Speckle Strain Echocardiography Predicts Outcome in Patients with Heart Failure with both Depressed and Preserved Left Ventricular Ejection Fraction
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Bibliographic record
Abstract
BACKGROUND: While speckle imaging has been shown to predict outcome in patients with heart failure (HF), it remains unclear whether speckle strain predicts outcome in patients with HF with preserved ejection fraction (HFPEF). METHODS: Four hundred twenty patients with HF by Framingham criteria and either: left ventricular (LV) EF <50%, or elevated LV filling pressure by comprehensive echo Doppler study in the setting of left ventricular ejection fraction (LVEF) ≥50%, were enrolled. Speckle tracking was used to measure strain and strain rate in multiple vectors. The primary endpoint was HF hospitalization or cardiovascular death. RESULTS: Follow-up was completed in 380/420 patients (90%). The mean age was 55.7 ± 0.8 years, 191/380 (50%) were male, 319/380 (84%) were hypertensive, 183/380 (48%) were diabetic, and 152/380 (40%) had known coronary artery disease. At a mean follow-up of 369 ± 30 days, 107/380 patients (28%) reached the primary endpoint: 97 HF rehospitalizations and 10 cardiac deaths. The best univariate predictors of outcome were global longitudinal peak strain (GLPS) (χ(2) = 25.6, P < 0.001), mitral DT (χ(2) = 16.8, P < 0.001), LVEF (χ(2) = 16.7, P < 0.0001), longitudinal early diastolic strain (χ(2) = 8.7, P = 0.003), and circumferential peak strain (χ(2) = 7.9, P = 0.005). On multivariate analysis, GLPS (P < 0.0001), LVEF (P = 0.0002), and mitral DT (P = 0.005) were independent predictors of outcome. In the 100 HF patients with preserved LVEF, there were 17 events. Patients with GPLS ≤-15 had significantly better event-free survival than patients with GPLS >-15 (χ(2) = 4.1, P = 0.04), whereas LVEF did not predict event-free survival. CONCLUSION: Speckle strain echocardiography is an important predictor of outcome in HF patients with both depressed and preserved LVEF.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
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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 it