Abstract 2068: Systematic Undersized Rigid Ring Decreases Recurrence Rate Following Repair of Ischemic Mitral Valve
Bibliographic record
Abstract
Introduction: Chronic ischemic mitral regurgitation (MR) has been associated with poor long-term survival. Suboptimal midterm results have been a growing concern in the surgical community. In recent years, our approach to repair those valves has evolved to a standardized technique using complete, rigid and small annuloplasty rings. This study aims to compare this systematic approach with our prior experience from 1996 –2001 where recurrent MR rate was high. Methods: 129 patients underwent repair for pure ischemic mitral valve regurgitation between 2002 and 2005 at our institution. Of these patients, 99 had clinical and echographic follow-up. These patients were compared to the 1996 –2001 cohort of 73 patients. Results: Preoperatively, 84% of patients were in NYHA class III or IV, 17% had moderate MR, 83% had moderate-severe to severe MR. Sixteen were redo operations, mostly of previous CABG. All patients except one were treated with a complete rigid ring (Annuloflo 46.5%, Physioring 34.9%, Etlogix 13.9%, others 3.8%). Ring size was: 24 (0.8%); 26 (55.8%); 28 (38%); or 30 (4.5%). Mortality was 8.5% at 30 days, 14.7% at 1 year and 17.8% at 2 years. Immediate postoperative regurgitation was absent or trace in all patients. Freedom from reoperation was 97%. Mean postoperative NYHA class was 1.15 at a mean follow-up of 28 months. Recurrent moderate mitral regurgitation (2+) was 15.34%, severe mitral regurgitation (3+ to 4+) was 13.4% at a mean follow-up of 16 months. In the 73 patients from the period 1996 –2001 at the same echo follow-up time, the moderate and severe recurrence were: 37% and 21%. The decrease in the recurrence rate was highly significant (p=0.001). Conclusion: A more standardized approach to ischemic mitral valve repair has improved the high recurrence rate previously reported by our group. Long-term follow-up is necessary to confirm these findings.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.003 | 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".