Older Age and Frailty are Associated with Higher Mortality but Lower ICU Admission with COVID-19
Bibliographic record
Abstract
Background: We report characteristics and outcomes of adults admitted to Canadian Immunization Research Network (CIRN) Serious Outcomes Surveillance (SOS) Network hospitals with COVID-19 in 2020. Methods: Patients with laboratory-confirmed COVID-19 admitted to 11 sites in Ontario, Quebec, Alberta, and Nova Scotia up to December 31, 2020 were enrolled in this prospective observational cohort study. Measures included age, sex, demographics, housing, exposures, Clinical Frailty Scale, comorbidities; in addition, length of stay, intensive care unit (ICU) admission, mechanical ventilation, and survival were assessed. Descriptive analyses and multivariable logistic regressions were conducted. Results: Among 2,011 patients, mean age was 71.0 (range 19-105) years. 29.7% were admitted from assisted living or long-term care facilities. The full spectrum of frailty was represented in both younger and older age groups. 81.8% had at least one underlying comorbidity and 27.2% had obesity. Mortality was 14.3% without ICU admission, and 24.6% for those admitted to ICU. Older age and frailty were independent predictors of lower ICU use and higher mortality; accounting for frailty, obesity was not an independent predictor of mortality, and associations of comorbidities with mortality were weakened. Conclusions: Frailty is a critical clinical factor in predicting outcomes of COVID-19, which should be considered in research and clinical settings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".