Sex disparities in quality of care and outcomes of patients with cancer presenting with ST elevation myocardial infarction; a nationwide cohort study
Bibliographic record
Abstract
Abstract Background While current evidence suggests that the clinical outcomes of ST-elevation myocardial infarction (STEMI) are worse among patients with cancer, it is unknown what role the patient’s sex plays. Methods A nationally-linked cohort of STEMI patients (January 2005-March 2019) were obtained from the UK Myocardial Infarction National Audit Project (MINAP) and UK national Hospital Episode Statistics Admitted Patient Care (HES APC) registries. The impact of sex on clinical outcomes was assessed using Cox proportional hazard models and competing risk models. Results A total of 8,581 STEMI indexed admissions with cancer who survived to discharge were identified between 1st Jan 2005 and 30th March 2019 (25.8% were women). Women were less likely to be admitted for care under a cardiology consultant (men 72.4%, women 63.9%), receive invasive coronary revascularization (men 60.2%, women 47.2%), or receive dual antiplatelet therapy (men 69.1%, women 61.9%). Women were also less likely to receive optimum care quality (men 64.1%, women 53.1%). After adjusting for confounders, women had higher risk of death within 1-year post-discharge (HR 1.40, 95% CI 1.29-1.53). The risk of major bleeding (HR 0.71, 95% CI 0.51-1.01) and reinfarction (HR 1.00, 95% CI 0.70-1.44) at 1 year were comparable to men. Relative survival analysis showed that 676 (95% CI 192-1,295) female lives across England can be saved at 1 year if sex disparities are addressed. Conclusion In STEMI patients with cancer, women have higher risk of death with hundreds of lives potentially saved if sex disparities in patients’ care are addressed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".