A patient-centered view of symptoms, functional impact, and priorities in post-COVID-19 syndrome: Cross-sectional results from the Québec Action Post-COVID cohort
Bibliographic record
Abstract
ABSTRACT Background Health services planning and mechanism-focused research would benefit from a clearer picture of symptoms, impact, and personal priorities in post-COVID-19 syndrome (PCS). This study aimed to provide estimates of the symptom, function, and quality of life (QOL) impact of PCS. Methods People living in Quebec, aged ≥18, were eligible for the Québec Action for/pour le Post-COVID (QAPC) study if they had symptoms lasting more than 4 weeks post-acute SARS-CoV-2 infection, with or without a positive COVID-19 test. Recruitment was through conventional and social media between September 2022-January 2023. Standardized and individualized questionnaires, in French or English, were accessed through an online portal. We report cross-sectional results from the baseline visit of the first 414 participants in this ongoing longitudinal study. Results Individuals spontaneously reported symptoms attributable to an average of 4.5 organ systems. Fatigue was most frequent. Effects on function and quality of life were moderate to severe, and had already persisted for a year or more in the majority. Personal intervention priorities included fatigue and post-exercise malaise, cognitive symptoms, shortness of breath, and impaired taste and smell. Women and men were similar on PCS impact, while older age was associated with lower impact. Interpretation Symptom clusters defined a range of severity, with fatigue a pervasive symptom at all levels of severity. Participants in this study are likely to be representative of those seeking health care for post-COVID-19 symptoms in Canada and the results can inform next steps for clinical, research, and health 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".