Usefulness of a single-item general self-rated health question to predict mortality 12 months after an acute coronary syndrome
Bibliographic record
Abstract
BACKGROUND: A single-item general self-rated health (GSRH) question consistently predicts mortality in community cohort studies, but has not been examined in patients with acute coronary syndrome (ACS). We investigated whether a single-item GSRH question predicted mortality 12 months post-discharge in 800 ACS patients. METHODS: Logistic regression was used to assess the relationship of the single-item GSRH question with mortality, controlling for cardiac risk factors, including depressive symptoms. RESULTS: The single-item GSHR question was associated with mortality on a bivariable basis (odds ratio=0.50, 95% confidence interval=0.28-0.92, P=0.027), but was not significant after controlling for other risk factors (odds ratio=0.80, 95% confidence interval=0.40-1.60, P=0.522).
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".