Comparison of frailty instruments for predicting mortality and prolon ged hospitalization in acute coronary syndrome patients
Bibliographic record
Abstract
OBJECTIVE: To evaluate the relative strengths of 3 frailty assessment instruments for predicting mortality and prolonged hospitalization in acute coronary syndrome patients. DESIGN: Prospective cohort study. SETTING: Acute cardiac care units in New Zealand. PARTICIPANTS: 1174 patients >70 years of age hospitalized with an acute coronary syndrome. INTERVENTIONS: The Clinical Frailty Scale (CFS), Edmonton Frail Scale (EFS) and Fried Criteria (Fried), were completed during hospital admission following an acute coronary syndrome when the patient was clinically stable. PRIMARY AND SECONDARY OUTCOME MEASURES: All-cause mortality over the next ~5 years and hospitalization for >10 days in the next year determined from national administrative data. RESULTS: During median follow-up of 5.1 years there were 353 deaths. Harrell's C-statistic for mortality for EFS was 0.663, Fried 0.648 and CFS 0.640 (p<0.001 for all). C-statistics for hospitalization >10 days (n = 267, 22%) were EFS 0.649, Fried 0.628, and CFS 0.584 (p<0.001 for all). Associations between increase in frailty scores and mortality were graded including in patients not classified as frail. The hazard ratio (HR) for mortality, adjusted for age and sex, for patients with an EFS score ≥9 (n = 197) compared to ≤2 (n = 331) was 5.0 (95% CI: 3.4-7.4). In models which included the Euroscore II or GRACE risk scores the EFS improved risk discrimination for both mortality and prolonged hospitalization more than the CFS and Fried. CONCLUSION: In older patients assessed following an acute coronary syndrome the EFS discriminated the risk of all cause mortality and prolonged hospitalization better than the CFS and Fried tests, and improved risk discrimination when added to clinical risk scores.
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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 | 0.013 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 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".