ArticleBMC infectious diseases2025
Long COVID in the population of COVID-19 hospitalized patients discharged from SUS' hospitals in Rio de Janeiro City, Brazil: a patient-engaged cohort survey study.
Article in BMC infectious diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLong COVID (LC) is a global health concern, affecting millions and placing significant strain on healthcare systems. However, there is a notable lack of LC research in low- and middle-income countries, particularly in the global south. This study aims to fill this gap by focusing on Brazil, a country with an emerging LC literature but limited population estimates due to sampling constraints. Our unique focus is to estimate the prevalence of persistent symptoms and LC self-reported diagnosis among COVID-19 patients hospitalized in Rio de Janeiro City public hospitals. We also aim to identify factors associated with the LC measures and most frequent symptoms, providing valuable insights for healthcare systems and policymakers.
methodsWe designed a comprehensive, patient-engaged cohort survey study to assess LC symptoms and administered it to a probability sample of adults six to 24 months post-discharge from public hospitals in Rio de Janeiro City. LC was measured as (i) at least one persistent symptom or (ii) self-reported LC. Among the symptoms, we considered post-exertional malaise, which is frequently neglected in LC studies. Additionally, we applied an adaptation of the DePaul Symptom Questionnaire to account not only for the presence but also the frequency of symptom occurrence. We estimate the prevalence of symptoms and use logistic regression models to identify associations between LC and the most frequent LC symptoms and independent variables, assessing demographic, socioeconomic, lifestyle, and clinical characteristics, vaccination, and severity of acute disease.
resultsResults indicate the predominant study's focus on low-income and highly vulnerable people, with an elevated prevalence of comorbidities before LC. In the study population of 11,328 persons, 71.3% (95%CI 66.3; 76.2) reported frequently experiencing at least one persistent symptom, and 39.3% (95%CI 34.2; 44.4) self-reported having LC. The most frequent symptoms were fatigue, post-exertional malaise, joint pain, sleep disturbance, and cognitive impairment, and symptoms were consistently more likely to occur among women. Age was non-linearly related to LC, and comorbidities before COVID-19 hospitalization were positively associated with LC symptoms.
conclusionsEvidence is provided for the LC burden among COVID-19 hospitalized patients even 24 months post-discharge. LC accessible and appropriate healthcare is fundamental.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.