Preinfarction Angina Prior to First Myocardial Infarction Does not Influence Long‐Term Prognosis: A Retrospective Study with Subgroup Analysis in Elderly and Diabetic Patients
Bibliographic record
Abstract
BACKGROUND AND HYPOTHESIS: Although prodromal angina occurring shortly before an acute myocardial infarction (MI) has protective effects against in-hospital complications, this effect has not been well documented after initial hospitalization, especially in older or diabetic patients. We examined whether angina 1 week before a first MI provides protection in these patients. METHODS: A total of 290 consecutive patients, 143 elderly (>64 years of age) and 147 adults (<65 years of age), 68 of whom were diabetic (23.4%) and 222 nondiabetic (76.6%), were examined to assess the effect of preceding angina on long-term prognosis (56 months) after initial hospitalization for a first MI. RESULTS: No significant differences were found in long-term complications after initial hospitalization in these adult and elderly patients according to whether or not they had prodromal angina (44.4% with angina vs 45.4% without in adults; 45.5% vs 58% in elderly, P < 0.2). Nor were differences found according to their diabetic status (61.5% with angina vs 72.7% without in diabetics; 37.3% vs 38.3% in nondiabetics; P = 0.4). CONCLUSION: The occurrence of angina 1 week before a first MI does not confer long-term protection against cardiovascular complications after initial hospitalization in adult or elderly patients, whether or not they have diabetes.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".