Association of Left Atrial Function With Mitral Regurgitation: The Atherosclerosis Risk in Communities Study
Bibliographic record
Abstract
BACKGROUND: Lower left atrial (LA) function may precede LA enlargement and contribute to mitral regurgitation (MR). We examined the association of LA reservoir strain (a measure of LA function) with MR in the ARIC (Atherosclerosis Risk in Communities) study. METHODS: We analyzed ARIC participants with echocardiograms at Visits 5 (2011-2013) and 7 (2018-2019). LA reservoir strain was measured at Visit 5. MR was diagnosed by echocardiography. The cross-sectional association was assessed at Visit 5, and the prospective association was examined through Visit 7 using multivariable logistic regression. RESULTS: In the cross-sectional analysis (n=4689, mean age 75.2±5.0 years, 60.2% female, 19.9% Black), 1927 participants (41.1%) had prevalent MR. Each 1-SD (7.53%) lower LA reservoir strain was associated with higher odds of prevalent MR (odds ratio [OR], 1.12 [95% CI, 1.04-1.20]). In the prospective analysis (n=1480, mean age 73.5±4.2 years, 54.9% female, 22.6% Black), 409 participants developed MR. A 1-SD (6.71%) lower LA reservoir strain was associated with higher odds of incident MR (OR, 1.18 [95% CI, 1.04-1.34]); the association was partially attenuated after adjusting for post-Visit 5 heart failure and atrial fibrillation (OR, 1.14 [95% CI, 1.00-1.30]) and further attenuated after adjusting for LA volume index from Visit 5 (OR, 1.11 [95% CI, 0.98-1.27]). CONCLUSIONS: LA reservoir strain is associated with prevalent and incident MR in older adults. The association between lower LA reservoir strain and incident MR may be partially explained by LA enlargement, apart from atrial fibrillation and heart failure.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".