose two).
Interpretation
Safety data from more than 298 million doses of mRNA COVID-19 vaccine administered in the first 6 months of the US vaccination programme show that most reported adverse events were mild and short in duration.
Funding
US Centers for Disease Control and Prevention.
Results
From Dec 14, 2020, to June 14, 2021, 298 792 852 doses of mRNA COVID-19 vaccines were administered in the USA: 167 177 332 were BNT162b2 and 131 639 515 were mRNA-1273 (appendix p 2). A greater proportion of vaccines was administered to females (155 969 573 [53·2%]) than to males (134 373 958 [45·8%]). The median age at vaccination was 50 years (IQR 33–65) for BNT162b2 and 56 years (39–68) for mRNA-1273. 112 698 875 (38·4%) recipients were non-Hispanic White. Race and ethnicity was unknown for 102 227 532 (34·9%) of all vaccine recipients.
During the study period, VAERS received and processed 340 522 reports: 164 669 following BNT162b2 and 175 816 following mRNA-1273 vaccination (table 1). Of these reports, 313 499 (92·1%) were classified as non-serious; 22 527 (6·6%) were serious, not resulting in death; and 4496 (1·3%) were deaths (table 1). 246 085 (72·3%) reports were among female participants and 154 171 (45·3%) reports were among those aged 18–49 years; median age was 50 years (IQR 36–64; table 1). 169 877 (49·9%) of those reporting race or ethnicity identified as non-Hispanic White, and for 75 334 (22·1%) race and ethnicity were unknown (table 1). The most common MedDRA preferred terms assigned to non-serious reports were headache (64 064 [20·4%] of 313 499), fatigue (52 048 [16·6%]), pyrexia (51 023 [16·3%]), chills (49 234 [15·7%]), and pain (47 745 [15·2%]; table 1). The most common MedDRA preferred terms assigned to serious reports were dyspnoea (4175 [15·4%] of 27 023), death (3802 [14·1%]), pyrexia (2986 [11·0%]), fatigue (2608 [9·7%]), and headache (2567 [9·5%]; table 1).
Table 1Characteristics of reports received and processed by VAERS for mRNA COVID-19 vaccines
Data are n or n (%). Includes vaccines administered from Dec 14, 2020, to June 14, 2021. VAERS=Vaccine Adverse Event Reporting System. MedDRA=Medical Dictionary for Regulatory Activities.
The reporting rate to VAERS was 1049·2 non-serious reports per million vaccine doses, and 90·4 serious reports per million doses (table 2). Among the prespecified adverse events of special interest, reporting rates ranged from 0·1 narcolepsy reports per million doses administered to 31·3 reports of COVID-19 disease per million doses administered (table 2). 4496 reports of death were made to VAERS following receipt of an mRNA COVID-19 vaccine (table 3). After review by clinical staff, 25 reports were excluded because of miscoding of death or duplicate reporting. Of the 4471 reports of deaths analysed, 2086 (46·7%) were reported following BNT162b2 and 2385 (53·3%) following mRNA-1273. 1906 (42·6%) deaths were in female vaccine recipients and 2485 (55·6%) were in male recipients; the median age of participants who died was 76 years (IQR 66–86; table 3). 3647 (81·6%) deaths were reported among individuals aged 60 years or older (table 3). 821 (18·4%) deaths were identified as being in long-term care-facility residents. Time to death following vaccination was available for 4118 (92·1%) reports; median time was 10·0 days (IQR 3–25). The greatest number of death reports occurred on day 1 (470 [11·4%] of 4118) and day 2 (312 [7·6%] 4118) following vaccination (appendix p 10).
Table 2Frequency and rates of adverse events of special interest reported to VAERS by recipients of mRNA COVID-19 vaccines
Includes vaccines administered from Dec 14, 2020, to June 14, 2021. VAERS=Vaccine Adverse Event Reporting System.
Table 3Frequency and rates of death reported to VAERS by recipients of mRNA COVID-19 vaccines, by sex and age group
Includes reports made and vaccines administered from Dec 14, 2020, to June 14, 2021. VAERS=Vaccine Adverse Event Reporting System.
Death certificates or autopsy reports were available for clinical review for 808 (18·1%) of 4471 reports of deaths. Among these, causes of death were most commonly diseases of the heart (376 [46·5%]) and COVID-19 (102 [12·6%]; appendix pp 3–4). Among the 3663 reports of death without a death certificate or autopsy, causes of death were most commonly unknown or unclear (1984 [54·2%]), diseases of the heart (621 [17·0%]), and COVID-19 (317 [8·7%]; appendix pp 3–4). Causes of death among reports with death certificate or autopsy reports available are shown by age in appendix p 5.
During the study period, 7 914 583 mRNA COVID-19 vaccine recipients enrolled in v-safe after dose one or dose two and completed at least one post-vaccination health survey during days 0–7 (table 4). The median age of v-safe participants was 50 years (IQR 36–63), 4 975 209 (62·9%) were female, 2 860 738 (36·1%) were male, and 4 701 715 (59·4%) identified as non-Hispanic White (table 4). 6 775 515 participants completed at least one survey during days 0–7 after dose one (table 5). Of these participants, 4 644 989 (68·6%) reported a local injection-site reaction and 3 573 429 (52·7%) reported a systemic reaction (table 5). Of the 5 674 420 participants who completed surveys after dose two, 4 068 447 (71·7%) reported an injection-site reaction and 4 018 920 (70·8%) a systemic reaction (table 5). Local injection-site reactions were reported more frequently after mRNA-1273 than after BNT162b2 (table 5). A similar pattern was found for systemic reactions after mRNA-1273 versus BNT162b2 (table 5). The most frequently reported events after dose one of either mRNA vaccine included injection-site pain, fatigue, and headache, which were also more frequent after dose two than after dose one (table 5). Differences in proportions of reactogenicity by dose number were similar after stratifying by age (vs ≥65 years) and sex (appendix p 6). More reactogenicity was reported among participants younger than 65 years than older participants and by female participants than male participants (appendix p 6).
Table 4Demographic characteristics of v-safe participants reporting receipt of an mRNA COVID-19 vaccine and completing at least one health survey 0–7 days after vaccination
Data are n (%). Includes vaccines administered from Dec 14, 2020, to June 14, 2021.
Table 5Local and systemic reactions and health impacts following mRNA COVID-19 vaccines reported during days 0–7 after vaccination to v-safe, by manufacturer and dose
Data are n (%). Includes health check-in surveys made and vaccines administered from Dec 14, 2020, to June 14, 2021.
Local and systemic reactions stratified by manufacturer, dose, days after vaccination, and severity are shown in the figure. Most reported symptoms were mild (figure). Participants reported moderate and severe reactogenicity most commonly on day 1 after dose two of either mRNA vaccine (figure). The proportion of participants who reported symptoms was greatest on day 1 and then decreased subsequently (figure). The highest proportions of participants reporting severe symptoms occurred on day 1 following dose two of mRNA-1273 (appendix p 8). On all other days, proportions of participants reporting severe symptoms did not exceed 3·0% for any individual symptom (appendix pp 7–8).
FigureLocal and systemic reactions to mRNA COVID-19 vaccines reported to v-safe, by manufacturer, dose, days after vaccination, and severity
Show full caption
Figure shows top reactions by reported frequency, after showing by dose number and by manufacturer. These top six reactions were determined by reported frequency after dose two of both mRNA COVID-19 vaccines in v-safe, excluding fever because it was not rated mild, moderate, or severe. Mild was defined as “noticeable symptoms but they aren’t a problem”, moderate as “symptoms that limit normal activities”, and severe as “make normal daily activities difficult or impossible”.
Reported health impacts were greater following dose two of either vaccine than dose one, and after mRNA-1273 than after BNT162b2 (table 5). After dose two of BNT162b2, 598 584 (20·5%) of 2 920 526 participants were unable to do normal activities, and 360 411 (12·3%) were unable to work (table 5). After dose two of mRNA-1273, 903 095 (32·8%) of 2 753 894 participants were unable to do normal activities, and 550 955 (20·0%) were unable to work (table 5). Less than 1·0% reported receiving medical care after receiving either dose of either vaccine (table 5). A very small proportion reported an emergency room visit or hospitalisation (table 5).
When stratified by sex, female participants reported a health impact more frequently than did male participants, peaking on day 1 after vaccination (appendix p 11). Following dose two of mRNA-1273 vaccine, 522 192 (41·4%) of 1 262 711 female participants reported an inability to do normal activities in the day 1 survey, and 296 178 (23·5%) reported an inability to work (appendix pp 9, 11). Among male recipients of dose two of mRNA-1273, on the day 1 survey 167 957 (25·6%) of 655 688 were unable to do normal activity and 110 868 (16·9%) were unable to work (appendix pp 9, 11).
Discussion
In this analysis of VAERS and v-safe data from the first 6 months of COVID-19 vaccination rollout in the USA, when over 298 million doses of mRNA vaccines were administered, we found that reactogenicity was similar to what was reported from clinical trials and from early post-authorisation monitoring.
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In both VAERS and v-safe, local injection-site and systemic reactions were commonly reported. V-safe participants more frequently reported transient reactions following mRNA-1273 than following BNT162b2, and more frequently following dose two of either vaccine compared with after dose one. Female participants and individuals younger than 65 years reported adverse events and reactions more frequently than male participants and those aged 65 years and older, respectively. Reporting rates for death were higher in older age groups, as expected on the basis of general age-specific mortality in the general adult population.
Safety monitoring of COVID-19 vaccines has been the most comprehensive in US history and has used established systems, including the Vaccine Safety Datalink (VSD),
20
US Centers for Disease Control and Prevention Vaccine safety monitoring—VSD.
VAERS, and a new system, v-safe, developed specifically for monitoring COVID-19 vaccine safety. During the study period, all COVID-19 vaccines were administered under EUAs, which require vaccine providers to report all serious adverse events (including deaths) that occur after vaccination to VAERS, regardless of whether they were plausibly associated with vaccination. Heightened public awareness of the COVID-19 vaccination programme, outreach and education to health-care providers and hospitals about COVID-19 EUA reporting requirements for adverse events, and adherence to EUA reporting requirements by providers and health systems, probably all contributed to the high volume of VAERS reports received.
Data from US safety monitoring systems for all COVID-19 vaccines authorised or approved by the FDA have been reviewed regularly by the ACIP COVID-19 Vaccines Safety Technical Work Group
21
US Centers for Disease Control and Prevention Advisory Committee on Immunization Practices. VaST Reports.
and at public ACIP meetings.
22
US Centers for Disease Control and Prevention Advisory Committee on Immunization Practices. Meeting information.
Similar to reports following receipt of other vaccines routinely administered to adults, most VAERS reports following mRNA COVID-19 vaccination were non-serious.
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surveillance prompted specific safety evaluations for anaphylaxis,
14
US Centers for Disease Control and Prevention Allergic reactions including anaphylaxis after receipt of the first dose of Pfizer-BioNTech COVID-19 vaccine—United States, December 14–23, 2020.
thrombosis with thrombocytopenia syndrome,
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myocarditis,
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and Guillain-Barré syndrome.
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After reports of anaphylaxis following mRNA vaccination with both vaccines, clinical guidance and management recommendations were updated.
31
US Centers for Disease Control and Prevention Interim clinical considerations.
Also during this time period, a safety signal for myocarditis was identified and investigated further in VAERS and other US safety systems.
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Thrombosis with thrombocytopenia syndrome
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and Guillain-Barré syndrome
30
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have been associated with Janssen’s Ad26.COV2.S adenoviral vector COVID-19 vaccine but not with mRNA vaccines. ACIP has conducted several benefit–risk assessments for each of the authorised or approved US COVID-19 vaccines;
22
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these assessments have resulted in several modifications to clinical guidance and a preferential recommendation for mRNA vaccines.
31
US Centers for Disease Control and Prevention Interim clinical considerations.
Reactogenicity findings following mRNA COVID-19 vaccination from VAERS and v-safe data are similar to those from a large study in the UK.
34
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The observed patterns might be explained in part by host characteristics known to influence reactogenicity, including age, sex, and the presence of underlying medical conditions.
35
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Didierlaurent AM
Tavares Da Silva F
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Female recipients have more vigorous antibody responses
36
Factors that influence the immune response to vaccination.
to certain vaccines and also tend to report more severe local and systemic reactions to influenza vaccine, compared with male recipients.
37
Klein SL
Jedlicka A
Pekosz A
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Female recipients might also be more likely than male recipients to respond to surveys.
38
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,
39
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Younger people might be more comfortable with smartphone-based surveys and more likely to respond to surveys generally.
40
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et al.
The feasibility of web surveys for obtaining patient-reported outcomes from cancer survivors: a randomized experiment comparing survey modes and brochure enclosures.
,
41
Surveying the general public over the internet using address-based sampling and mail contact procedures.
Using v-safe data, we were able to assess the effects of mRNA vaccination on daily-life activities among vaccine recipients for the first time for a vaccine administered in the USA. These effects were most frequently reported on day 1 after vaccination. Reports about the measures of health impacts used in v-safe, although self-assessed and subjective, correlate with reports about reactogenicity: more health impacts were reported by female than by male recipients, by participants younger than 65 years compared with older participants, after dose two compared with dose one, and by those who received mRNA-1273 versus BNT162b2. Reports of seeking medical care after mRNA vaccine were rare; v-safe surveys did not ask which symptoms prompted the participant to seek medical care. Reactogenicity and its associated health impacts, even if transient, might deter some from seeking vaccination. Surveys found that nearly half of unvaccinated adults younger than 50 years expressed concern about missing work because of vaccine side-effects and that employees who were given paid leave were more likely to get vaccinated than were those without paid leave;
42
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employer policies that accommodate such leave might increase vaccination coverage.
43
The White House FACT SHEET: President Biden to call on all employers to provide paid time off for employees to get vaccinated after meeting goal of 200 million shots in the first 100 days.
In our review and analysis of death reports to VAERS following mRNA vaccination, we found no unusual patterns in cause of death among the death reports received. Under the COVID-19 vaccine EUA regulations, health-care providers are required to report deaths and life-threatening adverse health events after COVID-19 vaccinations to VAERS regardless of their potential association with vaccination. These requirements make comparing the number of reported deaths to VAERS for COVID-19 vaccines with reported deaths following other adult vaccines
44
Moro PL
Arana J
Cano M
Lewis P
Shimabukuro TT
Deaths reported to the Vaccine Adverse Event Reporting System, United States, 1997–2013.
difficult because no other adult vaccines have been so widely administered under FDA EUAs. Initially, US COVID-19 vaccination was prioritised for individuals aged 65 years and older and those in long-term care facilities.
7
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These populations have the highest baseline mortality risk, complicating comparisons with mortality reporting for other adult vaccines. Similar to general mortality in the adult population,
45
Murphy SL
Xu J
Kochanek KD
Arias E
Tejada-Vera B
Deaths: final data for 2018.
reporting rates for deaths in this analysis increased with increasing age. The concentrated reporting of deaths on the first few days after vaccination follows patterns similar to those observed for other adult vaccinations.
46
US Centers for Disease Control and Prevention About the Vaccine Adverse Event Reporting System (VAERS).
This pattern might represent reporting bias because the likelihood to report a serious adverse event might increase when it occurs in close temporal proximity to vaccination.
There are limitations in any review of preliminary data concerning reports of death following vaccination. A comparison with national mortality data
45
Murphy SL
Xu J
Kochanek KD
Arias E
Tejada-Vera B
Deaths: final data for 2018.
suggests that certain causes of death, such as accidents, suicides, or cancer, are less likely to be reported to VAERS. Underreporting to VAERS, in general, is expected.
8
Shimabukuro TT
Nguyen M
Martin D
DeStefano F
Safety monitoring in the Vaccine Adverse Event Reporting System (VAERS).
The predominance of heart disease as a cause of death reported to VAERS warrants continued monitoring and assessment but might be driven by non-specific causes, such as cardiac arrest, that might be chosen as a terminal event if no immediate explanation for death was available. Death certificate or autopsy reports were available for only a small proportion of deaths reported to VAERS when our analyses were conducted. Finally, VAERS is designed as an early warning system to detect potential safety signals,
8
Shimabukuro TT
Nguyen M
Martin D
DeStefano F
Safety monitoring in the Vaccine Adverse Event Reporting System (VAERS).
and VAERS data alone generally cannot establish causal relationships between vaccination and adverse events. Another surveillance system, the VSD, showed no increased risk of non-COVID-19 mortality in vaccinated people.
47
Xu S
Huang R
Sy LS
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COVID-19 vaccination and non-COVID-19 mortality risk—seven integrated health care organizations, United States, December 14, 2020–July 31, 2021.
This study has several strengths, including the large population under surveillance and the comprehensive capture of national data from two complementary surveillance systems. Because the US Government purchased all COVID-19 doses and collected administration data, we were able to calculate VAERS reporting rates using the number of mRNA vaccine doses administered as denominators.
18
US Centers for Disease Control and Prevention COVID-19 vaccinations in the United States.
By contrast, VAERS analyses for non-COVID-19 vaccines rely on doses distributed, not administered. Because the number of doses distributed is greater than that of doses administered, these past VAERS analyses are likely to underestimate reporting rates of vaccine-related adverse events. Information from v-safe about how reactogenicity during the week after mRNA vaccination affects daily activities and work is novel and provides new insights.
An important limitation of this report is one shared by all VAERS analyses: we used data from a passive reporting system subject to underreporting and variable or incomplete reporting.
8
Shimabukuro TT
Nguyen M
Martin D
DeStefano F
Safety monitoring in the Vaccine Adverse Event Reporting System (VAERS).
Although VAERS death reports were individually reviewed by CDC physicians and follow-up is ongoing to obtain additional and missing records, other reports of serious adverse events were not individually reviewed. Additionally, VAERS reports require interpretation to identify whether reports meet clinical case definitions.
48
Vaccine Adverse Event Reporting System Guide to interpreting VAERS data.
A limitation of v-safe is the need for smartphone access. Because a subset of all vaccine recipients participated in v-safe, the results are unlikely to be generalisable to the entire vaccinated US population. Other differences might exist among participants who received mRNA-1273 or BNT162b2 vaccines that were unaccounted for; therefore, v-safe cannot be used to draw conclusions that one mRNA vaccine type is more reactogenic than the other. Additionally, participants in v-safe might be lost to follow-up because continuous enrolment is not required. Finally, this report only included v-safe responses received during the first week after vaccination.
During the first 6 months of the US COVID-19 vaccination programme, more than 50% of the eligible population received at least one vaccine dose.19 VAERS and v-safe data from this period show a post-authorisation safety profile for mRNA COVID-19 vaccines that is generally consistent with pre-authorisation trials
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and early post-authorisation surveillance reports.
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Serious adverse events, including myocarditis, have been identified following mRNA vaccinations; however, these events are rare. Vaccines are the most effective tool to prevent serious COVID-19 disease outcomes
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US Centers for Disease Control and Prevention COVID-19 vaccines and vaccination.
and the benefits of immunisation in preventing serious morbidity and mortality strongly favour vaccination.
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VAERS and v-safe, two complementary surveillance systems, will continue to provide data needed to inform policy makers, immunisation providers, other health-care professionals, and the public about the safety of COVID-19 vaccination.
HGR, JG, JRS, TRM, AMH, LEM, TTS, and DKS contributed to conceptualisation, data curation, formal analysis, investigation, methodology, project administration, visualisation, writing, and editing. JRS, TRM, TTS, DKS, JG, and LEM contributed to supervision. RL, PLM, and BZ contributed to data curation, formal analysis, validation, visualisation, writing, and editing, and have verified the underlying data. WEA and MMM contributed to data curation, analysis, writing, and editing. PS contributed to project administration, visualisation, writing, and editing. All authors had access to the underlying data of the study and were responsible for the decision to submit for publication.
Many countries are experiencing a resurgence of COVID-19, driven predominantly by the delta (B.1.617.2) variant of SARS-CoV-2. In response, these countries are considering the administration of a third dose of mRNA COVID-19 vaccine as a booster dose to address potential waning immunity over time and reduced effectiveness against the delta variant. We aimed to use the data repositories of Israel’s largest health-care organisation to evaluate the effectiveness of a third dose of the BNT162b2 mRNA vaccine for preventing severe COVID-19 outcomes.
Methods
Using data from Clalit Health Services, which provides mandatory health-care coverage for over half of the Israeli population, individuals receiving a third vaccine dose between July 30, 2020, and Sept 23, 2021, were matched (1:1) to demographically and clinically similar controls who did not receive a third dose. Eligible participants had received the second vaccine dose at least 5 months before the recruitment date, had no previous documented SARS-CoV-2 infection, and had no contact with the health-care system in the 3 days before recruitment. Individuals who are health-care workers, live in long-term care facilities, or are medically confined to their homes were excluded. Primary outcomes were COVID-19-related admission to hospital, severe disease, and COVID-19-related death. The third dose effectiveness for each outcome was estimated as 1 – risk ratio using the Kaplan-Meier estimator.
Findings
1 158 269 individuals were eligible to be included in the third dose group. Following matching, the third dose and control groups each included 728 321 individuals. Participants had a median age of 52 years (IQR 37–68) and 51% were female. The median follow-up time was 13 days (IQR 6–21) in both groups. Vaccine effectiveness evaluated at least 7 days after receipt of the third dose, compared with receiving only two doses at least 5 months ago, was estimated to be 93% (231 events for two doses vs 29 events for three doses; 95% CI 88–97) for admission to hospital, 92% (157 vs 17 events; 82–97) for severe disease, and 81% (44 vs seven events; 59–97) for COVID-19-related death.
Interpretation
Our findings suggest that a third dose of the BNT162b2 mRNA vaccine is effective in protecting individuals against severe COVID-19-related outcomes, compared with receiving only two doses at least 5 months ago.
Funding
The Ivan and Francesca Berkowitz Family Living Laboratory Collaboration at Harvard Medical School and Clalit Research Institute.
Introduction
Despite the initially promising results of nationwide vaccination campaigns, many countries are currently experiencing a resurgence of COVID-19, dominated by the delta (B.1.617.2) variant of SARS-CoV-2. After several months of low pandemic activity in early 2021, Israel is experiencing its fourth pandemic wave, despite over 55% of the population having been vaccinated with two doses of the BNT162b2 mRNA COVID-19 vaccine. First and second doses were given 21 days apart, as per the pre-approval randomised trials. The increase in infections and hospitalisations of vaccinated individuals likely stems from a combination of waning vaccine immunity over time,
1
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Antibody response to BTN162b2 mRNA vaccination in naïve versus SARS-CoV-2 infected subjects with and without waning immunity.
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given that many people in Israel were vaccinated 5–7 months ago, and from potentially reduced effectiveness of the vaccine against the delta variant.
4
Lopez Bernal J
Andrews N
Gower C
et al.
Effectiveness of Covid-19 vaccines against the B.1.617.2 (delta) variant.
A standard approach to overcoming waning immunity, also known as secondary vaccine failure, is the administration of an additional vaccine dose—often referred to as a booster dose. Faced with rising rates of COVID-19-related admissions to hospital, and based on initial evidence suggesting a pronounced humoral response to a third dose of the mRNA vaccines,
5
Ducloux D
Colladant M
Chabannes M
Yannaraki M
Courivaud C
Humoral response after 3 doses of the BNT162b2 mRNA COVID-19 vaccine in patients on hemodialysis.
,
6
Pfizer Second quarter 2021 earnings teleconference.
,
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the Israeli Ministry of Health announced a campaign to administer a third dose of the BNT162b2 mRNA COVID-19 vaccine (Pfizer–BioNTech). This campaign began with immunocompromised patients on July 13, 2021, and was expanded several times to include people aged over 60 years (on July 30), 50 years (on Aug 12), 40 years (on Aug 19), 30 years (on Aug 24), and eventually the entire population over the age of 12 years on Aug 30. The third dose was only given to people who had received the second dose at least 5 months ago. Administration of the third dose progressed rapidly, reaching over half of the population aged at least 60 years within the first 2 weeks. Other countries such as the USA, the UK, Germany, and France are planning or conducting campaigns to provide an additional dose for elderly and vulnerable populations,
8
Vaccine booster shots for 32m to begin next month.
,
9
Ignoring WHO call, major nations stick to vaccine booster plans.
,
10
Biden administration expected to call for COVID-19 vaccine booster shots.
such as immunocompromised patients, who have been shown to mount a lesser immune response to the vaccine.
11
Kearns P
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et al.
Examining the immunological effects of COVID-19 vaccination in patients with conditions potentially leading to diminished immune response capacity – the OCTAVE trial.
On Aug 12, 2021, the US Food and Drug Administration amended the authorisations for both mRNA COVID-19 vaccines (Pfizer–BioNTech’s BNT162b2 and Moderna’s mRNA-1273) to allow for the use of an additional dose in immunocompromised patients.
12
Food and Drug Administration Coronavirus (COVID-19) update: FDA authorizes additional vaccine dose for certain immunocompromised individuals.
On Sept 22, 2021, the authorisation was extended to include individuals aged 65 years or older, and younger individuals with increased medical or occupational risk.
13
Food and Drug Administration FDA authorizes booster dose of Pfizer-BioNTech COVID-19 vaccine for certain populations.
Research in context
Evidence before this study
No formal literature review was done. Several previous publications regarding the effectiveness of the third dose of the BNT162b2 mRNA COVID-19 vaccine have focused on antibody response, showing a pronounced humoral response after administration of the booster. Two recent studies from Israel have focused on clinical outcomes. The first reported a reduction of 90–96% in the risk for severe disease starting from day 12 after the booster dose, but did not adjust for pre-existing clinical conditions related to the risk of severe disease and did not evaluate the effectiveness within subgroups. The second found a reduction of 70–84% in the probability of testing positive for SARS-CoV-2 among vaccinated individuals, but did not estimate effectiveness for more severe outcomes.
Added value of this study
To our knowledge, the present study is the first to estimate the effectiveness of a third dose of an mRNA COVID-19 vaccine—BNT162b2 specifically—against severe outcomes with adjustment for various possible confounders, including comorbidities and behavioural factors, and within subgroups. Our results suggest that that a third dose of the BNT162b2 vaccine is effective in preventing severe COVID-19-related outcomes. Compared with two doses of the vaccine administered at least 5 months ago, receiving a third dose was estimated to have an effectiveness of 93% in preventing COVID-19-related admission to hospital, 92% in preventing severe disease, and 81% in preventing COVID-19-related death.
Implications of all the available evidence
As of October, 2021, many countries are experiencing a resurgence of SARS-CoV-2 infections despite hitherto successful vaccination campaigns. This situation has been suggested to be caused by the greater infectiousness of the delta (B.1.617.2) variant of SARS-CoV-2, and by waning immunity as time passes from earlier vaccination. In the face of the current resurgence, several countries are planning to administer a third booster dose of mRNA COVID-19 vaccine. Our study suggests that a third vaccine dose is effective in reducing severe COVID-19-related outcomes for patients who have received two vaccine doses at least 5 months ago.
We aimed to use the data repositories of Israel’s largest health-care organisation to estimate the effectiveness of a third dose of the BNT162b2 COVID-19 vaccine in preventing severe COVID-19-related outcomes.
Methods
Study design and participants
This study was designed to emulate a target trial
14
Using big data to emulate a target trial when a randomized trial is not available.
of the effects of a third dose of the BNT162b2 vaccine in a population of individuals who had already received two doses of the vaccine at least 5 months before recruitment. The study design is similar to our previous vaccine effectiveness studies conducted in the same population and setting, which have been described at length.
15
Dagan N
Barda N
Kepten E
et al.
BNT162b2 mRNA Covid-19 vaccine in a nationwide mass vaccination setting.
Clalit Health Services is the largest of four integrated payer-provider health-care organisations providing mandatory health-care coverage in Israel, insuring over half of the Israeli population. Clalit Health Services information systems are fully digitised and feed into a central data warehouse, covering all aspects of care, including COVID-19. The study period was July 30, 2020, to Sept 23, 2021.
To be included in the study, an individual had to have received the second vaccine dose at least 5 months before the recruitment date, and have been eligible to receive the third vaccine dose as per the guidelines of the Israeli Ministry of Health on at least one of the days of the study period. For those aged 60 years or above, this meant individuals with recruitment potential on or after July 30, 2021; for ages 50–59 years, recruitment potential from Aug 12, 2021; for ages 40–49 years, recruitment potential from Aug 19, 2021; for ages 30–39 years from Aug 24, 2021; and for those aged at least 12 years, from Aug 30, 2021. Additional inclusion criteria were membership in the health organisation for at least 12 months, no previous documented SARS-CoV-2 infection, and no contact with the health-care system in the 3 days before the recruitment date.
Immunocompromised patients who received the third dose before July 30, 2021, were not included in the study, as the focus was on providing vaccine effectiveness estimates applicable to the general population. Individuals who are health-care workers, live in long-term care facilities, or are medically confined to their homes (irrespective of COVID-19) were excluded due to concerns of residual confounding. Individuals with missing body-mass index or residential area data were also excluded. A complete definition of the study variables is provided in the appendix (pp 12–19).
This study was approved by the Clalit Health Services institutional review board and was exempt from requiring written informed consent. The protocol is included in the appendix (pp 3–11).
Procedures
The target trial for this study would compare two treatment strategies: administration of the third dose at recruitment (third dose group) and no administration of the third dose at any time during follow-up (control group). To emulate this target trial, each day during the study period, eligible individuals who received the third dose on that day were matched to eligible controls who were previously vaccinated with two vaccine doses but had not yet received the third dose. Controls matched on a given day who received the third dose on a future date would become newly eligible to be recruited into the third dose group on that future date.
Individuals in the third dose group and the control group were exactly matched on a set of potential confounders: age (categorised into 2-year bins), sex (male or female), place of residence, number of pre-existing chronic conditions considered to be risk factors for severe COVID-19 by the US Centers for Disease Control as of Dec 20, 2020 (divided into four bins),
16
Centers for Disease Control and Prevention Certain medical conditions and risk for severe COVID-19 illness.
calendar month in which each person received the second vaccine dose, and number of SARS-CoV-2 PCR tests performed in the 9 months before the index date (divided into six bins). The latter two matching variables were included as markers of health-seeking behaviour specifically related to vaccination against COVID-19, given that individuals who are more health conscious or concerned about the pandemic chose to be vaccinated sooner and did more PCR tests.
Outcomes
Primary outcomes were hospital admission for COVID-19, severe COVID-19 disease (according to US National Institutes of Health criteria
17
National Institutes of Health COVID-19 treatment guidelines.
), and COVID-19-related death. Each of these outcomes include the outcomes that precede it. These severe outcomes were chosen because of their greater public health importance, and because they are less likely to be affected by biases stemming from a differential tendency to be tested that is expected to exist between the study groups.
Secondary outcomes were less severe: documented SARS-CoV-2 infection confirmed by positive PCR test and symptomatic infection.
For each outcome, matched pairs of individuals were followed from the start of follow-up until the earliest of: documentation of the outcome, end of the study calendar period (Sept 26, 2021), or death. We also ended the follow-up of a matched pair if the control individual received the third dose. Outcomes were ascertained in the period starting 7 days after receipt of the third dose in the vaccinated, similar to the period used to determine full vaccination after the second dose, and until the end of follow-up.
Statistical analysis
We used the Kaplan-Meier estimator
18
Nonparametric estimation from incomplete observations.
to construct cumulative incidence curves and to estimate the risk for each outcome. The risks were compared via ratios and differences. We estimated the risk ratio for each outcome using only matched pairs in which both individuals were still at risk 7 days after receipt of the third vaccine dose in those vaccinated. We analysed outcomes in the full population and in subgroups defined by strata of age, sex, and number of comorbidities. 95% CIs were calculated using the nonparametric percentile bootstrap method with 1000 repetitions. The effectiveness of the third dose was estimated as 1 – risk ratio. As a sensitivity analysis, vaccine effectiveness was also estimated as 1 – incidence rate ratio derived from a Poisson regression using the same dataset, with no further adjustment. Analyses were done using R software (version 4.0.4).
We conducted an ecological analysis in which we plotted daily incidence proportions of SARS-CoV-2 infection (ie, positive PCR test) among the at-risk population by age group around the time the third dose vaccination campaign started.
Role of the funding source
The funder of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report.
Results
Between July 30, 2020, and Sept 23, 2021, 1 158 269 individuals were eligible to be included in the third dose group (appendix pp 20–21, 23). After matching, the third dose and control groups each included 728 321 individuals, with a median age of 52 years (IQR 37–68) and 51% were female (table 1). Baseline demographics were similar between the eligible population (ie, 1 158 269 individuals) and the matched population included in the study. Total follow-up time was 12 632 473 days, with a median follow-up time of 13 days (IQR 6–21) after the first 7 days in both groups, and a maximum follow-up time of 55 days.
Table 1Baseline characteristics
CDC=Centers for Disease Control and Prevention. BMI=body-mass index.
198 476 individuals appear in both groups, as they were first recruited as unvaccinated and then, following vaccination, re-recruited as vaccinated.
Effectiveness of the third vaccine dose, compared with two doses only, was estimated to be 93% (95% CI 88–97; 231 events for two doses vs 29 events for three doses) against admission to hospital, 92% (82–97; 157 vs 17 events) against severe disease, and 81% (59–97; 44 vs seven events) against COVID-19-related death (table 2). Cumulative incidence curves for COVID-19-related admission to hospital began to diverge around 6 days after vaccination; for severe disease and COVID-19-related death, divergence was seen at around 8–9 days after vaccination (figure 1). The estimated third-dose vaccine effectiveness against admission to hospital and severe disease was similar between males and females, and between individuals aged 40–69 years and those aged at least 70 years (table 3).
Table 2Effectiveness of the third vaccine dose versus two vaccine doses of the BNT162b2 mRNA COVID-19 vaccine
Estimates were obtained using the Kaplan-Meier estimator starting from day 7 after receipt of the third dose, in those who received it.
Figure 1Cumulative incidence curves comparing COVID-19-related admission to hospital (A), severe disease (B), and death (C) in individuals who received two versus three doses of the BNT162b2 mRNA COVID-19 vaccine
Show full caption
The dashed vertical line indicates day 7, on which the main analysis period begins.
Table 3Subgroup analysis of the effectiveness of the third vaccine dose versus two vaccine doses of the BNT162b2 mRNA COVID-19 vaccine
Estimates were obtained using the Kaplan-Meier estimator starting from day 7 after receipt of the third dose in those who received it. Data are listed as NA when one or both of the study groups do not have any events. NA=not available.
Third-dose vaccine effectiveness against documented SARS-CoV-2 infection was estimated to be 88% (95% CI 87–90; 6131 events for two doses vs 1135 events for three doses) and against symptomatic infection was 91% (89–92; 3345 vs 514 events; table 4). Individuals who received the third dose were tested less frequently for SARS-CoV-2 infection during follow-up than those who did not.
Table 4Infection outcomes in those who received a third vaccine dose versus two vaccine doses of the BNT162b2 mRNA COVID-19 vaccine
Estimates were obtained starting from day 7 after receipt of the third dose in those who received it. Tests were counted during the study follow-up period for each patient.
A sensitivity analysis defining booster effectiveness as 1 – incidence rate ratio yielded similar results: 87% (95% CI 82–92) against admission to hospital, 89% (83–94) against severe disease, and 84% (67–93) against COVID-19-related death (appendix p 22).
Our ecological analysis showed that, shortly after the third-dose vaccination campaign was initiated in each age group, the incidence trend began to decline in the respective age groups when compared with that of age groups not yet eligible (figure 2).
Figure 2Daily incidence of SARS-CoV-2 infection for different age groups around initiation of third dose vaccination
Show full caption
Daily incidence proportions of SARS-CoV-2 infection (ie, positive PCR-test) among the at-risk population by age group around the time the third dose vaccination was initiated (left Y axis). For each age group, the vertical dashed line with the same colour is the day that age group became eligible for the third dose. The epidemic curve (daily incidence counts) is shown shaded in the background (right Y axis). All curves were smoothed by using a moving 7-day mean, assigning for each day the value of the mean of the 7 days ending on that day.
Discussion
In this large observational study conducted using nationwide mass vaccination data in Israel, we estimated that a third dose of the BNT162b2 mRNA COVID-19 vaccine is effective in preventing severe COVID-19-related outcomes. Compared with two doses of the vaccine administered at least 5 months before, adding a third dose was estimated to be 93% effective in preventing COVID-19-related admission to hospital, 92% in preventing severe disease, and 81% in preventing COVID-19-related death, as of 7 or more days after the third dose.
Third-dose vaccine effectiveness against admission to hospital and severe disease was estimated to be similar between males and females, and between individuals aged 40–69 years and at least 70 years. In those aged 16–39 years, the rate of these severe outcomes was too small for meaningful estimation of the booster effectiveness. Effectiveness was also similar among groups defined by the number of comorbidities.
Most previous studies on this topic have focused on the antibody response elicited by the third dose of mRNA vaccines.
5
Ducloux D
Colladant M
Chabannes M
Yannaraki M
Courivaud C
Humoral response after 3 doses of the BNT162b2 mRNA COVID-19 vaccine in patients on hemodialysis.
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6
Pfizer Second quarter 2021 earnings teleconference.
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7
Wu K
Choi A
Koch M
et al.
Preliminary analysis of safety and immunogenicity of a SARS-CoV-2 variant vaccine booster.
Two recent studies from Israel reported on the effectiveness of the third dose in preventing clinical outcomes. The first study estimated a reduction of 92–97% in the risk for severe disease starting from day 12 after receipt of the third dose,
19
Bar-On YM
Goldberg Y
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et al.
Protection of BNT162b2 vaccine booster against COVID-19 in Israel.
but did not adjust for pre-existing clinical conditions related to the risk of severe disease, and did not evaluate the effectiveness within subgroups. A second study, which adjusted for various confounders and used a test-negative design, estimated a reduction of 70–84% in the probability of testing positive for SARS-CoV-2 among the vaccinated,
20
Patalon T
Gazit S
Pitzer VE
Prunas O
Warren JL
Weinberger DM
Short term reduction in the odds of testing positive for SARS-CoV-2; a comparison between two doses and three doses of the BNT162b2 vaccine.
but did not consider more severe outcomes.
The optimal time to achieve maximum protection against SARS-CoV-2-related outcomes after a third vaccine is unknown. In this study, we estimated effectiveness starting from day 7 after the third dose, which is similar to the period used to define full vaccination after the second dose.
21
Polack FP
Thomas SJ
Kitchin N
et al.
Safety and efficacy of the BNT162b2 mRNA COVID-19 vaccine.
Our choice is supported by high concentrations of antibodies in individuals 7 days after administration of the third dose.
6
Pfizer Second quarter 2021 earnings teleconference.
It is possible, however, that some degree of protection begins earlier. Although an increase in antibody production can be identified on days 3–5 after administration of the second dose of SARS-CoV-2 mRNA vaccines,
22
Ogata AF
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et al.
Circulating SARS-CoV-2 vaccine antigen detected in the plasma of mRNA-1273 vaccine recipients.
for other vaccines (eg, influenza), antibodies and antibody-secreting cells are detected as early as day 2 after a booster dose.
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Moreover, a rapid response of the immune system can potentially prevent infections in individuals even if they were exposed to the virus shortly before the third dose. Such protection is termed the post-exposure effect
25
Postexposure effects of vaccines on infectious diseases.
and is well established in vaccinations for other pathogens, such as varicella,
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measles,
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and hepatitis A.
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Our study has several limitations. First, differing testing frequencies between the groups do not allow unbiased estimates for the less severe secondary outcomes of documented infection and symptomatic infection. Second, as in any observational study, unmeasured confounding might exist. However, this concern is mitigated because our analysis was adjusted for various important possible confounders, including sociodemographic factors, clinical factors, and behavioural factors related to COVID-19. In addition, this study focuses on severe outcomes, which are less likely to be affected by differences in health-seeking behaviours or testing rates between groups. Third, due to the relative scarcity of events in individuals younger than 40 years, we could not evaluate vaccine effectiveness in this age group. Fourth, this vaccine effectiveness study did not explore potential adverse clinical events and excess health-care utilisation associated with the administration of a third dose. Finally, we excluded populations (health-care workers, those living in long-term care facilities, and those medically confined to their homes) that are likely to be targeted early to receive the booster dose.
There is an active debate surrounding the administration of third doses to individuals in some countries while other countries suffer from vaccine shortages.
29
WHO calls for halting COVID-19 vaccine boosters in favor of unvaccinated.
It is outside the scope of this epidemiological analysis to address the complex ethical issues involved in this debate, but there is an urgent need for increased vaccine production, distribution, and access worldwide. The present study was designed to use existing observational health data to study vaccine effectiveness in preventing specific COVID-19 outcomes, aiming to expand the scientific evidence base that might be useful in informing this broader discussion.
At the time of writing, many countries are experiencing a resurgence of SARS-CoV-2 infections despite hitherto successful vaccination campaigns, the cause of which is suggested to be the greater infectiousness of the delta variant and waning immunity as time passes from earlier vaccination. Regardless of the cause, these early findings suggest that a third dose of mRNA vaccine is effective in reducing severe COVID-19-related outcomes for patients who have received two doses at least 5 months before.
All authors conceived and designed the study. NB and ND collected and analysed the original data. NB, ND, and RDB had access to and verified the underlying data. All authors wrote the manuscript, critically reviewed the manuscript, and decided to proceed with publication. BYR and RDB supervised the study process. RDB vouches for the data and analysis.
Declaration of interests
NB, ND, and RDB report institutional grants to Clalit Research Institute from Pfizer outside the submitted work and unrelated to COVID-19, with no direct or indirect personal benefits. MAH reports grants from the US National Institutes of Health (NIH) and US Department of Veterans Affairs, and personal fees from Cytel and ProPublica. ML reports grants from Pfizer, NIH, the UK National Institute for Health Research, the US Centers for Disease Control and Prevention, Open Philanthropy Project, the Wellcome Trust, and Pfizer; personal fees from Merck, Bristol Meyers Squibb, Sanofi Pasteur, and Janssen; and unpaid advice given on Covid vaccines or vaccine studies to One Day Sooner, Pfizer, AstraZeneca, Janssen, and COVAXX (United Biosciences), outside the submitted work. BYR reports grants from NIH outside the submitted work. All other authors declare no competing interests.
