Elevated left atrial pressure estimated by Doppler echocardiography is a key determinant of mitral valve tenting in functional mitral regurgitation
Bibliographic record
Abstract
BACKGROUND: Functional mitral regurgitation (FMR) may occur in patients with reduced or preserved left ventricular ejection fraction (LVEF) and has been associated with excess valvular tenting only in patients with reduced LVEF. This study aimed at identifying the predictors of FMR and to determine whether or not they are different in patients with reduced versus preserved LVEF. METHODS: 190 consecutive patients free of congenital or primary valvular disease had a comprehensive echocardiographic assessment of LV remodelling and function, diastolic function and FMR severity. RESULTS: 112 patients had depressed LVEF (<50%) and 78 had preserved LVEF. FMR was present in 30 patients with preserved LVEF and in 65 with reduced LVEF. Higher E/Ea, E/A and larger mitral tenting were independent predictors of FMR regardless of LVEF. The mitral tenting area was an independent predictor of FMR severity in patients with reduced or preserved LVEF (p = 0.04 and p = 0.0045) in addition to E/A (p = 0.0007), E/Ea (p = 0.004) in patients with reduced and preserved LVEF, respectively. Higher E/Ea was independently associated with larger mitral tenting in patients with reduced and preserved LVEF. Mitral tenting area was linearly related to E/Ea (r = 0.30, p<0.0001) and E/A (r = 0.43, p<0.0001) and LA enlargement (r = 0.54, p<0.0001) after having paired 96 patients with and without FMR on indices of LV remodelling. CONCLUSIONS: In both patients with preserved and reduced LVEF, mitral tenting that leads to FMR is mainly determined by both mitral tethering forces-that is, displacement of papillary muscles and by pushing forces-that is, increased left atrial pressure. This study underscores that LV preload is a key determinant of FMR.
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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 | 0.003 |
| 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) | 0.001 | 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".