Systematic review and meta-analysis of the impact of sex on outcomes after aortic valve replacement
Bibliographic record
Abstract
AIMS: In recent years, extensive literature has been produced demonstrating inferior outcomes for women when compared with men undergoing heart valve interventions. Herein, we seek to analyze the literature comparing outcomes between men and women undergoing surgical aortic valve replacement (SAVR). METHODS: A systematic literature search of PubMed, MEDLINE, and Embase was conducted for articles comparing differences in outcomes between adult men and women undergoing SAVR. One thousand nine hundred and ninety titles were screened, of which 75 full texts were reviewed, and a total of 19 manuscripts met the inclusion criteria and were included in this review. RESULTS: Pooled estimates of mortality demonstrated that women tended to have lower rates of survival within the first 30 days post-SAVR, although mid-term and long-term mortality did not differ significantly up to 10 years postoperatively. Pooled estimates of postoperative data indicated no difference in the rates of stroke and postoperative bleeding. Rates of aortic valve reoperation and acute kidney injury favored women. CONCLUSION: Despite the inferior outcomes for women post-SAVR that have been reported in recent years, the results of this meta-analysis demonstrate comparable results between the sexes with comparable mid- to long-term mortality in data pooled from the literature. Although mortality favored men in the short term, rates of aortic valve reoperation and acute kidney injury favored women. Future investigation into this field should focus on identifying discrepancies in diagnosis and initial surgical management in order to address any potential factors contributing to discrepant short-term outcomes.
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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 | 0.017 | 0.052 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.028 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".