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 | Infectious Diseases | JAMA Internal Medicine | JAMA Network
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Table 1.  Characteristics of 26 823 Participants
Characteristics of 26 823 Participants
Table 2.  Descriptive Statistics of Symptom Prevalence by Belief and Serology Test Result Status
Descriptive Statistics of Symptom Prevalence by Belief and Serology Test Result Status
Table 3.  Associations Between Persistent Symptoms, Belief, and Serology Test Results
Associations Between Persistent Symptoms, Belief, and Serology Test Results
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    8 Comments for this article
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    Conclusion may not be valid
    Herbert Renz-Polster, MD | Mannheim Institute for Public Health, University of Heidelberg, Germany

    The authors  claim that “persistent physical symptoms after COVID-19 infection may be associated more with the belief in having been infected with SARS-CoV-2 than with having laboratory-confirmed COVID-19 infection.” (1) They base this statement on the absence of a positive correlation between typical symptoms of Long COVID and serological proof of a past SARS-CoV-2 infection.
    However, this conclusion may not be valid because the method used for ascertainment of past infection may not be accurate.

    First, a significant portion – indeed, up to 36 % - of infected adults may not seroconvert after SARS-CoV-2 infection and therefore
    may not have been identified by the serologic antibody test used. (2) (3) It has also been shown that patients who go on to develop Long COVID symptoms may be more likely to be among those who do not seroconvert after SARS-CoV-2 infection. (4) Therefore, the study may have misclassified a significant portion of patients with past COVID-19 infection as not infected in the past.

    Second, according to the manufacturer, the antibody test used in the study has a sensitivity of 87% and a specificity of 97.5 %. (1) This means that 13% of truly infected participants may have falsely been classified as non infected. The authors rightly assume that this may be a negligeable influence. However, what the authors - surprisingly - do not discuss, is the effect of the 2.5 % of possibly false positive results to be assumed. This fraction of false positive results in a study population of over 26,000 participants would amount to about 650 people who may have been classified as infected in the past when indeed they were not – and about half of those (49.6%, i.e. about 325 people) would have been included in the analysis.
    Given the fact that there were only 453 people in the group of participants with an apparent infection in the past, these concerns raise questions about the study results.

    In summary, the serological test used may be an unreliable marker for previous infection with SARS-CoV-2. This study therefore may not provide reliable data to support the authors' claims.


    References

    (1)
    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. JAMA Intern Med. Published online November 08, 2021. doi:10.1001/jamainternmed.2021.6454

    (2)
    Pathela P, Crawley A, Weiss D, et al. Seroprevalence of Severe Acute Respiratory Syndrome Coronavirus 2 Following the Largest Initial Epidemic Wave in the United States: Findings From New York City, 13 May to 21 July 2020. J Infect Dis. 2021;224(2):196-206. doi:10.1093/infdis/jiab200

    (3)
    Liu W, Russell RM, Bibollet-Ruche F, et al. Predictors of Nonseroconversion after SARS-CoV-2 Infection. Emerging Infectious Diseases. 2021;27(9):2454-2458. doi:10.3201/eid2709.211042

    (4)
    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. J Clin Immunol 41, 1490–1501 (2021). https://doi.org/10.1007/s10875-021-01083-7
    CONFLICT OF INTEREST: None Reported
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    Conclusion not supported by data
    Jean-Francois Grenier, MD |
    Saying that "persistent physical symptoms after COVID-19 infection may be associated more with the belief in having been infected with SARS-CoV-2 than with having laboratory-confirmed COVID-19 infection" is not supported by the data presented in this article.
    First, the study does not focus on "symptoms after COVID-19 infection," but rather on "self-reported beliefs of having had COVID-19 infection," which is very different.
    Second, extrapolating the 87% sensitivity of the Euroimmune ELISA test, that comes from a small study where median time to COVID onset was 44 days and in which convalescent patients with COVID onset more than 6 months ago
    were excluded, introduces a major bias in adjudicating presence or absence of past COVID. This is especially true when one knows that IgGs against SARS CoV 2 are waning over time.

    CONFLICT OF INTEREST: None Reported
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    Authors’ reply to Dr Grenier’s comments
    Cedric Lemogne, MD, PhD | Université de Paris, AP-HP, INSERM
    As described in the Methods section, our study did focus not only on the belief of having had COVID-19, but also on self-reported persistent physical symptoms, which were not considered as beliefs.

    Regarding the sensitivity of the Euroimmune ELISA test over time, assuming the worst-case scenario of a sensitivity (se) of the serology of 61.2 % at 9 months after the initial episode (1,2), with a prevalence (p) of 4% and a specificity (sp) of 97.5%, the probability of having had COVID-19 given a positive serology result would be about 50% (i.e., p*se/(p*se+(1-p)*(1-sp))) whereas the probability of having had
    COVID given a negative serology result would be about 1.6% (i.e., p*(1-se)/(p*(1-se)+(1-p)*sp))). Although 50% of false positive would not allow any conclusion on an individual level, the likelihood of having had COVID-19 would nonetheless be 30 times higher in participants with positive serology results than in those with negative serology results. On a populational level, serology is thus a powerful tool to examine clinical outcomes associated with an actual infection. Should persistent symptoms be uniquely associated with a past infection by SARS-CoV-2, we would thus have observed a robust association between serology results and these symptoms. Of course, this worst-case scenario is highly implausible, given that the participants had their serology between May and November 2020.

    References
    1. Kahre E, Galow L, Unrath M, Haag L, Blankenburg J, Dalpke AH, et al. Kinetics and seroprevalence of SARS-CoV-2 antibodies: a comparison of 3 different assays. Sci Rep. 21 juill 2021;11:14893.
    2. Perez-Saez J, Zaballa M-E, Yerly S, Andrey DO, Meyer B, Eckerle I, et al. Persistence of anti-SARS-CoV-2 antibodies: immunoassay heterogeneity and implications for serosurveillance. Clin Microbiol Infect. nov 2021;27(11):1695.e7-1695.e12.
    CONFLICT OF INTEREST: Corresponding author of the article
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    Authors’ reply to Dr Renz-Polster’s comments
    Cedric Lemogne, MD, PhD | Université de Paris, AP-HP, INSERM
    We acknowledge that the issue of false positive was not discussed in our article. We thank Dr Renz-Polster for this opportunity to clarify how reliable the serology results might be in the context of our study.

    Assuming a prevalence (p) of past infection of 4 %, a sensitivity (se) of 87 % and a specificity (sp) of 97.5 % (1), the probability of having had COVID-19 given a positive serology result is about 59% (i.e., p*se/(p*se+(1-p)*(1-sp))), whereas the probability of having had COVID given a negative serology result is about 0.5% (i.e., p*(1-se)/(p*(1-se)+(1-p)*sp))). Although we agree that 59% is
    not that good on an individual level, it means that the likelihood of having had COVID-19 is more than 100 times more likely in participants with positive serology results. On a populational level, serology is thus a powerful tool to examine clinical outcomes associated with an actual infection.

    Please note that this conclusion still holds when assuming the worst-case scenario of a sensitivity of the serology of 61.2 % at 9 months after the initial episode (2,3). In this case, the likelihood of having had COVID-19 would have been 30 times higher in participants with positive serology results than in those with negative serology results. Should persistent symptoms be uniquely associated with a past infection by SARS-CoV-2, we would have observed a robust association between serology results and these symptoms.

    Regarding the hypothesis that a weak anti-SARS-CoV-2 antibody response could be a risk factor of ´long COVID’, we did take this hypothesis into account in our analysis by computing additional logistic regression models including a belief by serology interaction for each persistent symptom (4). Should a negative serology after COVID-19 be a risk factor of ‘long COVID’, it would have resulted in a significant negative interaction, with the belief of having had COVID-19 being more strongly associated with persistent symptoms among those with negative than positive serology results. Against this hypothesis, there was no significant interaction (neither positive nor negative) for any of the 18 tested persistent symptoms.

    References
    1. Carrat F, de Lamballerie X, Rahib D, Blanché H, Lapidus N, Artaud F, et al. Antibody status and cumulative incidence of SARS-CoV-2 infection among adults in three regions of France following the first lockdown and associated risk factors: a multicohort study. Int J Epidemiol. 10 nov 2021;50(5):1458‑72
    2. Kahre E, Galow L, Unrath M, Haag L, Blankenburg J, Dalpke AH, et al. Kinetics and seroprevalence of SARS-CoV-2 antibodies: a comparison of 3 different assays. Sci Rep. 21 juill 2021;11:14893
    3. Perez-Saez J, Zaballa M-E, Yerly S, Andrey DO, Meyer B, Eckerle I, et al. Persistence of anti-SARS-CoV-2 antibodies: immunoassay heterogeneity and implications for serosurveillance. Clin Microbiol Infect. nov 2021;27(11):1695.e7-1695.e12
    4. Matta J, Wiernik E, Robineau O, Carrat F, Touvier M, Severi G, 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. JAMA Intern Med. 8 nov 2021
    CONFLICT OF INTEREST: Corresponding author of the article
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    Concerns about the Study
    Silvia Guerrero, phD in Biochem&Molec Biol | Coordinator of reseach group of Long Covid ACTS

    The results of this cross-sectional analysis of a large, population-based French cohort suggest that physical symptoms persisting 10 to 12 months after the COVID-19 pandemic first wave may be associated more with the belief in having experienced COVID-19 infection than with actually being infected with the SARS-CoV-2 virus.
    This conclusion is based on the lack of correlation between persistent symptoms and positive specific SARS-COV-2 serology results.
    There is insufficient evidence about the generation or duration of antibodies in specific subpopulations to infer that negative serology testing is synonymous with not having  the infection when clinical symptoms are
    present.  Long COVID has been associated with weak anti-SARS-CoV-2 antibody response (1).
    In addition, many Long COVID patients produce no detectable specific anti-SARS-COV-2 antibodies at all during their illness but many test positive for SARS-COV-2 specific cellular response, when performed, several months after the first infection. The results of a survey launch by a Spanish Long COVID patient organization support this conclusion (2).
    Further, patients with Long COVID have specific inflammation profiles (3) and virus spike protein has been found in CD16+ monocytes up to 15 months after infection (4) regardless of whether patients have positive serology against SARS-COV-2.

    1. Javier García-Abellán, Sergio Padilla, Marta Fernández-González, José A. García, Vanesa Agulló, María Andreo, Sandra Ruiz, Antonio Galiana, Félix Gutiérrez, and Mar Masiá. Antibody Response to SARS-CoV-2 is Associated with Long-term Clinical Outcome in Patients with COVID-19: a Longitudinal Study. J Clin Immunol. 2021 Jul 17 : 1–12.doi: 10.1007/s10875-021-01083-7 [Epub ahead of print]
    2. Nerea Montes, Èlia Domènech, Sílvia Guerrero, Bárbara Oliván-Blázquez, Rosa Magallón-Botaya. Analysis of cell-mediated immunity in people with long COVID. doi: 10.1101/2021.06.09.21258553 (bioRxiv preprint)
    3. Bruce K Patterson, Jose Guevara-Coto, Ram Yogendra, Edgar B Francisco, Emily Long, Amruta Pise, Hallison Rodrigues, Purvi Parikh, Javier Mora, Rodrigo A Mora-Rodríguez. Immune-Based Prediction of COVID-19 Severity and Chronicity Decoded Using Machine Learning. Front Immunol. 2021 Jun 28;12:700782. doi: 10.3389/fimmu.2021.700782. eCollection 2021.
    4. Bruce K. Patterson, Edgar B. Francisco, Ram Yogendra, Emily Long, Amruta Pise, Hallison Rodrigues, Eric Hall, Monica Herrara, Purvi Parikh, Jose Guevara-Coto, Xaiolan Chang, Jonah B Sacha, Rodrigo A Mora-Rodríguez, Javier Mora. Persistence of SARS CoV-2 S1 Protein in CD16+ Monocytes in Post-Acute Sequelae of COVID-19 (PASC) Up to 15 Months Post-Infection. doi: 10.1101/2021.06.25.449905 (bioRxiv preprint)
    CONFLICT OF INTEREST: None Reported
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    Assessing participants' self-report of having had COVID-19
    Nicholas Brown, PhD | Linnaeus University, Sweden
    It is understandable why some people in the study would believe they had COVID-19 infection because they had received confirmation, via a test or expert medical opinion, as shown in eTable 5.  (Unfortunately, it seems that neither the article nor the supplement tells us whether this proportion differed between the S− and S+ groups.) Thus, given the false positive rate of the serology test, the proportion of true cases of COVID among those who “believe” they had it is likely to be higher than the proportion of true cases of COVID among those who tested positive (cf. the comment above from Dr. Herbert Renz-Polster), even if every one of the participants who answered “No, but I think I had it” was mistaken. For the two-thirds of Belief+ participants who had a test result or medical examination to back them up, to “believe” that they had COVID was entirely rational; indeed, a statement by a member of this group that they did not “believe” they had been infected might itself be considered a denial of the scientific evidence.

    Matta et al.’s conclusion was that “belief” that one had had COVID was a stronger predictor of long COVID symptoms than a serology test. But an equally plausible interpretation is that the dried-blood serology test is not as good a way of determining whether one has been infected as asking patients. Yet this study has been extensively misinterpreted  as indicating the opposite; that is, that a large proportion of participants who have long COVID symptoms never actually had COVID in the first place. The possibilities for harm to patients if such erroneous ideas were to spread among medical professionals, policymakers, and the public are substantial. As a minimum, no conclusions should be drawn about the reality of long COVID until a replication has been conducted, this time using the gold standard of a positive PCR test (of which many millions have now been carried out worldwide, including in France) as the criterion for determining SARS-CoV-2 infection objectively.
    CONFLICT OF INTEREST: None Reported
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    Misclassification bias questions the conclusions
    Esther Rodriguez Rodriguez | MD, Psychiatrist in Acute Adolescent Hospitalization in Barcelona.
    The study uses serology results to determine if any prolonged symptoms are associated with infection. Despite the known limitations of serology tests, they can be useful when comparing positive and negative serologies within a sufficiently large population. And in fact, model 2 shows “a positive serology test result was associated with 10 categories of persistent symptoms”.

    But the validity of this identification becomes questionable when separating analysis of the participants by “belief”. It seems that misclassification bias was not ruled out for the other serology models (model 3 and following), which only demonstrate an association with anosmia. False positives
    should be treated as negative serologies, and may be assumed to have the same “belief” distribution, meaning most of them would fall into the “Belief-” group. We might also expect that false negatives (individuals who were in fact previously infected) would fall into the “Belief+” group, especially since 65% of them have confirmation in the form of a clinical diagnosis or a test. Whatever the serological result, the rate of actual infection should be very high for individuals who report having had an infection, and very low for those who do not.

    These distributions dramatically reduce the usefulness of serology to identify association with actual Covid-19 infection. Are prolonged symptoms really expected to be statistically significant in the mutually adjusted models? We assume that anosmia is the only symptom to stand out because it is the symptom most specific to Covid-19 but close review of the data shows its odds ratio collapses from 15.7 (model 2) to 2.73 (model 3), which is further evidence of misclassification. This in itself represents sufficient bias to question the conclusions.
    CONFLICT OF INTEREST: None Reported
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    Considering anosmia as very specific to Covid-19 leads to a different conclusion
    Eleni Iasonidou, MD | Primary care
    The authors appear to consider anosmia to be the only symptom specific to Covid-19 and claim this to be consistent with anosmia being the only symptom associated with positive serology.

    A closer look at the data raises questions. The association of anosmia with the “belief” that one had Covid-19 looks stronger (odds ratio of 28.66) than the association with serology (odds ratio of 15.69), and this is enhanced after mutual adjustment, when the odds ratio of anosmia is only 2.72 for serology, compared to 16.37 for “belief”. Thus, anosmia, “a hallmark of Covid-19 infection”, is much more highly correlated
    with belief than with serology – throwing the study’s conclusions into question.

    This specificity of anosmia implies that the number of affected individuals should be directly correlated to the number of infections. Within the seropositives, the rate of anosmia is 8.8 times higher among those who believe they have been infected ("Belief+" 9.7%) than among those who believe they have not ("Belief–" 1.1%), and the same ratio should be assumed for infection rates. This unbalanced distribution provides a convincing explanation for why prolonged symptoms continue to be associated with “belief” but not with serology after mutual adjustment, and further confirms the misclassification bias raised by Dr Esther Rodriguez Rodriguez using different data from the same study.

    Moreover, we can deduce from the rates of anosmia in the “Belief+” population (7.0%) and in the “Serology+” population (4.7%) that the first group contains 1.5 times more infected individuals than the latter group. In other words, “belief” seems more accurate than serology in identifying Covid-19 infection (what is expected when two-third of the "belief-positive" have received a physician diagnosis or a positive lab result), and the multiple symptoms other than anosmia associated with “belief” are likely to be consequences of the disease.

    It is perhaps relevant that when infection is confirmed by PCR/LFT test or clinical diagnosis (model 7), the point estimates of the odds ratios are greater than 1 for most of the prolonged symptoms. Although the sample size is too limited for these individual estimates to reach conventional levels of statistical significance (i.e., their 95% confidence intervals do not include 1.0), this cumulative evidence across symptoms is nevertheless suggestive of an association of these prolonged symptoms with Covid-19.
    CONFLICT OF INTEREST: None Reported
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    Original Investigation
    November 8, 2021

    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

    Author Affiliations
    • 1Université de Paris, “Population-based Cohorts Unit,” Institut National de la Santé et de la Recherche Médicale (INSERM), Paris Saclay University, Université de Versailles-Saint-Quentin-en-Yvelines, UMS 011, Paris, France
    • 2Université Lille, Centre Hospitalier de Tourcoing, ULR 2694-METRICS: Évaluation des technologies de santé et des pratiques médicales, Lille, France
    • 3Sorbonne Université, INSERM, Institut Pierre Louis d’Epidémiologie et de Santé Publique, Département de Santé Publique, Hôpital Saint-Antoine, Assistance publique–Hôpitaux de Paris (AP-HP), Paris, France
    • 4Sorbonne Paris Nord University, INSERM U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center–University of Paris (CRESS), Bobigny, France
    • 5Université Paris-Saclay, UVSQ, INSERM, CESP U1018, Gustave Roussy, Villejuif, France
    • 6Department of Statistics, Computer Science, Applications “G. Parenti,” University of Florence, Florence, Italy
    • 7Unité des Virus Emergents, UVE: Aix Marseille Université, IRD 190, INSERM 1207, Institut Hospitalo-Universitaire Méditerranée Infection, Marseille, France
    • 8Centre d’Etude du Polymorphisme Humain, Fondation Jean Dausset, Paris, France
    • 9AP-HP, Hôpital Hôtel-Dieu, Département Médico-Universitaire Psychiatrie et Addictologie, Service de Psychiatrie de l’adulte, Paris, France
    • 10Université de Paris, AP-HP, Hôpital Corentin-Celton, DMU Psychiatrie et Addictologie, Service de Psychiatrie de l’adulte et du sujet âgé, INSERM, Institut de Psychiatrie et Neurosciences de Paris (IPNP), UMR_S1266, Paris, France
    • 11Université de Paris, AP-HP, Hôpital Européen Georges-Pompidou, DMU endocrinologie, ophtalmologie, médecine infectieuse, médecine interne & immunologie, médecine sociale, Service de Médecine interne, Paris, France
    • 12Université de Paris, AP-HP, Hôpital Hôtel-Dieu, DMU Psychiatrie et Addictologie, Service de Psychiatrie de l’adulte, INSERM, IPNP, UMR_S1266, Paris, France
    JAMA Intern Med. 2022;182(1):19-25. doi:10.1001/jamainternmed.2021.6454
    Key Points

    Question  Are the belief in having had COVID-19 infection and actually having had the infection as verified by SARS-CoV-2 serology testing associated with persistent physical symptoms during the COVID-19 pandemic?

    Findings  In this cross-sectional analysis of 26 823 adults from the population-based French CONSTANCES cohort during the COVID-19 pandemic, self-reported COVID-19 infection was associated with most persistent physical symptoms, whereas laboratory-confirmed COVID-19 infection was associated only with anosmia. Those associations were independent from self-rated health or depressive symptoms.

    Meaning  Findings suggest that persistent physical symptoms after COVID-19 infection should not be automatically ascribed to SARS-CoV-2; a complete medical evaluation may be needed to prevent erroneously attributing symptoms to the virus.

    Abstract

    Importance  After an infection by SARS-CoV-2, many patients present with persistent physical symptoms that may impair their quality of life. Beliefs regarding the causes of these symptoms may influence their perception and promote maladaptive health behaviors.

    Objective  To examine the associations of self-reported COVID-19 infection and SARS-CoV-2 serology test results with persistent physical symptoms (eg, fatigue, breathlessness, or impaired attention) in the general population during the COVID-19 pandemic.

    Design, Setting, and Participants  Participants in this cross-sectional analysis were 26 823 individuals from the French population-based CONSTANCES cohort, included between 2012 and 2019, who took part in the nested SAPRIS and SAPRIS-SERO surveys. Between May and November 2020, an enzyme-linked immunosorbent assay was used to detect anti–SARS-CoV-2 antibodies. Between December 2020 and January 2021, the participants reported whether they believed they had experienced COVID-19 infection and had physical symptoms during the previous 4 weeks that had persisted for at least 8 weeks. Participants who reported having an initial COVID-19 infection only after completing the serology test were excluded.

    Main Outcomes and Measures  Logistic regressions for each persistent symptom as the outcome were computed in models including both self-reported COVID-19 infection and serology test results and adjusting for age, sex, income, and educational level.

    Results  Of 35 852 volunteers invited to participate in the study, 26 823 (74.8%) with complete data were included in the present study (mean [SD] age, 49.4 [12.9] years; 13 731 women [51.2%]). Self-reported infection was positively associated with persistent physical symptoms, with odds ratios ranging from 1.39 (95% CI, 1.03-1.86) to 16.37 (95% CI, 10.21-26.24) except for hearing impairment (odds ratio, 1.45; 95% CI, 0.82-2.55) and sleep problems (odds ratio, 1.14; 95% CI, 0.89-1.46). A serology test result positive for SARS-COV-2 was positively associated only with persistent anosmia (odds ratio, 2.72; 95% CI, 1.66-4.46), even when restricting the analyses to participants who attributed their symptoms to COVID-19 infection. Further adjusting for self-rated health or depressive symptoms yielded similar results. There was no significant interaction between belief and serology test results.

    Conclusions and Relevance  The findings of this cross-sectional analysis of a large, population-based French cohort suggest that persistent physical symptoms after COVID-19 infection may be associated more with the belief in having been infected with SARS-CoV-2 than with having laboratory-confirmed COVID-19 infection. Further research in this area should consider underlying mechanisms that may not be specific to the SARS-CoV-2 virus. A medical evaluation of these patients may be needed to prevent symptoms due to another disease being erroneously attributed to “long COVID.”

    Introduction

    After infection by SARS-CoV-2, both hospitalized and nonhospitalized patients have an increased risk of various persistent physical symptoms that may impair their quality of life, such as fatigue, breathlessness, or impaired attention.1-3 Although the term “long COVID” has been coined to describe these symptoms4 and putative mechanisms have been proposed,3,5,6 the symptoms may not emanate from SARS-CoV-2 infection per se but instead may be ascribed to SARS-CoV-2 despite having other causes. In this study, we examined the association of self-reported COVID-19 infection and of serology test results with persistent physical symptoms. We hypothesized that the belief in having been infected with SARS-CoV-2 would be associated with persistent symptoms while controlling for actual infection.

    Methods

    The French CONSTANCES population-based cohort study7 received ethical approval and included approximately 200 000 volunteers who were aged 18 to 69 years between 2012 and 2019 and who consented to be followed up through annual questionnaires and linked administrative databases.8 A total of 35 852 volunteers responding to annual questionnaires through the internet were invited to take part in the nested Santé, Pratiques, Relations et Inégalités Sociales en Population Générale Pendant la Crise COVID-19 (SAPRIS) and SAPRIS-Sérologie (SERO) surveys.9,10 Ethical approval and written or electronic informed consent were obtained from each participant before enrollment in the original cohort. The SAPRIS survey was approved by the French Institute of Health and Medical Research ethics committee, and the SAPRIS-SERO study was approved by the Sud-Mediterranée III ethics committee. Electronic informed consent was obtained from all participants for dried-blood spot testing. No one received compensation or was offered any incentive for participating in this study. Quiz Ref IDThe present study is a cross-sectional analysis of data from the SAPRIS and SAPRIS-SERO surveys nested in the French CONSTANCES cohort.

    Serologic Testing

    Between May and November 2020, self-sampling dried-blood spot kits were mailed to each participant. Each kit included material (a dried-blood spot card, lancets, and a pad), printed instructions, and an addressed, stamped, and padded envelope to be returned with the card to a centralized biobank (CEPH Biobank). Received blood spots were visually assessed, registered, punched, and stored in tubes (0.5 mL, FluidX 96-Format 2D code; Brooks Life Sciences) at −30 °C. Eluates were processed with an enzyme-linked immunosorbent assay (Euroimmun) to detect anti–SARS-CoV-2 antibodies (IgG) directed against the S1 domain of the virus spike protein. A test was considered positive for SARS-CoV-2 when the results indicated an optical density ratio of 1.1 or greater (sensitivity, 87%; specificity, 97.5%).11 The participants received their serology test results by mail or email.

    Self-reported COVID-19 Infection

    Between December 2020 and January 2021, the participants answered this question from the fourth SAPRIS questionnaire: “Since March, do you think you have been infected by the coronavirus (whether or not confirmed by a physician or a test)?” Participants answered “Yes,” “No,” or “I don’t know.” At the time they answered this question, the participants were aware of their serology test results (eFigure in Supplement 1). A total of 2788 participants (7.8%) who answered “I don’t know” were excluded.

    The participants who answered “Yes” additionally answered this question: “When did you get the coronavirus? Between March and June; In July or August; Between September and now.” Participants who indicated having been initially infected after serologic testing (n = 1312 [3.6%]) were excluded. The participants who answered “Yes” also answered this question: “Has this been confirmed? Yes, by virological or PCR test (based on nose swab; results provided after at least 24 hours); Yes, by antigenic test performed (based on nose swab; results provided within 1 hour); Yes, by serological test (based on a blood test; results provided after at least 24 hours); Yes, by rapid diagnostic test (based on blood test; results provided within 1 hour); Yes, by saliva test; Yes, by chest CT scan; Yes, by a physician (without testing); No, but I think I had it; I don’t know.”

    Persistent Physical Symptoms

    In the same questionnaire, symptoms were measured by the following question: “Since March 2020, have you had any of the following symptoms that you did not usually have before?” On the basis of the literature,1-3 the following symptoms were explored: sleep problems, joint pain, back pain, muscular pain, sore muscles, fatigue, poor attention or concentration, skin problems, sensory symptoms (pins and needles, tingling or burning sensation), hearing impairment, constipation, stomach pain, headache, breathing difficulties, palpitations, dizziness, chest pain, cough, diarrhea, anosmia, and other symptoms.

    Two additional questions were asked for each symptom: “Has this symptom been present in the past 4 weeks?” Participants answered “Yes, but not present anymore,” “Yes, and still present,” or “No”; “How much time did this symptom last? Or how long has it been since you have had this symptom (if it is still present)?” with possible responses ranging from “Less than a week” to “More than 8 weeks.” To avoid considering symptoms that were no longer present or only transient and to limit recall bias, only participants who responded “Yes” and “More than 8 weeks” to these 2 questions were considered as having persistent symptoms. Because we aimed to compare participants who self-reported having had COVID-19 infection with those who did not, we did not distinguish between persistent symptoms that were similar to those experienced at the time of the initial episode and potentially new symptoms.

    Participants who declared having any of the listed persistent symptoms also answered the following question: “Do you attribute the current symptoms to COVID-19?” and participants answered “Yes, all”; “Yes, only a few”; “No”; or “I don’t know.” Participants who answered “Yes, all” or “Yes, only a few” were considered to attribute their symptoms to COVID-19 infection.

    Covariates

    Age, sex, educational level, income, and self-rated health in 2019 were obtained from the inclusion questionnaire and the 2019 CONSTANCES questionnaire. Depressive symptoms during the pandemic were measured as part of the SAPRIS survey by using the Center for Epidemiologic Studies Depression Scale.12

    Statistical Analysis

    The crude prevalence of persistent physical symptoms was first calculated for 4 groups of participants according to both belief (ie, self-reported COVID-19 infection) and serology test results: belief negative and serology negative; belief positive and serology negative; belief negative and serology positive; and belief positive and serology positive. We used χ2 tests to search for between-group differences. To specifically test our hypothesis, we used separate logistic regressions for each persistent symptom as the outcome computed in models including either belief (model 1), serology test result (model 2), or both (model 3), adjusting for age, sex, income, and educational level. Additional models searched for belief by serology test result interactions. In sensitivity analyses, the models were further adjusted for self-rated health or depressive symptoms. Exploratory analyses were restricted to participants attributing their persistent symptoms to COVID-19 infection. A 2-sided value of P < .05 was considered statistically significant. All analyses were conducted using SAS, version 9.4 (SAS Institute Inc).

    Results

    Of 35 852 volunteers invited to participate in this cross-sectional analysis, a cohort of 26 823 (74.8%) with complete data were included (mean [SD] age, 49.4 [12.9] years; 13 731 women [51.2%]; and 13 092 men [48.8%]) (Table 1). The crude prevalence rates of persistent symptoms by belief and by serology test result categories are given in Table 2. Compared with participants in the CONSTANCES cohort, the participants in the present study were more likely to be older, men, more educated, have higher levels of income, and have better self-reported health (eTable 1 in Supplement 1). Quiz Ref IDThe prevalence of persistent physical symptoms ranged from 0.5% (146 participants with anosmia) to 10.2% (2729 participants with sleep problems). A total of 1091 participants had a serology test result positive for SARS-CoV-2, including 453 participants (41.5%) who subsequently reported having had COVID-19 infection before the serology test. A total of 914 participants reported having had COVID-19 infection before the serology test, including 453 (49.6%) with a serology test result positive for SARS-CoV-2 (Table 2). Differences in covariates according to the serology test results, the belief in having had COVID-19 infection, and both are reported in eTables 2, 3, and 4 in Supplement 1. Whether or not the diagnosis was confirmed by a laboratory test or by a physician among the participants with a positive belief is reported in eTable 5 in Supplement 1.

    Before adjustment, the belief in having had COVID-19 infection was associated with 15 of 18 categories of persistent symptoms (Table 3, model 1), whereas a positive serology test result was associated with 10 categories of persistent symptoms (Table 3, model 2). Quiz Ref IDAfter mutual adjustment, positive belief was significantly associated with higher odds of having all persistent symptoms, with odds ratios (ORs) ranging from 1.39 (95% CI, 1.03-1.86) to 16.37 (95% CI, 10.21-26.24) except for hearing impairment (OR, 1.45; 95% CI, 0.82-2.55) and sleep problems (OR, 1.14; 95% CI, 0.89-1.46) (Table 3, model 3). Quiz Ref IDBy contrast, a positive serology test result remained positively associated only with anosmia (OR, 2.72; 95% CI, 1.66-4.46) and was negatively associated with skin problems (OR, 0.49; 95% CI, 0.29-0.85) (Table 3, model 3). There was no significant interaction between belief and serology. Adjusting for self-rated health or depressive symptoms yielded similar results except for joint pain (OR, 1.31; 95% CI, 0.97-1.77) and back pain (OR, 1.29; 95% CI, 0.97-1.72), which were no longer associated with belief when adjusting for depressive symptoms (eTable 6 in Supplement 1).

    Restricting the analyses to participants with a positive belief and attributing their persistent symptoms to COVID-19 showed a positive serology test result to be associated only with anosmia (OR, 2.97; 95% CI, 1.58-5.57) (eTable 7 in Supplement 1). Similarly, confirmation of the diagnosis by a laboratory test or by a physician (vs the response, “No, but I think I had it,” and excluding participants who answered “I don’t know”) was also associated only with anosmia (OR, 4.29; 95% CI, 1.92-9.58) (eTable 7 in Supplement 1).

    Discussion

    This cross-sectional analysis of data from a population-based cohort found that persistent physical symptoms 10 to 12 months after the COVID-19 pandemic first wave were associated more with the belief in having experienced COVID-19 infection than with having laboratory-confirmed SARS-CoV-2 infection.

    In previous studies, the association between persistent symptoms and SARS-CoV-2 serology test results may be explained by the belief in having experienced COVID-19 infection.13 Furthermore, most previous studies assessing “long COVID” included only patients who had COVID-19 infection, thus lacking a control group of patients who did not have the infection.3,14 Indeed, our results showed that the persistent physical symptoms observed after COVID-19 infection were quite frequent in the general population. Because our study also included participants who reported not having had COVID-19 infection with either positive or negative serology test results, we were able to compare the prevalence of persistent physical symptoms according to these 2 variables. We were also able to perform analyses restricted to participants attributing their persistent symptoms to COVID-19 infection. Although our study did not assess long COVID per se because we also included participants without COVID-19 infection, these specific analyses may be more representative of the long COVID clinical issue in real-life settings15 than the picture provided by cohorts of patients with a laboratory-confirmed or physician-documented COVID-19 infection.

    Although the participants were aware of the serology results when they reported having had COVID-19 infection or not, less than half of those with a positive serology test reported having experienced the disease. Conversely, among those who reported having had the disease, approximately half had a negative serology test result, consistent with some findings in clinical settings.15 These results, which allowed for disentangling the correlates of the serology test results from those of the belief in having had COVID-19 infection, were not unexpected. First, patients with a positive serology test result but no or only mild symptoms of COVID-19 infection may not believe that they had the disease. Because persistent symptoms may be more frequent among patients who experienced a higher number of acute COVID-19 symptoms,16 the severity of the initial episode may partially confound the association between the belief in having experienced COVID-19 infection and persistent symptoms among participants with positive serology test results. However, this belief was associated with persistent symptoms to a similar extent among participants with negative serology test results as shown by the lack of any interaction between belief and serology. Even if this belief could be explained by the experience of a COVID-19 infection–like episode among some of these participants, these results support the idea that persistent physical symptoms attributed to COVID-19 infection may not be specific to SARS-CoV-2. Second, patients who believe that they have had COVID-19 infection may reject a negative serology test result for several reasons, including perceptions about the frequency of false-negative tests and data suggesting that a weak anti–SARS-CoV-2 antibody response could be a risk factor of long COVID.17 Indeed, since the first definitions of long COVID, it has been proposed that the associated antibodies profile is “uncharacterized.”18 Among participants in the present study who believed that they had experienced COVID-19 infection, anosmia was the only symptom associated with the confirmation of the diagnosis by a laboratory test or a physician. In other words, those who responded, “No, but I think I had it” were 4 times less likely to have anosmia, with no differences regarding all other symptoms, further suggesting that these other symptoms were not specific to actual infection by SARS-CoV-2.

    Two main mechanisms may account for our findings. First, having persistent physical symptoms may have led to the belief in having had COVID-19, especially in the context of a growing concern regarding long COVID. Although adjusting for self-rated health before the pandemic did not affect our results, another disease may underlie symptoms attributed to COVID-19 infection. Second, the belief in having had COVID-19 infection may have increased the likelihood of symptoms, either directly by affecting perception19,20 or indirectly by prompting maladaptive health behaviors, such as physical activity reduction or dietary exclusion. These mechanisms are thought to contribute to the long-described persistence of physical symptoms after acute infections.21

    Strengths and Limitations

    In addition to a large, population-based sample, the strengths of our study included the joint examination of self-reported COVID-19 infection and serology testing results while controlling for several covariates, including self-rated health—a robust indicator of physical health—and depressive symptoms.

    This study had limitations. Quiz Ref IDFirst, selection biases limit the representativeness of our sample. Second, our study may not have investigated all of the symptoms that patients with long COVID are reporting. However, the symptoms we studied were among those that are frequently explored in studies investigating long COVID3 and reported by patients with long COVID.22 Third, we analyzed persistent symptoms separately; different outcomes may be tested by clustering symptoms. In addition, because our study also included participants who did not report having had COVID-19 infection, we did not distinguish between symptoms that were experienced at the time of the initial episode of COVID-19 infection and new symptoms that occurred afterward. Fourth, we cannot exclude the possibility of misclassification regarding serology test results. On the basis of the present results, we estimate the prevalence of previous SARS-CoV-2 infection to be about 4%, and with a sensitivity of 87%, we would expect 139 participants to have false-negative results, which is less than 1% of those with negative serology test results. False-negative results were thus unlikely to have much influence on the associations between persistent symptoms and serology. In addition, the lack of any interaction between belief and serology test results suggests that persistent symptoms were associated with belief to a similar extent in participants with positive and negative serology test results. This finding makes our results unlikely to be explained solely by false-negative results. Furthermore, serology test results were associated only with persistent anosmia, a hallmark of COVID-19 infection, strengthening our confidence in the serology test results. This result held true even when restricting our analyses to participants attributing their symptoms to COVID-19 infection. Fifth, participants were aware of their serology test results when they reported having had COVID-19 infection or not. This factor may have reduced our ability to disentangle the associations of the 2 measures with persistent physical symptoms.

    Conclusions

    The results of this cross-sectional analysis of a large, population-based French cohort suggest that physical symptoms persisting 10 to 12 months after the COVID-19 pandemic first wave may be associated more with the belief in having experienced COVID-19 infection than with actually being infected with the SARS-CoV-2 virus. Although our study cannot determine the direction of the association between belief and symptoms, our results suggest that further research regarding persistent physical symptoms after COVID-19 infection should also consider mechanisms that may not be specific to the SARS-CoV-2 virus. From a clinical perspective, patients in this situation should be offered a medical evaluation to prevent their symptoms being erroneously attributed to COVID-19 infection and to identify cognitive and behavioral mechanisms that may be targeted to relieve the symptoms.23

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    Article Information

    Accepted for Publication: September 17, 2021.

    Published Online: November 8, 2021. doi:10.1001/jamainternmed.2021.6454

    Corresponding Author: Cédric Lemogne, MD, PhD, Service de Psychiatrie de l’adulte, Hôpital Hôtel-Dieu, 1 place du Parvis Notre-Dame, 75004 Paris, France (cedric.lemogne@aphp.fr).

    Author Contributions: Drs Matta and Lemogne had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

    Acquisition, analysis, or interpretation of data: Matta, Wiernik, Robineau, Carrat, Touvier, de Lamballerie, Blanché, Deleuze, Hoertel, Ranque, Goldberg, Lemogne.

    Drafting of the manuscript: Matta, Lemogne.

    Critical revision of the manuscript for important intellectual content: Matta, Wiernik, Robineau, Carrat, Touvier, Severi, de Lamballerie, Blanché, Deleuze, Gouraud, Hoertel, Ranque, Goldberg, Zins.

    Statistical analysis: Matta, Robineau, Hoertel.

    Obtained funding: Blanché, Zins.

    Administrative, technical, or material support: Blanché, Deleuze, Gouraud, Goldberg, Zins.

    Supervision: Carrat, Touvier, Blanché, Gouraud, Goldberg, Lemogne.

    Conflict of Interest Disclosures: Dr Robineau reported personal fees and nonfinancial support from Gilead, ViiV Healthcare, and Merck Sharp & Dohme Corp outside the submitted work. Dr Carrat reported personal fees from Sanofi outside the submitted work. Dr de Lamballerie reported grants from the French Ministry of Research and the French Institute of Health and Medical Research during the conduct of the study. Dr Hoertel reported personal fees and nonfinancial support from Lundbeck outside the submitted work. Dr Lemogne reported personal fees from Boehringer Ingelheim, Janssen-Cilag, Lundbeck, and Otsuka Pharmaceutical outside the submitted work. No other disclosures were reported.

    Funding/Support: The CONSTANCES cohort benefits from grant ANR-11-INBS-0002 from the French National Research Agency. CONSTANCES is supported by the Caisse Nationale d’Assurance Maladie, the French Ministry of Health, the Ministry of Research, and the Institut National de la Santé et de la Recherche Médicale (INSERM). CONSTANCES is also partly funded by AstraZeneca, Lundbeck, L’Oréal, and Merck Sharp & Dohme Corp. The Santé, Pratiques, Relations et Inégalités Socials en Population Générale Pendant la Crise COVID-19 (SAPRIS) and SAPRIS-Sérologie (SERO) study was supported by grants ANR-10-COHO-06 and ANR-20-COVI-000 from the Agence Nationale de la Recherche; grant 20DMIA014-0 from Santé Publique France; grant 20RR052-00 from the Fondation pour la Recherche Médicale; and grant C20-26 from INSERM.

    Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

    Group Information: A complete list of the members of the SAPRIS-SERO study group appears in Supplement 2.

    Additional Contributions: Céline Ribet, PhD, Mireille Pellicer, MD, Laura Quintin, MSc, Stephane Le Got, MSc, all from the CONSTANCES cohort, and Céline Dorival, PhD, and Jerôme Nicol, MSc, from INSERM Institut Pierre Louis d’Epidémiologie et de Santé Publique, substantially contributed to data collection for this work.

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