Effect of Sotagliflozin on Early Mortality and Heart Failure-Related Events
Bibliographic record
Abstract
BACKGROUND: Approximately 25% of patients admitted to hospitals for worsening heart failure (WHF) are readmitted within 30 days. OBJECTIVES: The authors conducted a post hoc analysis of the SOLOIST-WHF (Effect of Sotagliflozin on Cardiovascular Events in Patients With Type 2 Diabetes Post-WHF) trial to evaluate the efficacy of sotagliflozin versus placebo to decrease mortality and HF-related events among patients who began study treatment on or before discharge from their index hospitalization. METHODS: The main endpoint of interest was cardiovascular death or HF-related event (HF hospitalization or urgent care visit) occurring within 90 and 30 days after discharge for the index WHF hospitalization. Treatment comparisons were by proportional hazards models, generating HRs, 95% CIs, and P values. RESULTS: Of 1,222 randomized patients, 596 received study drug on or before their date of discharge. Sotagliflozin reduced the main endpoint at 90 days after discharge (HR: 0.54 [95% CI: 0.35-0.82]; P = 0.004) and at 30 days (HR: 0.49 [95% CI: 0.27-0.91]; P = 0.023) and all-cause mortality at 90 days (HR: 0.39 [95% CI: 0.17-0.88]; P = 0.024). In subgroup analyses, sotagliflozin reduced the 90-day main endpoint regardless of sex, age, estimated glomerular filtration rate, N-terminal pro-B-type natriuretic peptide, left ventricular ejection fraction, or mineralocorticoid receptor agonist use. Sotagliflozin was well-tolerated but with slightly higher rates of diarrhea and volume-related events than placebo. CONCLUSIONS: Starting sotagliflozin before discharge in patients with type 2 diabetes hospitalized for WHF significantly decreased cardiovascular deaths and HF events through 30 and 90 days after discharge, emphasizing the importance of beginning sodium glucose cotransporter treatment before discharge.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".