Risk stratification in patients with heart failure: the value of considering both global longitudinal left ventricular strain and mechanical dispersion
Bibliographic record
Abstract
In previous studies, mechanical dispersion (MD) predicted ventricular arrhythmias independently of left ventricular ejection fraction (LVEF). Moreover, the combination of MD and global longitudinal strain (GLS) increased the prediction of arrhythmic events. We investigated the prognostic value of a new 2-dimensional strain index, GLS/MD, in patients with heart failure (HF). We analyzed 340 consecutive HF outpatients in sinus rhythm. Echocardiography was performed at 1.6 ± 0.4 months after hospital discharge. The end point included sudden cardiac death, ventricular fibrillation, and sustained ventricular tachycardia (SCD/VA). During the follow-up period (36 ± 9 months), SCD/VA occurred in 48 patients (14.1%). A multivariate Cox regression analysis, which included LVEF, early diastolic transmitral / mitral annular velocity ratio (E/E'), GLS, MD, and GLS/MD in the model, revealed that GLS/MD was the best independent predictor of SCD/VA (HR = 3.22, 95% confidence interval = 1.72-6.15, p = 0.03). Separate inclusion of LVEF, systolic mitral annular velocity, E/E', GLS, and MD together with GLS/MD showed that GLS/MD remained the best predictor of SCD/VA (each p < 0.05). The optimal GLS/MD cutoff value to predict SCA/VA was -0.20%/ms (80% sensitivity, 76% specificity). Irrespective of LVEF, free survival was significantly better in patients with GLS/MD ≤ -0.2%/ms (log-rank test, p < 0.001). In conclusion, GLS/MD may improve cardiovascular risk stratification in subjects with HF.
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How this classification was reachedexpand
Full frame distilled prediction
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 | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".