Do women spend longer on wait lists for coronary bypass surgery? Analysis of a population-based registry in British Columbia, Canada
Bibliographic record
Abstract
BACKGROUND: Studies have shown patients who are delayed for surgical cardiac revascularization are faced with increased risks of symptom deterioration and death. This could explain the observation that operative mortality among persons undergoing coronary artery bypass surgery (CABG) is higher among women than men. However, in jurisdictions that employ priority wait lists to manage access to elective cardiac surgery, there is little information on whether women wait longer than men for CABG. It is therefore difficult to ascertain whether higher operative mortality among women is due to biological differences or to delayed access to elective CABG. METHODS: Using records from a population-based registry, we compared the wait-list time between women and men in British Columbia (BC) between 1990 and 2000. We compared the number of weeks from registration to surgery for equal proportions of women and men, after adjusting for priority, comorbidity and age. RESULTS: In BC in the 1990 s, 9,167 patients aged 40 years and over were registered on wait lists for CABG and spent a total of 136,071 person-weeks waiting. At the time of registration for CABG, women were more likely to have a comorbid condition than men. We found little evidence to suggest that women waited longer than men for CABG after registration, after adjusting for comorbidity and age, either overall or within three priority groups. CONCLUSION: Our findings support the hypothesis that higher operative mortality during elective CABG operations observed among women is not due to longer delays for the procedure.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 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".