Left Atrial Distensibility and E/e' for Estimating Left Ventricular Filling Pressure in Patients With Stable Angina - A Comparative Echocardiography and Catheterization Study -
Bibliographic record
Abstract
BACKGROUND: Although E/e' (the ratio of early diastolic mitral inflow velocity to early diastolic mitral annular velocity) is widely used to measure left ventricular filling pressure (LVFP), its accuracy is questionable in coronary artery disease patients. METHODS AND RESULTS: Echocardiograms and LVFP were obtained from 174 patients with stable angina (Canadian Cardiovascular Society angina grade I-II) who had received interventions for angiography-confirmed coronary stenosis. Compared with single-vessel groups, the multiple-vessel group exhibited lower mitral annular velocities, higher LVFP, and stronger correlations between E/regional e' and LVFP. Additionally, stronger correlations between E/regional e' and LVFP existed in patients with systolic dysfunction or lower variation of myocardial performance index (MPI) among anterior, inferior and lateral borders of mitral annulus. Average e' was not superior to any regional e' for assessing LVFP by the E/e' method. E/e' and left atrial (LA) ejection fraction (EF) correlated linearly with LVFP, but the correlation between LA distensibility and LVFP was logarithmical. Compared with E/e', LA distensibility and LAEF were superior for identifying high LVFP. CONCLUSIONS: E/e' is not completely satisfactory for assessing LVFP in patients with stable angina, especially those with single-vessel disease, preserved systolic function or high MPI variation. For identifying high LVFP, LA distensibility and LAEF are better than E/e'.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".