Persistent COVID-19 symptoms in community-living older adults from the Canadian Longitudinal Study on Aging (CLSA)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Symptom persistence in non-hospitalized COVID-19 patients, also known as Long COVID or Post-acute Sequelae of COVID-19, is not well characterized or understood, and few studies have included non-COVID-19 control groups. METHODS: We used data from a cross-sectional COVID-19 questionnaire (September-December 2020) linked to baseline (2011-2015) and follow-up (2015-2018) data from a population-based cohort including 23,757 adults 50+ years to examine how age, sex, and pre-pandemic physical, psychological, social, and functional health were related to the severity and persistence of 23 COVID-19-related symptoms experienced between March 2020 and questionnaire completion. RESULTS: The most common symptoms are fatigue, dry cough, muscle/joint pain, sore throat, headache, and runny nose; reported by over 25% of participant who had (n = 121) or did not have (n = 23,636) COVID-19 during the study period. The cumulative incidence of moderate/severe symptoms in people with COVID-19 is more than double that reported by people without COVID-19, with the absolute difference ranging from 16.8% (runny nose) to 37.8% (fatigue). Approximately 60% of male and 73% of female participants with COVID-19 report at least one symptom persisting >1 month. Persistence >1 month is higher in females (aIRR = 1.68; 95% CI: 1.03, 2.73) and those with multimorbidity (aIRR = 1.90; 95% CI: 1.02, 3.49); persistence >3 months decreases by 15% with each unit increase in subjective social status after adjusting for age, sex and multimorbidity. CONCLUSIONS: Many people living in the community who were not hospitalized for COVID-19 still experience symptoms 1- and 3-months post infection. These data suggest that additional supports, for example access to rehabilitative care, are needed to help some individuals fully recover.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it