COVID-19–Associated Outcomes of Critical Illness in Patients with Frailty: a Cohort Study
Bibliographic record
Abstract
Background Pre-admission frailty has been associated with higher hospital mortality in patients with critical illness. We aimed to measure the prevalence of frailty and its associated outcomes in patients with COVID-19 critical illness. Methods A historical cohort study of all adults admitted to ICU with a pneumonia diagnosis in Alberta, Canada between May 1, 2020, and October 31, 2020. At ICU admission patients were routinely assessed for frailty using the Clinical Frailty Scale (CFS). Frailty was defined as a CFS score ≥5. Primary outcomes were pre-admission frailty prevalence and hospital mortality. Results The cohort (n=521) prevalence of frailty was 34.2% (n=178), mean (SD) age was 58.8 (14.9) years, APACHE II 22.8 (8.0), and 39.5% (n=206) were female. COVID-19 pneumonia was diagnosed in (19.0%; n=99) admissions; pre-admission frailty was present in 20.2% (n=20) vs. 79.8% (n=79) non-frail (p<.001). Among ICU patients admitted with COVID-19, hospital mortality in frail patients was 35.4% (n=63) vs. 14.0% (n=48) in non-frail (p<.001). Conclusion Pre-admission frailty was present in 20.2% of COVID-19 ICU admissions and was associated with higher risk of hospital mortality. Frailty assessment may yield valuable prognostic information when considering COVID-19 ICU admission; however, further study is needed to identify effect on patient-centred outcomes in this heterogeneous population.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 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".