Impact of physician’s sex/gender on processes of care, and clinical outcomes in cardiac operative care: a systematic review
Bibliographic record
Abstract
OBJECTIVES: This systematic review aimed to assess the role of physician's sex and gender in relation to processes of care and/or clinical outcomes within the context of cardiac operative care. DESIGN: A systematic review. DATA SOURCES: Searches were conducted in PsycINFO, Embase and Medline from inception to 6 September 2018. The reference lists of relevant systematic reviews and included studies were also searched. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Quantitative studies of any design were included if they were published in English or French, involved patients of any age undergoing a cardiac surgical procedure and specifically assessed differences in processes of care or clinical patient outcomes by physician's sex or gender. Studies were screened in duplicate by two pairs of independent reviewers. OUTCOME MEASURES: Processes of care, patient morbidity and patient mortality. RESULTS: The search yielded 2095 publications after duplicate removal, of which two were ultimately included. These studies involved various types of surgery, including cardiac. One study found that patients treated by female surgeons compared with male surgeons had a lower 30-day mortality. The other study, however, found no differences in patient outcomes by surgeon's sex. There were no studies that investigated anaesthesiologist's sex/gender. There were also no studies investing physician's sex or gender exclusively in the cardiac operating room. CONCLUSIONS: The limited data surrounding the impact of physician's sex/gender on the outcomes of cardiac surgery inhibits drawing a robust conclusion at this time. Results highlight the need for primary research to determine how these factors may influence cardiac operative practice, in order to optimise provider's performance and improve outcomes in this high-risk patient group.
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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 | 0.018 | 0.098 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.010 |
| Bibliometrics | 0.010 | 0.013 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".