Long-term outcomes comparison of mitral valve repair or replacement for secondary mitral valve regurgitation. An updated systematic review and reconstructed time-to-event study-level meta-analysis
Bibliographic record
Abstract
BACKGROUND AND AIM: The ideal surgical intervention for secondary mitral regurgitation (SMR), a disease of the left ventricle not the mitral valve itself, is still debated. We performed an updated systematic review and study-level meta-analysis investigating mitral valve repair (MVr) versus mitral valve replacement (MVR) for adult patients with SMR, with or without coronary artery disease (CAD). METHODS: PubMed, CENTRAL and EMBASE were searched for studies comparing MVr versus MVR. Randomized trial or observational studies were considered eligible. Primary endpoint was long-term mortality for any cause. Kaplan-Meier survival curves were reconstructed and compared with Cox linear regression. Landmark analysis and time-varying hazard ratio (HR) were analyzed. Sensitivity analyses included meta-regression and separate sub-analysis. A random effects model was used. RESULTS: Twenty-three studies (MVr=3,727 and MVR=2,839) were included. One study was a randomized trial, and 19 studies were adjusted. The mean weighted follow-up was 3.7±2.8 years. MVR was associated with significative greater late mortality (HR=1.26; 95 % CI, 1.14-1.39; P<0.0001) at 10-year follow-up. There was a time-varying trend showing an increased risk of mortality in the first 2 years after MVR (HR=1.38; 95 % CI, 1.21-1.56; P<0.0001), after which this difference dissipated (HR=0.94; 95 % CI, 0.81-1.09; P=0.41). Separate sub-analyses showed comparable long-term mortality in patients with concomitant coronary surgery ≥90 %, left ventricle ejection fraction ≤40 %, and sub-valvular apparatus preservation rate of 100 %. CONCLUSIONS: Compared to repair, MVR is associated with higher probability of mortality in the first 2 years following surgery, after which the two procedures showed comparable late mortality rate.
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 | 0.010 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.030 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".