Sex differences in outcomes of transcatheter edge‐to‐edge repair with MitraClip: A meta‐analysis
Bibliographic record
Abstract
BACKGROUND: Transcatheter edge-to-edge repair (TEER) with MitraClip improves outcomes among select patients with moderate-to-severe and severe mitral regurgitation; however, data regarding sex-specific differences in the outcomes among patients undergoing TEER are limited. METHODS: An electronic search of the PubMed, Embase, Central, and Web of Science databases for studies comparing sex differences in outcomes among patients undergoing TEER was performed. Summary estimates were primarily conducted using a random-effects model. RESULTS: Eleven studies with a total of 24,905 patients (45.6% women) were included. Women were older and had a lower prevalence of comorbidities, including diabetes, chronic kidney disease, and coronary artery disease. There was no difference in procedural success (odds ratio [OR]: 0.75, 95% confidence interval [CI]: 0.55-1.05) and short-term mortality (i.e., up to 30 days) between women and men (OR: 1.16, 95% CI: 0.97-1.39). Women had a higher incidence of periprocedural bleeding and stroke (OR: 1.34, 95% CI: 1.15-1.56) and (OR: 1.57, 95% CI: 1.10-2.25), respectively. At a median follow-up of 12 months, there was no difference in mortality (OR: 0.98, 95% CI: 0.89-1.09) and heart failure hospitalizations (OR: 1.07, 95% CI: 0.68-1.67). An analysis of adjusted long-term mortality showed a lower incidence of mortality among women (hazards ratio: 0.77, 95% CI: 0.67-0.88). CONCLUSIONS: Despite a lower prevalence of baseline comorbidities, women undergoing TEER with MitraClip had higher unadjusted rates of periprocedural stroke and bleeding as compared with men. There was no difference in unadjusted procedural success, short-term or long-term mortality. However, women had lower adjusted mortality on long-term follow-up. Future high-quality studies assessing sex differences in outcomes after TEER are needed to confirm these findings.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.078 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".