Transcatheter Edge‐to‐Edge Repair for Severe Mitral Regurgitation in Patients With Cardiogenic Shock: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
BACKGROUND: Patients with severe mitral regurgitation and cardiogenic shock demonstrate a poor prognosis. Mitral transcatheter edge-to-edge repair could alter patient management. METHODS AND RESULTS: We systematically reviewed PubMed/Medline, Scopus, and Cochrane Library until January 2023, including studies assessing transcatheter edge-to-edge repair in patients with severe mitral regurgitation and cardiogenic shock. Studies with <5 patients were excluded. The primary outcome was device success and all-cause death, while secondary outcomes included myocardial infarction, stroke, and heart failure hospitalization rates at 30-day and intermediate-term follow-up. A fixed-effects meta-analysis was used to estimate pooled rates. Risk of bias was assessed with the Newcastle-Ottawa Scale. A total of 24 studies and 5428 patients were included, with a mean age of 71.2±3.3 years and a high mean Society of Thoracic Surgery score (15.2±8.9). Device success was achieved in 86% (95% CI, 85%-87%) and mitral regurgitation ≤2+ in 89% (95% CI: 88%-90%). The 30-day all-cause mortality rate was 14% (95% CI, 13%-15%). Stroke, myocardial infarction, and heart failure hospitalization rates were 2% (95% CI, 1%-2%), 15% (95% CI, 13%-18%), and 9% (95% CI, 8%-10%), respectively. Patients with acute myocardial infarction had similar device success (81% [95% CI, 74%-87%]), a 30-day mortality rate of 20% (95% CI, 16%-25%), and intermediate-term mortality rate of 14% (95% CI, 9%-19%). In non-myocardial infarction populations, the 30-day mortality rate was 13% (95% CI, 13%-14%), and the intermediate-term mortality rate was 35% (95% CI, 34%-36%). CONCLUSIONS: In patients with mitral regurgitation and cardiogenic shock, transcatheter edge-to-edge repair is associated with favorable 30-day and intermediate-term outcomes. Limitations, including the observational design of included studies and considerable heterogeneity, necessitate further research in this setting.
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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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.025 |
| 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 | 0.001 |
| 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".