The association of typical and atypical symptoms with in-hospital mortality in older adults with COVID-19: a multicentre cohort study
Bibliographic record
Abstract
Atypical disease presentations are common in older adults with COVID-19. The objective of this study was to determine the prevalence of atypical and typical symptoms in older adults with COVID-19 through progressive pandemic waves and the association of these symptoms with in-hospital mortality. This retrospective cohort study included consecutive adults aged over 65 years with confirmed COVID-19 infection who were admitted to seven hospitals in Toronto, Canada, from 1 March 2020 to 30 June 2021. The median age for the 1786 patients was 78.0 years and 847 (47.5%) were female. Atypical symptoms (as defined by geriatric syndromes) occurred in 1187 patients (66.5%), but rarely occurred in the absence of other symptoms ( n = 106; 6.2%). The most common atypical symptoms were anorexia ( n = 598; 33.5%), weakness ( n = 519; 23.9%), and delirium ( n = 449; 25.1%). Dyspnea (adjusted odds ratio [aOR] 2.05; 95% confidence interval [CI] 1.62–2.62), tachycardia (aOR 1.87; 95% CI 1.14–3.04), and delirium (aOR 1.52; 95% CI 1.18–1.96) were independently associated with in-hospital mortality. In a cohort of older adults hospitalized with COVID-19 infection, atypical presentations frequently overlapped with typical symptoms. Further research should be directed at understanding the cause and clinical significance of atypical presentations in older adults.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".