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: Adult patients with laboratory-confirmed COVID-19 admitted to eleven sites in Ontario, Quebec, Alberta and Nova Scotia up to December 31, 2020 were enrolled in this prospective observational cohort study. Age, sex, demographics, housing, exposure characteristics, Clinical Frailty Scale, comorbidities, and outcomes including length of stay, intensive care unit (ICU) admission, mechanical ventilation, and survival were conducted. Descriptive analyses and multivariable logistic regressions were conducted. Findings: Among 2011 patients, mean age was 71·0 (range 19-105) years. 45·7% were women and 74·0% were white. 21·5% were admitted from Assisted Living facilities, 8·2% from long term care, and 2·1% from homeless shelters. The full spectrum of frailty was represented in both younger and older age groups. The majority (61·7% of adults <65 and 91·2% of those >=65) had at least one underlying comorbidity and 27·2% had obesity. Mortality was 14·3% among those not admitted to ICU, and 24·6% for those admitted to ICU. Older age and higher frailty were associated with reduced ICU admission but increased mortality. Obesity was independently associated with ICU admission but not with death. Associations between underlying comorbidities and adverse outcomes were attenuated but persisted when adjusting for frailty. Interpretation: Frailty and age were independent predictors of lower ICU use and higher mortality; when accounting for frailty, obesity was not an independent predictor of mortality, and associations of comorbidities with mortality were weakened. Funding Statement: Funding was provided by the Public Health Agency of Canada and the Canadian Institutes of Health Research. Declaration of Interests: MKA reports grant funding from the Public Health Association of Canada, CIHR, Canadian Frailty Network, Sanofi Pasteur and GSK group of companies, and payments from Pfizer, Sanofi Pasteur and Seqirus outside the submitted work. AM reports payments from GSK, Seqirus and Sanofi Pasteur, outside the submitted work. JEM reports payments from RestorBio, Sanofi, GSK, Merck and Medicago outside of the submitted work. TFH reports grants from Pfizer and GSK. ML reports payments from Sanofi, Medicago, Sequirus, and Pfizer outside the submitted work. SAM reports grants and payments from Pfizer, GSK, Merck, Novartis and Sanofi, outside the submitted work. JG, JJL, GB, LV, ME, DM-C, AA, KW, ST, SS, AMc and KK report no conflicts of interest. Ethics Approval Statement: The protocol for active COVID-19 surveillance has been approved by each local site’s Research Ethics Board.
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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 | 0.002 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".