Sex and Medium-term Outcomes of ST-Segment Elevation Myocardial Infarction in Kerala, India: A Propensity Score–Matched Analysis
Bibliographic record
Abstract
Background Sex-based differences have been found in outcomes following ST-segment myocardial infarction (STEMI). Studies assessing sex-based differences in STEMI among Indian patients have reported conflicting results. Methods A prospective multicenter registry of consecutive patients with STEMI who presented to percutaneous coronary intervention (PCI)–capable hospitals in the Indian state of Kerala between June 2013 and March 2017 was used to assess 1-year outcomes. The primary endpoint was a composite of major adverse cardiac events (MACE), including death, stroke, nonfatal myocardial infarction, and rehospitalization for heart failure. Outcomes of 2 sex-based propensity score–matched groups were compared. Results We included 3194 patients (19.4% women). Women presenting with STEMI were older, had more traditional cardiovascular risk factors, and were more likely to be classified as living in poverty. After propensity-score matching, women experienced greater incidence of MACE (20.9% vs 14.3%, P < 0.01), primarily driven by increased 1-year mortality (14.3% vs 8.6%, P < 0.01). Women were more likely to experience prehospital delays, compared with men. Although reperfusion rates were similar between the groups, men were more likely than women to undergo reperfusion within the first 12 hours of chest pain onset. Among patients undergoing primary PCI, women were more likely to have delayed PCI than were men (80.2% vs 72.9%, P = 0.03). Procedural characteristics were similar between groups. Conclusions Women in this cohort experienced higher incidence of MACE at 1 year, compared to men, primarily owing to increased mortality. Timeliness of reperfusion appears to be the primary factor impacting differences in outcomes between the 2 groups and may represent an attractive target for quality-improvement initiatives.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".