Impact of Long-COVID on Health-related Quality of Life in Japanese COVID-19 Patients

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We aimed to assess the disease burden caused by long-COVID in Japan. Methods: We conducted a cross sectional self-report questionnaire survey. The questionnaire was mailed to 530 eligible patients, who were recovered from acute COVID-19 in April 2021. Answers were classified into two groups; participants who have no symptom and those who have any ongoing symptoms that lasted longer than four weeks at the time of the survey. We compared health-related quality of life scores estimated by the EQ-5D-3L questionnaire between these two groups after adjusting basic characteristics of the participants by propensity score matching. Results: 349 participants reported no symptoms and 108 reported any symptoms at the time of the survey. The participants who reported any symptoms showed a lower value on a Visual Analogue Scale (median 70 [IQR 60-80]) and on the EQ-5D-3L (median 0.81 [IQR 0.77-1.0]) than those reporting no symptoms (median 85 [IQR 75-90] and 1.0 [IQR 1.0-1.0], respectively). After adjusting for background characteristics, these trends did not change substantially (Visual Analog Scale: median 70 [IQR 60-80] vs 80 [IQR 77-90], EQ-5D-3L: median 0.81 [IQR 0.76-1.0] vs 1.0 [IQR 1.0-1.0]). Conclusions: Due to their long duration, long-COVID symptoms represent a substantial disease burden expressed in impact on health-related quality of life. Trial registration: Not applicable. Health Economics & Outcomes Research COVID-19 disease burden Quality of life long-COVID Figures Figure 1 Figure 2 Background Coronavirus disease 2019 (COVID-19) caused by the SARS-CoV-2 virus, has become a global health threat [ 1 ]. Not only its acute phase of disease, but so-called “long-COVID” is also a cause of substantial disease burden [ 2 , 3 ]. A systematic review reported that 80% of patients developed one or more long-term symptoms and the prevalence of 55 long-term effects of COVID-19 [ 4 ]. There is no clear definition of long-COVID so far, however, the National Institute for Health and Care Excellence (NICE) in The UK defined it as “signs and symptoms that develop during or following an infection consistent with covid-19 and which continue for more than four weeks and are not explained by an alternative diagnosis” [ 5 ]. This term includes ongoing symptomatic COVID-19, from four to 12 weeks post-infection, and post-COVID-19 syndrome, beyond 12 weeks post-infection [ 6 ]. The symptoms of long-COVID are various and often different from the acute phase of COVID-19. Miyazato and colleagues reported that the mean time from COVID-19 symptom onset to the emergence of alopecia was 58.6 days and one of patients presented dysosmia after 92 days after symptom onset [ 7 ]. Other symptoms such as general fatigue [ 8 , 9 ], respiratory symptoms [ 10 , 11 ], cognitive and mental health disorder [ 12 , 13 ], and so forth [ 14 , 15 ] have been reported as long-COVID. Considering its chronic phase, the disease burden of COVID-19 should be larger than that of other respiratory infections due to length and variety of the symptoms. However, the empirical basis for a quantitative assessment of the disease burden imposed by long-COVID is currently scant. An important element towards disease burden assessment is health-related quality of life impact. The objective of the present study is to collect and analyse empirical information on the health-related quality of life (HRQoL) due to long-COVID. Methods Settings We conducted a survey in which a self-report questionnaire was mailed to eligible patients who had recovered from COVID-19 in April 2021 with two reminders 2 weeks and 1 month later. Potential participants were recruited from patients who had recovered from COVID-19 and visited the outpatient service of the Disease Control and Prevention Center (DCC) in the NCGM in order to obtain pre-donation screening test for COVID-19 convalescent plasmapheresis (Another study named “Collection and antibody measurement of Convalescent plasma foreseeing the use for COVID-19 treatment”). 530 patients who had recovered from COVID-19 (70 out of 448 needs supplementary oxygen support) and visited the outpatient service of the Disease Control and Prevention Center (DCC) in National Center for Global Health and Medicine (NCGM), Tokyo, Japan from 1st February 2020 to 31st March 2021. Participation in the survey was voluntary and not anonymous. Participants were requested to complete and return the questionnaire. 457 of 530 (86.2%) patients completely answered the questionnaire and were included in the analysis. Statistical analysis Answers were classified into two groups; participants who have no symptom and those who have any ongoing symptoms that lasted longer than four weeks at the time of the survey. We compared visual analogue scale (VAS) and HRQoL values estimated by the EQ-5D-3L questionnaire [ 16 ] by Japanese value set [ 17 ] between two groups using Mann-Whitney U test, after adjusting basic characteristics of the participants by one-to-one propensity score matching (nearest neighbour pair matching, caliper = 0.2) calculated by multivariate logistic regression model predicting the likelihood of having ongoing symptoms [ 18 , 19 ]. We included age, sex, BMI, smoking, drinking, hypertension, diabetes, chronic obstructive lung diseases, malignancy, use of antivirals, use of systemic steroids, and severe COVID-19 disease during admission (use of mechanical ventilation or extracorporeal membrane oxygenation during admission, according to the definition by a report of national registry data in Japan [ 20 ]). The standardized mean difference was used to measure covariate balance, and an absolute standardized difference above 20% was interpreted as a meaningful imbalance. Two-sided p values of <0.05 were considered to show statistical significance. All analyses were conducted by R, version 4.0.5 [ 21 ]. Ethics approval According to local ethical guidelines, responses to questionnaire were regarded as patient consent. This study was reviewed and approved by the Ethics Committee of the Center Hospital of the NCGM (NCGM-G-004121-00). Results Table 1 shows the basic characteristics of the participants. 457 patients recovered from acute phase of COVID-19 and 108 of them presented at least one symptom. The proportion of female was larger in “Any symptom” group than that in “No symptom” group. There was no substantial difference between the two groups in terms of their age and medical history. Crude comparison of VAS and QOL showed that “Any symptom” group had lower VAS and QOL values than the “No symptom” group did (VAS: 70 vs 85, QOL: 0.81 vs 1.0, respectively). Table 1 Characteristics of participants No symptom Any symptom P value* SMD Number 349 108 Age 48 [39-55] 47 [40-54] 0.724 0.001 Male 188 (53.9) 38 (35.2) 0.001 < 0.383 BMI 23.2 [21.1-25.6] 23.4 [20.9-26.9] 0.453 0.163 Smoking 130 (37.2) 38 (35.5) 0.819 0.036 Drinking 290 (83.1) 86 (79.6) 0.471 0.089 Hypertension 52 (14.9) 14 (13.0) 0.754 0.056 Diabetes 23 (6.6) 5 (4.6) 0.646 0.085 COPD 3 (0.9) 0 (0.0) 1.0 < 0.132 Malignancy 6 (1.7) 0 (0.0) 0.343 0.187 Use of antivirals 62 (18.8) 22 (20.8) 0.672 0.049 Use of steroids 40 (12.8) 13 (13.3) 0.865 0.013 Severe disease † 7 (2.1) 6 (5.6) 0.092 0.183 Oxygen support 44 (12.6) 13 (13.3) 0.870 0.027 VAS 85 [75-90] 70 [60-80] < 0.001 0.810 QOL 1.0 [1.0-1.0] 0.81 [0.77-1.0] < 0.001 0.845 Median [interquartile range] for continuous variables, number (%) for categorical variables. *Mann-Whitney U test for continuous variables, Fisher's exact test for categorical variables. † Use of mechanical ventilation or extracorporeal membrane oxygenation during admission. SMD: standardized mean difference, BMI: Body Mass Index, COPD: chronic obstructive pulmonary disease, VAS: Visual Analogue Scale, QOL: Quality of Life Table 2 describes the characteristics of the data after propensity score matching. 91 pairs included in the matched data and 17 of “Any symptom” group were discarded. Adjusted comparison of VAS and QOL showed a similar trend to the results of crude comparison. Both VAS and QOL were lower in the “Any symptom” group (VAS: 70 vs 80, QOL: 0.81 vs 1.0, respectively). Table 2 Characteristics of participants after propensity score matching No symptom Any symptom P value* SMD Number 91 91 Age 46 [39-52] 46 [39-54] 0.515 0.123 Male 29 (31.9) 29 (31.9) 1.0 < 0.001 BMI 22.7 [20.8-26.8] 23.4 [20.9-26.5] 0.801 0.051 Smoking 30 (33.0) 30 (33.0) 1.0 < 0.001 Drinking 68 (74.7) 74 (81.3) 0.371 0.160 Hypertension 7 (7.7) 10 (11.0) 0.612 0.113 Diabetes 5 (5.5) 5 (5.5) 1.0 < 0.001 COPD 0 (0.0) 0 (0.0) NA < 0.001 Malignancy 0 (0.0) 0 (0.0) NA < 0.001 Use of antivirals 16 (17.6) 16 (17.6) 1.0 0.063 Use of steroids 14 (15.4) 12 (13.2) 0.833 < 0.001 Severe disease † 3 (3.3) 3 (3.3) 1.0 < 0.001 VAS 80 [77-90] 70 [60-80] < 0.001 0.763 QOL 1.0 [1.0-1.0] 0.81 [0.76-1.0] < 0.001 0.80 Median [interquartile range] for continuous variables, number (%) for categorical variables. *Mann-Whitney U test for continuous variables, Fisher's exact test for categorical variables. † Use of mechanical ventilation or extracorporeal membrane oxygenation during admission. SMD: standardized mean difference, BMI: Body Mass Index, COPD: chronic obstructive pulmonary disease, VAS: Visual Analogue Scale, QOL: Quality of Life Table 3 describes the characteristics of “long-COVID” symptoms. We defined “long-COVID” as the status in which any symptoms attributed to SARS-nCoV-2 infection lasting more than four weeks in the present study. 201 of 457 (44.0%) participants reported at least one symptom after four weeks have passed since their symptom onset due to COVID-19. The most common symptom of long-COVID was general fatigue. 58 of 457 (12.7%) participants have had general fatigue longer than four weeks. The second most common symptom was alopecia. 55 of 457 (12.0%) participants have experienced hair loss worse than usual. Table 3 Details of symptoms lasted longer than four weeks in the participants Number Duration (days) Number of symptoms 457 At least 1 201 (44.0) 1 73 (16.0) 2 46 (10.1) 3 47 (10.3) 4 and more 34 (7.4) Fatigue 58 (12.7) 50 [30-60] Hair loss 55 (12.0) 60 [30-90] Cough 54 (11.8) 40 [30-60] Dysosmia 47 (10.3) 45 [30-60] Dysgeusia 47 (10.3) 35 [30-60] Shortness of breath 36 (7.9) 42.5 [30-60] Loss of concentration 34 (7.4) 40 [30-90] Depression 29 (6.3) 40 [30-60] Absolute number (%) for the number of participants, median [interquartile range] for the duration of symptoms. Figure 1 and 2 show a violin plot of VAS and QOL value, respectively. The “Any symptom” group showed greater variance in both indicators. Discussion The present study demonstrated that the phenomenon we called “long-COVID” can impair the HRQOL substantially. This would be another important aspect of COVID-19 to consider because it implies a heavier disease burden to us than other influenza like illnesses (ILIs) do, not only due to its severity but also the characteristics of its chronic phase. In the first place, COVID-19 showed higher case-fatality than other ILIs [ 22 – 24 ]. Additionally, it might cause a substantial burden through accumulated mild disease only. Furthermore, the frequency and the duration of symptoms due to “long-COVID” are also noteworthy. Our results showed that nearly half of the patients who recovered from acute COVID-19 (201/457) experienced any symptoms lasting more than four weeks. As for patients who required supplementary oxygen support, 32 out of 70 (45.7%) presented any symptoms longer than four weeks. The precise duration of such symptoms was not obvious because more than 100 participants reported that their symptoms were still ongoing, nevertheless, we can say that the symptoms attributed to “long-COVID” often continue several months. Albeit the HRQOL value of the participants who have any “long-COVID” symptoms was higher than that of the acute phase of other ILIs reported by a previous study in Japan (0.81 vs 0.66, respectively) [ 25 ], QOL lost attributed to “long-COVID” should be greater than that due to the acute phase of other ILIs because of its duration. These results suggest that prevention is more important in COVID-19 countermeasures than other ILIs because effective treatment of “long-COVID” is not clearly established yet [ 6 , 26 ]. Although there is no doubt that vaccination against SARS-CoV-2 will reduce the risk of fatal and severe COVID-19 [ 27 – 29 ], its effectiveness against “long-COVID” is not demonstrated yet. This may provide an additional incentive to prevent SARS-CoV-2 infection even in the absence of known risk factors of severe illness. There are several limitations in our study. First, our results are based on the questionnaire survey then there are some recall biases in participants’ responses. Similarly, the potential participants were enrolled from the visitors of outpatient department at the national center hospital of infectious diseases in Japan, then the study population might be influenced by selection biases. In addition, we could not take “new variants” into consideration. The difference in severity, infectiousness, and so forth between such new variants and old ones were already reported [ 30 – 32 ], however, there is no solid evidence about the frequency and the severity of “long-COVID” symptoms in new variants. This should be the subject of future study. In addition, we should be careful about the representativeness of the data when we interpret the results because our survey includes a comparatively small number of participants from Japan. However, the response rate of our survey was extremely high (86.2%), and non-response bias may therefore be limited. Furthermore, we compared VAS and EQ-5D-3L values after adjusting participants’ background by propensity score matching. Conclusions What we call “long-COVID” brings us substantial disease burden in addition to the burden attributed to the acute phase of COVID-19. This additional burden makes the whole disease burden of COVID-19 heavier, making prevention strategies all the more important. The influence of vaccination and variants on “long-COVID” should be examined in the near future. Declarations Ethics approval This study was reviewed and approved by the Ethics Committee of the Center Hospital of the NCGM (NCGM-G-004121-00) Consent for publication According to local ethical guidelines, responses to questionnaire were regarded as patient consent. Availability of data and materials The data that support the findings of this study are available upon request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions. Competing interests PB reports grants from the EU's SC1-PHE-CORONAVIRUS-2020 programme, Pfizer, GlaxoSmithKlein, and European Commission IMI, unrelated to this work. Funding This research was funded by JSPS KAKENHI [Grant number 18K17369], a grant for the National Center for Global Health and Medicine [20A05], AMED under Grant Number JP20fk0108502 and the Health and Labour Sciences Research Grant, “Research for risk assessment and implementation of crisis management functions for emerging and re-emerging infectious diseases.” Authors’ contributions Shinya Tsuzuki: Conceptualization, Funding Acquisition, Data Curation, Formal Analysis, Methodology, Visualization, Original Draft Preparation. Yusuke Miyazato: Data Curation, Review and Editing. Mari Terada: Data Curation, Review and Editing. Shinichiro Morioka: Data Curation, Project Administration, Review and Editing. Norio Ohmagari: Conceptualization, Funding Acquisition, Project Administration, Review and Editing. Philippe Beutels: Supervision, Project Administration, Review & Editing. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-948458","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research","associatedPublications":[],"authors":[{"id":55987215,"identity":"0a03d0c8-79a0-48b7-a8d8-f65df236b843","order_by":0,"name":"Shinya 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Center","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Shinichiro","middleName":"","lastName":"Morioka","suffix":""},{"id":55987219,"identity":"11998f3a-ac6c-498a-9303-3bb37d23a04d","order_by":4,"name":"Norio Ohmagari","email":"","orcid":"","institution":"National Center for Global Health and Medicine: Kokuritsu Kenkyu Kaihatsu Hojin Kokuritsu Kokusai Iryo Kenkyu Center","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Norio","middleName":"","lastName":"Ohmagari","suffix":""},{"id":55987220,"identity":"c2eed89f-c50b-400b-80e8-cdd034ae17fb","order_by":5,"name":"Philippe Beutels","email":"","orcid":"","institution":"University of Antwerp Drie Eiken Campus: Universiteit Antwerpen Campus Drie Eiken","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Philippe","middleName":"","lastName":"Beutels","suffix":""}],"badges":[],"createdAt":"2021-09-29 11:07:39","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-948458/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-948458/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":14413535,"identity":"77afc230-847d-4370-a834-52649f7a3d2c","added_by":"auto","created_at":"2021-10-11 15:23:01","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":18990,"visible":true,"origin":"","legend":"Violin plot of visual analogue scale \nRed colour represents “No symptom” group and blue colour represents “With symptom” group.","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-948458/v1/c0fc75cd9e6f629699c3d510.png"},{"id":14413166,"identity":"fc077172-d183-4b4c-bc55-d8d65e8ae0d4","added_by":"auto","created_at":"2021-10-11 15:20:01","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":17409,"visible":true,"origin":"","legend":"Violin plot of Quality of Life\nRed colour represents “No symptom” group and blue colour represents “With symptom” group.","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-948458/v1/7148da7302a7eefe20c89737.png"},{"id":14413536,"identity":"735bea6e-4faa-47b2-9970-5b46923fb32d","added_by":"auto","created_at":"2021-10-11 15:23:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":414489,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-948458/v1/b597a4a5-9087-4eb8-98e8-8c49a1b21693.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003eImpact of Long-COVID on Health-related Quality of Life in Japanese COVID-19 Patients\u003c/p\u003e","fulltext":[{"header":"Background","content":"\u003cp\u003eCoronavirus disease 2019 (COVID-19) caused by the SARS-CoV-2 virus, has become a global health threat [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Not only its acute phase of disease, but so-called \u0026ldquo;long-COVID\u0026rdquo; is also a cause of substantial disease burden [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. A systematic review reported that 80% of patients developed one or more long-term symptoms and the prevalence of 55 long-term effects of COVID-19 [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThere is no clear definition of long-COVID so far, however, the National Institute for Health and Care Excellence (NICE) in The UK defined it as \u0026ldquo;signs and symptoms that develop during or following an infection consistent with covid-19 and which continue for more than four weeks and are not explained by an alternative diagnosis\u0026rdquo; [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. This term includes ongoing symptomatic COVID-19, from four to 12 weeks post-infection, and post-COVID-19 syndrome, beyond 12 weeks post-infection [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe symptoms of long-COVID are various and often different from the acute phase of COVID-19. Miyazato and colleagues reported that the mean time from COVID-19 symptom onset to the emergence of alopecia was 58.6 days and one of patients presented dysosmia after 92 days after symptom onset [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Other symptoms such as general fatigue [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], respiratory symptoms [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], cognitive and mental health disorder [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], and so forth [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] have been reported as long-COVID.\u003c/p\u003e \u003cp\u003eConsidering its chronic phase, the disease burden of COVID-19 should be larger than that of other respiratory infections due to length and variety of the symptoms. However, the empirical basis for a quantitative assessment of the disease burden imposed by long-COVID is currently scant. An important element towards disease burden assessment is health-related quality of life impact. The objective of the present study is to collect and analyse empirical information on the health-related quality of life (HRQoL) due to long-COVID.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv class=\"Section2\" id=\"Sec3\"\u003e\n \u003ch2\u003eSettings\u003c/h2\u003e\n \u003cp\u003eWe conducted a survey in which a self-report questionnaire was mailed to eligible patients who had recovered from COVID-19 in April 2021 with two reminders 2 weeks and 1 month later. Potential participants were recruited from patients who had recovered from COVID-19 and visited the outpatient service of the Disease Control and Prevention Center (DCC) in the NCGM in order to obtain pre-donation screening test for COVID-19 convalescent plasmapheresis (Another study named \u0026ldquo;Collection and antibody measurement of Convalescent plasma foreseeing the use for COVID-19 treatment\u0026rdquo;). 530 patients who had recovered from COVID-19 (70 out of 448 needs supplementary oxygen support) and visited the outpatient service of the Disease Control and Prevention Center (DCC) in National Center for Global Health and Medicine (NCGM), Tokyo, Japan from 1st February 2020 to 31st March 2021. Participation in the survey was voluntary and not anonymous. Participants were requested to complete and return the questionnaire. 457 of 530 (86.2%) patients completely answered the questionnaire and were included in the analysis.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec4\"\u003e\n \u003ch2\u003eStatistical analysis\u003c/h2\u003e\n \u003cp\u003eAnswers were classified into two groups; participants who have no symptom and those who have any ongoing symptoms that lasted longer than four weeks at the time of the survey. We compared visual analogue scale (VAS) and HRQoL values estimated by the EQ-5D-3L questionnaire [\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e] by Japanese value set [\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e] between two groups using Mann-Whitney U test, after adjusting basic characteristics of the participants by one-to-one propensity score matching (nearest neighbour pair matching, caliper = 0.2) calculated by multivariate logistic regression model predicting the likelihood of having ongoing symptoms [\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e]. We included age, sex, BMI, smoking, drinking, hypertension, diabetes, chronic obstructive lung diseases, malignancy, use of antivirals, use of systemic steroids, and severe COVID-19 disease during admission (use of mechanical ventilation or extracorporeal membrane oxygenation during admission, according to the definition by a report of national registry data in Japan [\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e]). The standardized mean difference was used to measure covariate balance, and an absolute standardized difference above 20% was interpreted as a meaningful imbalance. Two-sided p values of \u0026lt;0.05 were considered to show statistical significance. All analyses were conducted by R, version 4.0.5 [\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e\n\u003c/div\u003e\n\u003ch2\u003eEthics approval\u003c/h2\u003e\n\u003cp\u003eAccording to local ethical guidelines, responses to questionnaire were regarded as patient consent. This study was reviewed and approved by the Ethics Committee of the Center Hospital of the NCGM (NCGM-G-004121-00).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eTable \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e shows the basic characteristics of the participants. 457 patients recovered from acute phase of COVID-19 and 108 of them presented at least one symptom. The proportion of female was larger in \u0026ldquo;Any symptom\u0026rdquo; group than that in \u0026ldquo;No symptom\u0026rdquo; group. There was no substantial difference between the two groups in terms of their age and medical history. Crude comparison of VAS and QOL showed that \u0026ldquo;Any symptom\u0026rdquo; group had lower VAS and QOL values than the \u0026ldquo;No symptom\u0026rdquo; group did (VAS: 70 vs 85, QOL: 0.81 vs 1.0, respectively).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable border=\"1\" id=\"Tab1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCharacteristics of participants\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNo symptom\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAny symptom\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value*\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSMD\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e349\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48 [39-55]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47 [40-54]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.724\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e188 (53.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38 (35.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt; 0.383\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23.2 [21.1-25.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23.4 [20.9-26.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.453\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.163\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e130 (37.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38 (35.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.819\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDrinking\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e290 (83.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e86 (79.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.471\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.089\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHypertension\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52 (14.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14 (13.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.754\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.056\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiabetes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23 (6.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (4.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.646\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.085\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCOPD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt; 0.132\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMalignancy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.343\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.187\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eUse of antivirals\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62 (18.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22 (20.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.672\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.049\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eUse of steroids\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40 (12.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13 (13.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.865\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSevere disease\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e\u0026dagger;\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (2.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (5.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.092\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.183\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eOxygen support\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44 (12.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13 (13.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.870\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eVAS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e85 [75-90]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70 [60-80]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.810\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eQOL\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.0 [1.0-1.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.81 [0.77-1.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.845\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eMedian [interquartile range] for continuous variables, number (%) for categorical variables.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003e*Mann-Whitney U test for continuous variables, Fisher\u0026apos;s exact test for categorical variables.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003eUse of mechanical ventilation or extracorporeal membrane oxygenation during admission.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eSMD: standardized mean difference, BMI: Body Mass Index, COPD: chronic obstructive pulmonary disease, VAS: Visual Analogue Scale, QOL: Quality of Life\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e describes the characteristics of the data after propensity score matching. 91 pairs included in the matched data and 17 of \u0026ldquo;Any symptom\u0026rdquo; group were discarded. Adjusted comparison of VAS and QOL showed a similar trend to the results of crude comparison. Both VAS and QOL were lower in the \u0026ldquo;Any symptom\u0026rdquo; group (VAS: 70 vs 80, QOL: 0.81 vs 1.0, respectively).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable border=\"1\" id=\"Tab2\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCharacteristics of participants after propensity score matching\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNo symptom\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAny symptom\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value*\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSMD\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46 [39-52]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46 [39-54]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.515\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.123\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29 (31.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29 (31.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22.7 [20.8-26.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23.4 [20.9-26.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.801\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.051\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30 (33.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30 (33.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDrinking\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e68 (74.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e74 (81.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.371\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.160\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHypertension\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (7.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (11.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.612\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.113\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiabetes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (5.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (5.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCOPD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMalignancy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eUse of antivirals\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16 (17.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16 (17.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.063\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eUse of steroids\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14 (15.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12 (13.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.833\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSevere disease\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e\u0026dagger;\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (3.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (3.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eVAS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e80 [77-90]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70 [60-80]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.763\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eQOL\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.0 [1.0-1.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.81 [0.76-1.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.80\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eMedian [interquartile range] for continuous variables, number (%) for categorical variables.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003e*Mann-Whitney U test for continuous variables, Fisher\u0026apos;s exact test for categorical variables.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003eUse of mechanical ventilation or extracorporeal membrane oxygenation during admission.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eSMD: standardized mean difference, BMI: Body Mass Index, COPD: chronic obstructive pulmonary disease, VAS: Visual Analogue Scale, QOL: Quality of Life\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e describes the characteristics of \u0026ldquo;long-COVID\u0026rdquo; symptoms. We defined \u0026ldquo;long-COVID\u0026rdquo; as the status in which any symptoms attributed to SARS-nCoV-2 infection lasting more than four weeks in the present study. 201 of 457 (44.0%) participants reported at least one symptom after four weeks have passed since their symptom onset due to COVID-19. The most common symptom of long-COVID was general fatigue. 58 of 457 (12.7%) participants have had general fatigue longer than four weeks. The second most common symptom was alopecia. 55 of 457 (12.0%) participants have experienced hair loss worse than usual.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable border=\"1\" id=\"Tab3\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDetails of symptoms lasted longer than four weeks in the participants\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNumber\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDuration (days)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of symptoms\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e457\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAt least 1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e201 (44.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e73 (16.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46 (10.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47 (10.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e4 and more\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34 (7.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFatigue\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58 (12.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e50 [30-60]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHair loss\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e55 (12.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e60 [30-90]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCough\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54 (11.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e40 [30-60]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDysosmia\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47 (10.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e45 [30-60]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDysgeusia\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47 (10.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e35 [30-60]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eShortness of breath\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36 (7.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e42.5 [30-60]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eLoss of concentration\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34 (7.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e40 [30-90]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDepression\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29 (6.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e40 [30-60]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\"\u003eAbsolute number (%) for the number of participants, median [interquartile range] for the duration of symptoms.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e show a violin plot of VAS and QOL value, respectively. The \u0026ldquo;Any symptom\u0026rdquo; group showed greater variance in both indicators.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present study demonstrated that the phenomenon we called \u0026ldquo;long-COVID\u0026rdquo; can impair the HRQOL substantially. This would be another important aspect of COVID-19 to consider because it implies a heavier disease burden to us than other influenza like illnesses (ILIs) do, not only due to its severity but also the characteristics of its chronic phase. In the first place, COVID-19 showed higher case-fatality than other ILIs [\u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Additionally, it might cause a substantial burden through accumulated mild disease only.\u003c/p\u003e \u003cp\u003eFurthermore, the frequency and the duration of symptoms due to \u0026ldquo;long-COVID\u0026rdquo; are also noteworthy. Our results showed that nearly half of the patients who recovered from acute COVID-19 (201/457) experienced any symptoms lasting more than four weeks. As for patients who required supplementary oxygen support, 32 out of 70 (45.7%) presented any symptoms longer than four weeks. The precise duration of such symptoms was not obvious because more than 100 participants reported that their symptoms were still ongoing, nevertheless, we can say that the symptoms attributed to \u0026ldquo;long-COVID\u0026rdquo; often continue several months. Albeit the HRQOL value of the participants who have any \u0026ldquo;long-COVID\u0026rdquo; symptoms was higher than that of the acute phase of other ILIs reported by a previous study in Japan (0.81 vs 0.66, respectively) [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], QOL lost attributed to \u0026ldquo;long-COVID\u0026rdquo; should be greater than that due to the acute phase of other ILIs because of its duration.\u003c/p\u003e \u003cp\u003eThese results suggest that prevention is more important in COVID-19 countermeasures than other ILIs because effective treatment of \u0026ldquo;long-COVID\u0026rdquo; is not clearly established yet [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Although there is no doubt that vaccination against SARS-CoV-2 will reduce the risk of fatal and severe COVID-19 [\u003cspan additionalcitationids=\"CR28\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], its effectiveness against \u0026ldquo;long-COVID\u0026rdquo; is not demonstrated yet. This may provide an additional incentive to prevent SARS-CoV-2 infection even in the absence of known risk factors of severe illness.\u003c/p\u003e \u003cp\u003eThere are several limitations in our study. First, our results are based on the questionnaire survey then there are some recall biases in participants\u0026rsquo; responses. Similarly, the potential participants were enrolled from the visitors of outpatient department at the national center hospital of infectious diseases in Japan, then the study population might be influenced by selection biases. In addition, we could not take \u0026ldquo;new variants\u0026rdquo; into consideration. The difference in severity, infectiousness, and so forth between such new variants and old ones were already reported [\u003cspan additionalcitationids=\"CR31\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], however, there is no solid evidence about the frequency and the severity of \u0026ldquo;long-COVID\u0026rdquo; symptoms in new variants. This should be the subject of future study.\u003c/p\u003e \u003cp\u003eIn addition, we should be careful about the representativeness of the data when we interpret the results because our survey includes a comparatively small number of participants from Japan. However, the response rate of our survey was extremely high (86.2%), and non-response bias may therefore be limited. Furthermore, we compared VAS and EQ-5D-3L values after adjusting participants\u0026rsquo; background by propensity score matching.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eWhat we call \u0026ldquo;long-COVID\u0026rdquo; brings us substantial disease burden in addition to the burden attributed to the acute phase of COVID-19. This additional burden makes the whole disease burden of COVID-19 heavier, making prevention strategies all the more important. The influence of vaccination and variants on \u0026ldquo;long-COVID\u0026rdquo; should be examined in the near future.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was reviewed and approved by the Ethics Committee of the Center Hospital of the NCGM (NCGM-G-004121-00)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAccording to local ethical guidelines, responses to questionnaire were regarded as patient consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available upon request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePB reports grants from the EU\u0026apos;s SC1-PHE-CORONAVIRUS-2020 programme, Pfizer, GlaxoSmithKlein, and European Commission IMI, unrelated to this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by JSPS KAKENHI [Grant number 18K17369], a grant for the National Center for Global Health and Medicine [20A05], AMED under Grant Number JP20fk0108502 and the Health and Labour Sciences Research Grant, \u0026ldquo;Research for risk assessment and implementation of crisis management functions for emerging and re-emerging infectious diseases.\u0026rdquo;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eShinya Tsuzuki: Conceptualization, Funding Acquisition, Data Curation, Formal Analysis, Methodology, Visualization, Original Draft Preparation. Yusuke Miyazato: Data Curation, Review and Editing. Mari Terada: Data Curation, Review and Editing. Shinichiro Morioka: Data Curation, Project Administration, Review and Editing. Norio Ohmagari: Conceptualization, Funding Acquisition, Project Administration, Review and Editing. Philippe Beutels: Supervision, Project Administration, Review \u0026amp; Editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank all the people who participated in our survey and study, \u0026ldquo;Collection and antibody measurement of Convalescent plasma foreseeing the use for COVID-19 treatment\u0026rdquo;.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eGuan W, Ni Z, Hu Y, Liang W, Ou C, He J, et al. Clinical Characteristics of Coronavirus Disease 2019 in China. N Engl J Med. 2020;382:1708\u0026ndash;20.\u003c/li\u003e\n \u003cli\u003edel Rio C, Collins LF, Malani P. Long-term Health Consequences of COVID-19. JAMA [Internet]. 2020 [cited 2020 Oct 6]; Available from: https://jamanetwork.com/journals/jama/fullarticle/2771581\u003c/li\u003e\n \u003cli\u003eUK guidelines for managing long-term effects of COVID-19 - The Lancet [Internet]. [cited 2021 May 17]. Available from: https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(21)00847-3/fulltext\u003c/li\u003e\n \u003cli\u003eLopez-Leon S, Wegman-Ostrosky T, Perelman C, Sepulveda R, Rebolledo PA, Cuapio A, et al. More than 50 long-term effects of COVID-19: a systematic review and meta-analysis. Sci Rep. 2021;11:16144.\u003c/li\u003e\n \u003cli\u003eSivan M, Taylor S. NICE guideline on long covid. BMJ. British Medical Journal Publishing Group; 2020;371:m4938.\u003c/li\u003e\n \u003cli\u003eCrook H, Raza S, Nowell J, Young M, Edison P. Long covid-mechanisms, risk factors, and management. BMJ. 2021;374:n1648.\u003c/li\u003e\n \u003cli\u003eMiyazato Y, Morioka S, Tsuzuki S, Akashi M, Osanai Y, Tanaka K, et al. Prolonged and Late-Onset Symptoms of Coronavirus Disease 2019. Open Forum Infect Dis. 2020;7:ofaa507.\u003c/li\u003e\n \u003cli\u003eMandal S, Barnett J, Brill SE, Brown JS, Denneny EK, Hare SS, et al. \u0026lsquo;Long-COVID\u0026rsquo;: a cross-sectional study of persisting symptoms, biomarker and imaging abnormalities following hospitalisation for COVID-19. Thorax. 2021;76:396\u0026ndash;8.\u003c/li\u003e\n \u003cli\u003eCarf\u0026igrave; A, Bernabei R, Landi F, Gemelli Against COVID-19 Post-Acute Care Study Group. Persistent Symptoms in Patients After Acute COVID-19. JAMA. 2020;324:603\u0026ndash;5.\u003c/li\u003e\n \u003cli\u003eGo\u0026euml;rtz YMJ, Herck MV, Delbressine JM, Vaes AW, Meys R, Machado FVC, et al. Persistent symptoms 3 months after a SARS-CoV-2 infection: the post-COVID-19 syndrome? ERJ Open Research [Internet]. European Respiratory Society; 2020 [cited 2021 Jul 31]; Available from: https://openres.ersjournals.com/content/early/2020/09/01/23120541.00542-2020\u003c/li\u003e\n \u003cli\u003eTenforde MW. Symptom Duration and Risk Factors for Delayed Return to Usual Health Among Outpatients with COVID-19 in a Multistate Health Care Systems Network \u0026mdash; United States, March\u0026ndash;June 2020. MMWR Morb Mortal Wkly Rep [Internet]. 2020 [cited 2021 Jul 31];69. Available from: https://www.cdc.gov/mmwr/volumes/69/wr/mm6930e1.htm\u003c/li\u003e\n \u003cli\u003eMazza MG, De Lorenzo R, Conte C, Poletti S, Vai B, Bollettini I, et al. Anxiety and depression in COVID-19 survivors: Role of inflammatory and clinical predictors. Brain, Behavior, and Immunity. 2020;89:594\u0026ndash;600.\u003c/li\u003e\n \u003cli\u003eHalpin SJ, McIvor C, Whyatt G, Adams A, Harvey O, McLean L, et al. Postdischarge symptoms and rehabilitation needs in survivors of COVID-19 infection: A cross-sectional evaluation. J Med Virol. 2021;93:1013\u0026ndash;22.\u003c/li\u003e\n \u003cli\u003eBoscolo-Rizzo P, Borsetto D, Fabbris C, Spinato G, Frezza D, Menegaldo A, et al. Evolution of Altered Sense of Smell or Taste in Patients With Mildly Symptomatic COVID-19. JAMA Otolaryngol Head Neck Surg. 2020;146:729.\u003c/li\u003e\n \u003cli\u003ePuntmann VO, Carerj ML, Wieters I, Fahim M, Arendt C, Hoffmann J, et al. Outcomes of Cardiovascular Magnetic Resonance Imaging in Patients Recently Recovered From Coronavirus Disease 2019 (COVID-19). JAMA Cardiol. 2020;5:1265.\u003c/li\u003e\n \u003cli\u003eRabin R, Gudex C, Selai C, Herdman M. From translation to version management: a history and review of methods for the cultural adaptation of the EuroQol five-dimensional questionnaire. Value Health. 2014;17:70\u0026ndash;6.\u003c/li\u003e\n \u003cli\u003eTsuchiya A, Ikeda S, Ikegami N, Nishimura S, Sakai I, Fukuda T, et al. Estimating an EQ-5D population value set: the case of Japan. Health Economics. 2002;11:341\u0026ndash;53.\u003c/li\u003e\n \u003cli\u003eRosenbaum PR, Rubin DB. The central role of the propensity score in observational studies for causal effects. :15.\u003c/li\u003e\n \u003cli\u003eDolan P. Modeling valuations for EuroQol health states. Med Care. 1997;35:1095\u0026ndash;108.\u003c/li\u003e\n \u003cli\u003eMatsunaga N, Hayakawa K, Terada M, Ohtsu H, Asai Y, Tsuzuki S, et al. Clinical epidemiology of hospitalized patients with COVID-19 in Japan: Report of the COVID-19 REGISTRY JAPAN. Clin Infect Dis. 2020;\u003c/li\u003e\n \u003cli\u003eR Core Team. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing; 2018.\u003c/li\u003e\n \u003cli\u003ePastor-Barriuso R, P\u0026eacute;rez-G\u0026oacute;mez B, Hern\u0026aacute;n MA, P\u0026eacute;rez-Olmeda M, Yotti R, Oteo-Iglesias J, et al. Infection fatality risk for SARS-CoV-2 in community dwelling population of Spain: nationwide seroepidemiological study. BMJ. 2020;371:m4509.\u003c/li\u003e\n \u003cli\u003ePoletti P, Tirani M, Cereda D, Trentini F, Guzzetta G, Marziano V, et al. Age-specific SARS-CoV-2 infection fatality ratio and associated risk factors, Italy, February to April 2020. Eurosurveillance. European Centre for Disease Prevention and Control; 2020;25:2001383.\u003c/li\u003e\n \u003cli\u003evan Asten L, Harmsen CN, Stoeldraijer L, Klinkenberg D, Teirlinck AC, de Lange MMA, et al. Excess Deaths during Influenza and Coronavirus Disease and Infection-Fatality Rate for Severe Acute Respiratory Syndrome Coronavirus 2, the Netherlands. Emerg Infect Dis. 2021;27:411\u0026ndash;20.\u003c/li\u003e\n \u003cli\u003eTsuzuki S, Yoshihara K. The characteristics of influenza-like illness management in Japan. BMC Public Health. 2020;20:568.\u003c/li\u003e\n \u003cli\u003eCarson G, Carson G, Sigfrid L, Olliaro P, Norton A, Paparella G, et al. Research priorities for Long Covid: refined through an international multi-stakeholder forum. BMC Medicine. 2021;19:84.\u003c/li\u003e\n \u003cli\u003eEscobar LE, Molina-Cruz A, Barillas-Mury C. BCG vaccine protection from severe coronavirus disease 2019 (COVID-19). PNAS. National Academy of Sciences; 2020;117:17720\u0026ndash;6.\u003c/li\u003e\n \u003cli\u003ePilishvili T. Interim Estimates of Vaccine Effectiveness of Pfizer-BioNTech and Moderna COVID-19 Vaccines Among Health Care Personnel \u0026mdash; 33 U.S. Sites, January\u0026ndash;March 2021. MMWR Morb Mortal Wkly Rep [Internet]. 2021 [cited 2021 Jun 21];70. Available from: https://www.cdc.gov/mmwr/volumes/70/wr/mm7020e2.htm\u003c/li\u003e\n \u003cli\u003ePolack FP, Thomas SJ, Kitchin N, Absalon J, Gurtman A, Lockhart S, et al. Safety and Efficacy of the BNT162b2 mRNA Covid-19 Vaccine. New England Journal of Medicine [Internet]. Massachusetts Medical Society; 2020 [cited 2021 Feb 6]; Available from: https://www.nejm.org/doi/10.1056/NEJMoa2034577\u003c/li\u003e\n \u003cli\u003eChallen R, Brooks-Pollock E, Read JM, Dyson L, Tsaneva-Atanasova K, Danon L. Risk of mortality in patients infected with SARS-CoV-2 variant of concern 202012/1: matched cohort study. BMJ. 2021;n579.\u003c/li\u003e\n \u003cli\u003eGrint DJ, Wing K, Williamson E, McDonald HI, Bhaskaran K, Evans D, et al. Case fatality risk of the SARS-CoV-2 variant of concern B.1.1.7 in England, 16 November to 5 February. Euro Surveill. 2021;26.\u003c/li\u003e\n \u003cli\u003ePatone M, Thomas K, Hatch R, Tan PS, Coupland C, Liao W, et al. Analysis of severe outcomes associated with the SARS-CoV-2 Variant of Concern 202012/01 in England using ICNARC Case Mix Programme and QResearch databases. medRxiv. Cold Spring Harbor Laboratory Press; 2021;2021.03.11.21253364.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"health-and-quality-of-life-outcomes","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"hqlo","sideBox":"Learn more about [Health and Quality of Life Outcomes](http://hqlo.biomedcentral.com)","snPcode":"12955","submissionUrl":"https://submission.nature.com/new-submission/12955/3","title":"Health and Quality of Life Outcomes","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"COVID-19, disease burden, Quality of life, long-COVID ","lastPublishedDoi":"10.21203/rs.3.rs-948458/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-948458/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e The empirical basis for a quantitative assessment of the disease burden imposed by long-COVID is currently scant. We aimed to assess the disease burden caused by long-COVID in Japan.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e We conducted a cross sectional self-report questionnaire survey. The questionnaire was mailed to 530 eligible patients, who were recovered from acute COVID-19 in April 2021. Answers were classified into two groups; participants who have no symptom and those who have any ongoing symptoms that lasted longer than four weeks at the time of the survey. We compared health-related quality of life scores estimated by the EQ-5D-3L questionnaire between these two groups after adjusting basic characteristics of the participants by propensity score matching.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e 349 participants reported no symptoms and 108 reported any symptoms at the time of the survey. The participants who reported any symptoms showed a lower value on a Visual Analogue Scale (median 70 [IQR 60-80]) and on the EQ-5D-3L (median 0.81 [IQR 0.77-1.0]) than those reporting no symptoms (median 85 [IQR 75-90] and 1.0 [IQR 1.0-1.0], respectively). After adjusting for background characteristics, these trends did not change substantially (Visual Analog Scale: median 70 [IQR 60-80] vs 80 [IQR 77-90], EQ-5D-3L: median 0.81 [IQR 0.76-1.0] vs 1.0 [IQR 1.0-1.0]).\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eDue to their long duration,\u003cstrong\u003e \u003c/strong\u003elong-COVID symptoms represent a substantial disease burden expressed in impact on health-related quality of life.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eTrial registration:\u003c/strong\u003e Not applicable.\u003c/p\u003e","manuscriptTitle":"Impact of Long-COVID on Health-related Quality of Life in Japanese COVID-19 Patients","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-10-11 15:19:59","doi":"10.21203/rs.3.rs-948458/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2021-11-01T00:00:00+00:00","index":3,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2021-10-27T10:01:36+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2021-10-27T07:03:28+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2021-10-27T01:00:00+00:00","index":2,"fulltext":""},{"type":"reviewerAgreed","content":"","date":"2021-10-27T00:00:00+00:00","index":1,"fulltext":""},{"type":"editorAssigned","content":"","date":"2021-09-29T00:00:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2021-09-28T23:00:00+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2021-09-28T23:00:00+00:00","index":"","fulltext":""},{"type":"submitted","content":"Health and Quality of Life Outcomes","date":"2021-09-28T08:10:04+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"health-and-quality-of-life-outcomes","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"hqlo","sideBox":"Learn more about [Health and Quality of Life Outcomes](http://hqlo.biomedcentral.com)","snPcode":"12955","submissionUrl":"https://submission.nature.com/new-submission/12955/3","title":"Health and Quality of Life Outcomes","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0c441f6c-d6d3-4cf0-a7ec-9672bfa9ab4f","owner":[],"postedDate":"October 11th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":7776352,"name":"Health Economics \u0026 Outcomes Research"}],"tags":[],"updatedAt":"2025-06-08T07:24:13+00:00","versionOfRecord":[],"versionCreatedAt":"2021-10-11 15:19:59","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-948458","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-948458","identity":"rs-948458","version":["v1"]},"buildId":"ApUGefWb6u5IBVtyqm6d5","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}