Incidence and Characterization of Post-COVID-19 Symptoms in Hospitalized COVID-19 Survivors to Recognize Syndemic Connotations in India: Single-Center Prospective Observational Cohort Study
Bibliographic record
Abstract
BACKGROUND: Long COVID, or post-COVID-19 syndrome, is the persistence of signs and symptoms that develop during or after COVID-19 infection for more than 12 weeks and are not explained by an alternative diagnosis. In spite of health care recouping to prepandemic states, the post-COVID-19 state tends to be less recognized from low- and middle-income country settings and holistic therapeutic protocols do not exist. Owing to the syndemic nature of COVID-19, it is important to characterize post-COVID-19 syndrome. OBJECTIVE: We aimed to determine the incidence of post-COVID-19 symptoms in a cohort of inpatients who recovered from COVID-19 from February to July 2021 at a tertiary-care center in South India. In addition, we aimed at comparing the prevalence of post-COVID-19 manifestations in intensive care unit (ICU) and non-ICU patients, assessing the persistence, severity, and characteristics of post-COVID-19 manifestations, and elucidating the risk factors associated with the presence of post-COVID-19 manifestations. METHODS: A total of 120 adult patients admitted with COVID-19 in the specified time frame were recruited into the study after providing informed written consent. The cohort included 50 patients requiring intensive care and 70 patients without intensive care. The follow-up was conducted on the second and sixth weeks after discharge with a structured questionnaire. The questionnaire was filled in by the patient/family member of the patient during their visit to the hospital for follow-up at 2 weeks and through telephone follow-up at 6 weeks. RESULTS: The mean age of the cohort was 55 years and 55% were men. Only 5% of the cohort had taken the first dose of COVID-19 vaccination. Among the 120 patients, 58.3% had mild COVID-19 and 41.7% had moderate to severe COVID-19 infection. In addition, 60.8% (n=73) of patients had at least one persistent symptom at the sixth week of discharge and 50 (41.7%) patients required intensive care during their inpatient stay. The presence of persistent symptoms at 6 weeks was not associated with severity of illness, age, or requirement for intensive care. Fatigue was the most common reported persistent symptom with a prevalence of 55.8%, followed by dyspnea (20%) and weight loss (16.7%). Female sex (odds ratio [OR] 2.4, 95% CI 1.03-5.58; P=.04) and steroid administration during hospital stay (OR 4.43, 95% CI 1.9-10.28; P=.001) were found to be significant risk factors for the presence of post-COVID-19 symptoms at 6 weeks as revealed by logistic regression analysis. CONCLUSIONS: Overall, 60.8% of inpatients treated for COVID-19 had post-COVID-19 symptoms at 6 weeks postdischarge from the hospital. The incidence of post-COVID-19 syndrome in the cohort did not significantly differ across the mild, moderate, and severe COVID-19 severity categories. Female sex and steroid administration during the hospital stay were identified as predictors of the persistence of post-COVID-19 symptoms at 6 weeks.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".