Effects of Liraglutide on Worsening Renal Function Among Patients With Heart Failure With Reduced Ejection Fraction
Bibliographic record
Abstract
BACKGROUND: The FIGHT (Functional Impact of GLP-1 [glucagon-like peptide-1] for Heart Failure Treatment) trial randomized 300 patients with heart failure with reduced ejection fraction (HFrEF) and a recent hospitalization for heart failure to liraglutide versus placebo. While there was no difference in the primary outcome (rank score of time to death, time to rehospitalization for heart failure, and change in NT-proBNP [N-terminal pro-B-type natriuretic peptide]), there was a significant increase in cystatin C among patients randomized to liraglutide raising concern of adverse renal outcomes. We performed a post hoc analysis of FIGHT to investigate whether liraglutide was associated with worsening renal function (WRF). METHODS: The relationship between randomization to liraglutide and WRF was evaluated using logistic regression models. Two hundred seventy-four patients (91%) had complete data to assess for WRF defined as: increase in SCr ≥0.3 mg/dL, or ≥25% decrease in estimated glomerular filtration rate, or an increase in cystatin C ≥0.3 mg/L from baseline to 180-days. RESULTS: Patients with WRF (n=113, 41%), compared with those without, were older, had more comorbidities, and lower utilization of guideline-directed medical treatment. Logistic regression models showed that age and baseline cystatin C levels were associated with WRF. In adjusted models, liraglutide was not associated with excess risk of WRF compared with placebo (odds ratio, 1.02 [95% CI, 0.62-1.67]). There was also no difference in the rank score when WRF was added as a fourth-tier outcome. CONCLUSIONS: Liraglutide was not associated with WRF among patients with HFrEF and a recent hospitalization for heart failure. These data support the relative renal safety profile of liraglutide among patients with HFrEF. Registration: URL: http://www.clinicaltrials.gov. Unique identifier: NCT01800968.
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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 | 0.001 |
| 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".