AST/ALT ratio predicts the functional severity of chronic heart failure with reduced left ventricular ejection fraction
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: Despite previous research that focused on liver transaminases as predictors of cardiovascular disease, there has been limited research evaluating the predictive value of AST/ALT ratio in patients with heart failure. We aimed to investigate AST/ALT ratio as an indicator of the functional severity in chronic heart failure with reduced left ventricular ejection fraction. RESULTS: Overall, 105 patients previously diagnosed with HFrEF from Buraidah-Al Qassim province, Saudi Arabia were included in this retrospective cross-sectional study. Data on study variables, including demographic data, left ventricular ejection fraction, NYHA class, and AST/ALT ratio, were collected from patients' records. The patients were divided into two groups, namely group-1 (AST/ALT ratio < 1) and group-2 (AST/ALT ratio ≥ 1), to identify any differences in their cardiac function profiles. NYHA class and NT-proBNP were higher and LVEF was lower in group-2 than in group-1. We found a mild significant correlation between AST/ALT ratio and APRI, FIB-4 score, NYHA-class, and LVEF (r = 0.2, 0.25, 0.26, and - 0.24, respectively; P < 0.05). Multivariate linear regression analysis model and ROC curve showed that AST/ALT ratio could independently predict HFrEF functional severity with a best cut-off value of 0.9, sensitivity of 43.6%, and specificity of 81.4%.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.001 | 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 it