Abstract P187: Assessing Gender Bias in the Treatment of Cardiovascular Disease in Canada
Bibliographic record
Abstract
The objective of this study was to determine the presence of gender bias in the treatment of CVD in Canada. Gender bias has been explored extensively in the treatment of CVD, particularly AMI. Previous research is inconsistent in suggesting that women who suffer an AMI are treated less optimally than men. To date, gender bias has not been well addressed in other CVD's, specifically CVA, CABG, or RRT. In an attempt to get a clearer grasp of the problem, CAP was also studied and served as a control. Retrospective chart reviews for all AMI's, CVA's, CABG's, and CAP's in 1995/6, 1998/9, and 2000/1 in two locations of Newfoundland (St. John's and central) were reviewed. Outcomes were analyzed for differences between men and women. Adjusting for baseline differences, regression models were used to assess the following: AMI - time to thrombolytics, admission to CCU, death, discharge beta blockers, ACE/ARB, anti-lipids, ASA; CVA - LOS, transfer to and time to rehabilitation center, death; CABG - time to CABG; CAP - appropriateness of antibiotics (AB), death. RRT was analyzed from the results of the STARRT (Study To Assess Renal Replacement Therapy) study, a Canadian multicentre retrospective chart review of incident dialysis patients followed for six months. Outcomes were explored for differences in care between men and women. Optimal care was based on 1) length of pre-dialysis care; 2) modality choice; 3) access; 4) laboratory parameters at dialysis start; 5) clinical outcomes. Women who had suffered an AMI had a significantly longer time to thrombolytics and were less likely to be admitted to the CCU but did not differ significantly from men in other modes of treatment. Women who were RRT patients began dialysis at a lower eGFR level after receiving less pre-dialysis care than men. Women who received treatment for CAP were less likely than men to receive the appropriate AB's according to the 1993 guidelines for AB treatment of CAP. There were no significant treatment differences between men and women who had suffered a CVA or who had had a CABG. There were no gender differences in death for any of the diseases. There is little evidence of a significant gender bias in cardiovascular disease in Canada. A potential gender bias in the treatment of CVD patients needs to be explored further.
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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 | 0.007 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".