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      Prevalence and Predictors of COVID-19 Long-Term Symptoms: A Cohort Study from the Amazon Basin

      brief-report

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          ABSTRACT.

          It remains unclear whether a previous history of tropical infectious diseases and a second SARS-COV-2 infection may influence the likelihood of later symptoms. In this prospective cohort study, individuals infected with SARS-CoV-2 were followed up by telephone shortly after diagnosis of COVID-19 and again 12 months later. Poisson regression was used to identify the predictors of the highest number of symptoms in the post-COVID-19 syndrome. A total of 1,371 patients with COVID-19, with a mean age of 39.7 ± 11.7 years and 50% female, were followed for 12 months. Reinfection was found in 32 (2.3%) participants, and 806 (58.8%) individuals reported a previous history of dengue, malaria, Zika, chikungunya, leprosy, and visceral leishmaniasis. Eight hundred seventy-seven (63.9%) participants reported late symptoms related to COVID-19. After adjusting for multiple factors, female sex, non-White race, number of acute-phase symptoms, body mass index, and reinfection were independent predictors of higher number of symptoms in post-COVID-19 syndrome. Female sex, non-White race, number of acute-phase symptoms, body mass index, and reinfection, but not previous endemic tropical diseases, were associated with long-term symptoms.

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          Attributes and predictors of long COVID

          Carole H. Sudre, Benjamin Murray, Thomas Varsavsky … (2021)
          Reports of long-lasting coronavirus disease 2019 (COVID-19) symptoms, the so-called 'long COVID', are rising but little is known about prevalence, risk factors or whether it is possible to predict a protracted course early in the disease. We analyzed data from 4,182 incident cases of COVID-19 in which individuals self-reported their symptoms prospectively in the COVID Symptom Study app1. A total of 558 (13.3%) participants reported symptoms lasting ≥28 days, 189 (4.5%) for ≥8 weeks and 95 (2.3%) for ≥12 weeks. Long COVID was characterized by symptoms of fatigue, headache, dyspnea and anosmia and was more likely with increasing age and body mass index and female sex. Experiencing more than five symptoms during the first week of illness was associated with long COVID (odds ratio = 3.53 (2.76-4.50)). A simple model to distinguish between short COVID and long COVID at 7 days (total sample size, n = 2,149) showed an area under the curve of the receiver operating characteristic curve of 76%, with replication in an independent sample of 2,472 individuals who were positive for severe acute respiratory syndrome coronavirus 2. This model could be used to identify individuals at risk of long COVID for trials of prevention or treatment and to plan education and rehabilitation services.
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            Long COVID or post-COVID-19 syndrome: putative pathophysiology, risk factors, and treatments

            Shin Yong (2021)
            Long COVID or post-COVID-19 syndrome first gained widespread recognition among social support groups and later in scientific and medical communities. This illness is poorly understood as it affects COVID-19 survivors at all levels of disease severity, even younger adults, children, and those not hospitalized. While the precise definition of long COVID may be lacking, the most common symptoms reported in many studies are fatigue and dyspnoea that last for months after acute COVID-19. Other persistent symptoms may include cognitive and mental impairments, chest and joint pains, palpitations, myalgia, smell and taste dysfunctions, cough, headache, and gastrointestinal and cardiac issues. Presently, there is limited literature discussing the possible pathophysiology, risk factors, and treatments in long COVID, which the current review aims to address. In brief, long COVID may be driven by long-term tissue damage (e.g. lung, brain, and heart) and pathological inflammation (e.g. from viral persistence, immune dysregulation, and autoimmunity). The associated risk factors may include female sex, more than five early symptoms, early dyspnoea, prior psychiatric disorders, and specific biomarkers (e.g. D-dimer, CRP, and lymphocyte count), although more research is required to substantiate such risk factors. While preliminary evidence suggests that personalized rehabilitation training may help certain long COVID cases, therapeutic drugs repurposed from other similar conditions, such as myalgic encephalomyelitis or chronic fatigue syndrome, postural orthostatic tachycardia syndrome, and mast cell activation syndrome, also hold potential. In sum, this review hopes to provide the current understanding of what is known about long COVID.
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              Global Prevalence of Post COVID-19 Condition or Long COVID: A Meta-Analysis and Systematic Review

              Chen Chen, Spencer Haupert, Lauren Zimmermann … (2022)
              Abstract Introduction This study aims to examine the worldwide prevalence of post COVID-19 condition, through a systematic review and meta-analysis. Methods PubMed, Embase, and iSearch were searched on July 5, 2021 with verification extending to March 13, 2022. Using a random effects framework with DerSimonian-Laird estimator, we meta-analyzed post COVID-19 condition prevalence at 28+ days from infection. Results 50 studies were included, and 41 were meta-analyzed. Global estimated pooled prevalence of post COVID-19 condition was 0.43 (95% CI: 0.39,0.46). Hospitalized and non-hospitalized patients have estimates of 0.54 (95% CI: 0.44,0.63) and 0.34 (95% CI: 0.25,0.46), respectively. Regional prevalence estimates were Asia— 0.51 (95% CI: 0.37,0.65), Europe— 0.44 (95% CI: 0.32,0.56), and North America— 0.31 (95% CI: 0.21,0.43). Global prevalence for 30, 60, 90, and 120 days after infection were estimated to be 0.37 (95% CI: 0.26,0.49), 0.25 (95% CI: 0.15,0.38), 0.32 (95% CI: 0.14,0.57) and 0.49 (95% CI: 0.40,0.59), respectively. Fatigue was the most common symptom reported with a prevalence of 0.23 (95% CI: 0.17,0.30), followed by memory problems (0.14 [95% CI: 0.10,0.19]). Discussion This study finds post COVID-19 condition prevalence is substantial; the health effects of COVID-19 appear to be prolonged and can exert stress on the healthcare system.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Am J Trop Med Hyg
                Journal ID (iso-abbrev): Am J Trop Med Hyg
                Journal ID (publisher-id): tpmd
                Journal ID (hwp): tropmed
                Title: The American Journal of Tropical Medicine and Hygiene
                Publisher: The American Society of Tropical Medicine and Hygiene
                ISSN (Print): 0002-9637
                ISSN (Electronic): 1476-1645
                Publication date (Electronic): 26 June 2023
                Publication date (Print): August 2023
                Publication date PMC-release: 26 June 2023
                Volume: 109
                Issue: 2
                Pages: 466-470
                Affiliations
                [ 1 ]Federal University of Acre, Rio Branco, Brazil;
                [ 2 ]University of Campinas, Campinas, Brazil;
                [ 3 ]Federal University of Parana, Curitiba, Brazil;
                [ 4 ]Division of Infectious Disease, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts;
                [ 5 ]Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
                Author notes
                [* ]Address correspondence to Odilson M. Silvestre, Federal University of Acre, Rodovia BR 364, Km 04, s/n, Distrito Industrial, Rio Branco, Acre 69920-900, Brazil. E-mail: oms087@ 123456mail.harvard.edu

                Authors’ addresses: Kletey M. Silva, Dhayn C. A. Freitas, Sabrina S. Medeiros, Laís V. A. Miranda, Jessica B. M. Carmo, Roberta G. Silva, Luana L. Becker, Emanuel S. Abreu, Leonardo Buranello, Maria S. M. Souza, and Odilson M. Silvestre, Federal University of Acre, Rio Branco, Brazil, E-mails: kletey.silva@ 123456sou.ufac.br , dhaynfreitas@ 123456gmail.com , sasamedeirosds@ 123456gmail.com , laisvitoria.am@ 123456hotmail.com , jborsoim@ 123456gmail.com , robertagabrielas@ 123456hotmail.com , luana.livelli@ 123456hotmail.com , emanuel225@ 123456outlook.com.br , leonardo.buranello23@ 123456gmail.com , ms16msouza@ 123456gmail.com , and oms087@ 123456mail.harvard.edu . Wilson Nadruz, University of Campinas, Campinas, Brazil, E-mail: wilsonnadruz@ 123456gmail.com . Miguel M. Fernandes-Silva, Federal University of Parana, Curitiba, Brazil, E-mail: miguelmoritafernandes@ 123456gmail.com . James H. Maguire, Division of Infectious Diseases, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, E-mail: jmaguire@ 123456bwh.harvard.edu . Cristina Toledo-Cornell, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, E-mail: ctoledocornell@ 123456gmail.com .

                Article
                Publisher ID: tpmd220362
                DOI: 10.4269/ajtmh.22-0362
                PMC ID: 10397456
                PubMed ID: 37364863
                SO-VID: fe705b29-ce3e-4333-89fc-281c7fd6ded1
                Copyright © © The author(s)
                License:

                This is an open-access article distributed under the terms of the Creative Commons Attribution (CC-BY) License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                Date received : 06 June 2022
                Date accepted : 10 December 2022
                Page count
                Pages: 5
                Categories
                Subject: Short Report

                ScienceOpen disciplines: Infectious disease & Microbiology
                Data availability:
                ScienceOpen disciplines: Infectious disease & Microbiology

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