Abstract 11216: Greater Prognostic Value of Left Atrial Mechanics Compared to Left Atrial Volume in Atrial Functional Mitral Regurgitation
Bibliographic record
Abstract
Introduction: Atrial functional mitral regurgitation (AFMR) is associated with increased mortality and morbidity. Optimal management however remains unclear. Mechanism of AFMR is linked to left atrial remodeling yet left atrial (LA) size and function are still poorly characterized. Objectives: To assess LA size and function by reservoir strain (LASr) and reservoir work (LAWr) and their impact on outcome in AFMR. Methods: Consecutive patients examined at our institution between 2001-2019 and with AFMR of at least moderate MR degree were examined. LAWr was estimated as LASr x LA reservoir volume, and patients were grouped by median LASr or LAWr. Outcomes were all-cause death or heart failure hospitalizations. Results: 515 patients with moderate or greater AFMR were followed for a median of 5 [range 1-17] years. All patients had previously documented atrial fibrillation (AF) (38%), heart failure with preserved ejection fraction (HFpEF) without AF (24%), or both (HFpEF+AF, 38%). LA volume was largest in AF patients and smallest in HFpEF while LA function parameters were greater in HFpEF and AF compared to the combined HFpEF+AF group (Fig. A,B).During follow-up, patients with low LASr or LAWr had higher risk of death (p <0.001, Fig. C) and heart failure hospitalizations (p<0.05). In Cox regression analyses, low LASr and LAWr, but not LA volume and left ventricular function, were associated with a higher risk of death (LASr: HR 2.3 (95% CI 1.6-3.5); LAWr HR 3.4 (95% CI 2.4-4.7), both p<0.001) after adjustment for clinical and echocardiographic confounders. Conclusion: LA reservoir function but not LA size is a robust predictor of outcome in AFMR with moderate or greater MR. This provides mechanistic insights into the interplay of functional parameters versus LA geometric changes in AFMR.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".