Prevalence of persistent symptoms at least 1 month after SARS-CoV-2 Omicron infection in adults
Bibliographic record
Abstract
Background: Persistent post-COVID-19 symptoms pose an important health care burden. The Omicron variant has rapidly spread across the world and infected millions of people, largely exceeding previous variants. The potential for many of these people to develop persistent symptoms is a major public health concern. The aim of this study was to determine the prevalence and risk factors of post-COVID-19 symptoms associated with Omicron. Methods: We conducted a single-centre prospective observational study in Quebec, Canada, between December 2021 and April 2022. Participants were adults enrolled in the Biobanque Québécoise de la COVID-19 (BQC19). Cases were considered Omicron cases as more than 85% were estimated to be attributable to Omicron variant during that period. Adults with polymerase chain reaction (PCR)-confirmed COVID-19 were recruited at least 4 weeks after the onset of infection. Results: Of 1,338 individuals contacted, 290 (21.7%) participants were recruited in BQC19 during that period. Median duration between the initial PCR test and follow-up was 44 days (IQR 31-56 d). A total of 137 (47.2%) participants reported symptoms at least 1-month post-infection. The majority (98.6%) had a history of mild COVID-19 illness. Most common persistent symptoms included fatigue (48.2%), shortness of breath (32.6%), and cough (24.1%). Number of symptoms during acute COVID-19 was identified as a risk factor for post-COVID-19 symptoms (OR 1.07 [95% CI 1.03% to 1.10%] p = 0.009). Conclusions: This is the first study reporting the prevalence of post-COVID-19 symptoms associated with Omicron in Canada. These findings will have important implications for provincial services planning.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".