Natural History and Predictors of Outcome in Patients With Concomitant Functional Mitral Regurgitation at the Time of Aortic Valve Replacement
Bibliographic record
Abstract
BACKGROUND: Concomitant functional mitral regurgitation (FMR) in patients undergoing aortic valve replacement (AVR) is frequently not corrected because it may improve after AVR; however, data supporting this assumption are sparse. We ascertained the impact of clinical and echocardiographic parameters on the outcome of patients with or without concomitant FMR at the time of AVR. METHODS AND RESULTS: Clinical and echocardiographic follow-up was performed on 848 patients who underwent AVR after 1990. Risk factors for mortality and a composite outcome of heart failure (CHF) symptoms, CHF death, or subsequent mitral repair or replacement, were examined with bootstrapped Cox proportional hazard models. Follow-up was 4591 patient-years (mean 5.4+/-3.4 years; maximum 14.2 years). FMR > or = 2+ had no independent adverse effect on survival in patients with aortic stenosis (AS) or insufficiency (AI). However, AS patients with FMR > or = 2+ and 1 additional risk factor (left atrial diameter >5 cm, preoperative peak aortic valve gradient <60 mm Hg, or atrial fibrillation) were at increased risk for the composite outcome (hazard ratio [HR]: 2.7; P=0.004). AI patients with FMR > or = 2+ and a left ventricular end-systolic diameter <45 mm were also at risk (HR: 4.0; P=0.02). Clinical risk factors in the AS and AI subgroups were associated with an increased likelihood of mitral regurgitation > or = 2+ at 18 months postoperatively. CONCLUSIONS: AS patients with FMR > or = 2+ and a left atrial diameter >5 cm, preoperative peak aortic valve gradient <60 mm Hg, or atrial fibrillation have a significantly higher risk of CHF and persistent mitral regurgitation after AVR than other AS patients. AI patients with FMR > or = 2+ and a left ventricular end-systolic diameter <45 mm preoperatively are also at increased risk. Others fare well after AVR.
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) | 0.000 | 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) | 0.000 | 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".