Longitudinal Changes in Diastolic Dysfunction in Heart Failure with Reduced Ejection Fraction: Clinical and Echocardiographic Associations
Bibliographic record
Abstract
Background Diastolic dysfunction (DD) in heart failure with reduced ejection fraction (HFrEF) is relatively understudied, particularly regarding longitudinal changes in DD after HFrEF diagnosis and their clinical and echocardiographic associations. Methods This retrospective study included 360 patients with HFrEF who visited heart failure (HF) clinics in King Salman Heart Center, Riyadh, Saudi Arabia, between October 2019 and January 2020. Associations between DD grades and patients' clinical characteristics and echocardiographic parameters at diagnosis and during follow-up were evaluated. Results At diagnosis, left ventricular ejection fraction (LVEF) was 26.7% ( ± 7.2%), and 43.1%, 29.4%, and 27.5% of patients had grade III, II, and I DD, respectively. After 3.4 years, 65% and 57.5% of patients with grades III and II DD, respectively, improved by at least one grade. Concordant improvements in almost all diastolic parameters were observed. DD grade improvement was predicted by increased LVEF ( P < 0.001), nonischemic HF etiology, and absence of myocardial infarction ( P < 0.001). No associations were found with HF medications or cardiovascular risk factors. DD improvement was independently associated with improved New York Heart Association class ( P = 0.008), lower B-type natriuretic peptide level ( P < 0.001), and higher systolic blood pressure ( P < 0.001), regardless of LVEF, age, and time since diagnosis. Conclusions In HFrEF, DD improves with better LVEF and absence of ischemia or infarction. DD improvement is independently associated with improved New York Heart Association class, systolic blood pressure, and B-type natriuretic peptide level, suggesting that in HFrEF, diastolic HF coexists with and parallels systolic HF severity, and contributes independently to symptoms and hemodynamics.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".