Gender differences in the clinical management of patients with angina pectoris: a cross-sectional survey in primary care
Bibliographic record
Abstract
BACKGROUND: Previous research suggests that women admitted to hospital with acute myocardial infarction (MI) are managed less intensively than men. Chronic stable angina is the commonest clinical manifestation of coronary heart disease in the community, but little information is available concerning its contemporary clinical management. The aim of this study is to assess the extent of gender differences in the clinical management of angina pectoris in primary care. METHODS: A cross-sectional survey undertaken in 8 sentinel centres serving 63,724 individuals in the city of Liverpool (15% of the city population). Aspects of clinical care assessed included: risk factor recording (smoking, cholesterol, blood pressure, body mass index); secondary prevention (aspirin, beta-blocker, statin); cardiac investigation (exercise ECG, perfusion scanning, angiography); and revascularisation (percutaneous coronary intervention, coronary artery bypass grafting). Male-to-female adjusted odds ratios (AOR) were calculated (adjusted for age, angina duration, age at diagnosis and previous MI) using logistic regression. RESULTS: 1,162 patients (610 men; 552 women) with angina were identified. Women were older than men (71 vs 67 years), with a shorter duration of angina (6 vs 7 years), and a lower prevalence of previous MI (25% vs 43%). Men were significantly more likely than women to undergo detailed risk factor assessment (AOR = 1.35, 95%CI 1.06 to 1.73); receive 'triple' secondary prevention with aspirin, beta-blockers and statins (AOR = 1.47, 95%CI 1.07 to 2.02); access exercise ECG testing (AOR = 1.31, 95%CI 1.02 to 1.68); angiography (AOR = 1.61, 95%CI 1.23 to 2.12); and undergo coronary revascularisation (AOR = 1.93, 95%CI 1.39 to 2.68). CONCLUSION: Systematic gender differences exist in the comprehensive clinical management of patients with angina in primary care.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".