Impact of Left Ventricular to Mitral Valve Ring Mismatch on Recurrent Ischemic Mitral Regurgitation After Ring Annuloplasty
Bibliographic record
Abstract
BACKGROUND: In ischemic mitral regurgitation (IMR), ring annuloplasty is associated with a significant rate of recurrent MR. Ring size is based on intertrigonal distance without consideration of left ventricular (LV) size. However, LV size is an important determinant of mitral valve (MV) leaflet tethering before and after repair. We aimed to determine whether LV-MV ring mismatch (mismatch of LV size relative to ring size) is associated with recurrent MR in patients with IMR after restrictive ring annuloplasty. METHODS: Patients with moderate or severe IMR from the 2 Cardiothoracic Surgical Trials Network IMR trials who received MV repair were examined at 1 year after surgery. Baseline LV size was assessed by LV end-diastolic dimension and LV end-systolic dimension (LVESd). LV-MV ring mismatch was calculated as the ratio of LV to ring size (LV end-diastolic dimension/ring size and LVESd/ring size). RESULTS: At 1 year after ring annuloplasty, 45 of 214 patients with MV repair (21%) had moderate or greater MR. In univariable logistic regression analysis, larger LVESd (P=0.02) and LVESd/ring size (P=0.007) were associated with recurrent MR. In multivariable models adjusted for age, sex, baseline LV ejection fraction, and severe IMR, only LVESd/ring size (odd ratio per 0.5 increase, 2.20; 95% confidence interval, 1.05-4.62; P=0.038) remained significantly associated with 1-year MR recurrence. CONCLUSIONS: LV-MV ring size mismatch is associated with increased risk of MR recurrence. This finding may be helpful in guiding choice of ring size to prevent recurrent MR in patients undergoing MV repair and in identifying patients who may benefit from MV repair with additional subvalvular intervention or MV replacement rather than repair alone. CLINICAL TRIAL REGISTRATION: URL:http://clinicaltrials.gov. Unique identifiers: NCT00806988 and NCT00807040.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".