Does sex impact outcomes after mitral valve surgery? A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: The published literature investigating the impact of sex on outcomes after mitral valve (MV) surgery has demonstrated inferior outcomes for females over males. However, the true relationship between sex and outcomes after MV surgery continues to be poorly understood. MATERIALS: PubMed, Medline, and Embase were systematically searched for articles published from 1 January 2005 to 1 August 2021. This systematic review included retrospective and prospective studies investigating the relationship between sex and outcomes after MV surgery. In all, 2068 articles were initially screened and 12 studies were included in this review. RESULTS: Few studies were adequately powered or structured to investigate this topic. Few studies propensity matched patients or isolated for surgical approach. In individual studies, females experienced increased rates of short-term and long-term mortality and increased 1-year mortality in the pooled data. Males experienced increased rates of required pacemaker insertion. The remaining rates of morbidity and mortality did not differ significantly between males and females. CONCLUSIONS: This review identified increased rates of 1-year mortality in the pooled data for females, while males had increased rates of pacemaker insertion. Despite this, the absence of propensity matching and isolating for surgical approach has introduced confounding variables that impair the ability of the included studies to interpret the results found in the current literature. Studies isolating for surgical approach, propensity matching patients, and examining outcomes with long-term follow-up are required to elucidate the true nature of this relationship.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.056 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.034 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".