Frailty as a predictor of mortality among patients with COVID-19: a systematic review and meta-analysis
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: A large number of studies have explored the association between frailty and mortality among COVID-19 patients, with inconsistent results. The aim of this meta-analysis was to synthesize the evidence on this issue. METHODS: Three databases, PubMed, Embase, and Cochrane Library, from inception to 20th January 2021 were searched for relevant literature. The Newcastle-Ottawa Scale (NOS) was used to assess quality bias, and STATA was employed to pool the effect size by a random effects model. Additionally, potential publication bias and sensitivity analyses were performed. RESULTS: Fifteen studies were included, with a total of 23,944 COVID-19 patients, for quantitative analysis. Overall, the pooled prevalence of frailty was 51% (95% CI: 44-59%). Patients with frailty who were infected with COVID-19 had an increased risk of mortality compared to those without frailty, and the pooled hazard ratio (HR) and odds ratio (OR) were 1.99 (95% CI: 1.66-2.38) and 2.48 (95% CI: 1.78-3.46), respectively. In addition, subgroup analysis based on population showed that the pooled ORs for hospitalized patients in eight studies and nursing home residents in two studies were 2.62 (95% CI: 1.68-4.07) and 2.09 (95% CI: 1.40-3.11), respectively. Subgroup analysis using the frailty assessment tool indicated that this association still existed when using the clinical frailty scale (CFS) (assessed in 6 studies, pooled OR = 2.88, 95% CI: 1.52-5.45; assessed in 5 studies, pooled HR = 1.99, 95% CI: 1.66-2.38) and other frailty tools (assessed in 4 studies, pooled OR = 1.98, 95% CI: 1.81-2.16). In addition, these significant positive associations still existed in the subgroup analysis based on study design and geographic region. CONCLUSION: Our study indicates that frailty is an independent predictor of mortality among patients with COVID-19. Thus, frailty could be a prognostic factor for clinicians to stratify high-risk groups and remind doctors and nurses to perform early screening and corresponding interventions urgently needed to reduce mortality rates in patients infected by SARS-CoV-2.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.018 | 0.004 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it