Heterogeneity in Treatment Effects in the Reduction of Dietary Sodium to Less Than 100 mmol in Heart Failure (SODIUM-HF): A Secondary Post Hoc Analysis
Bibliographic record
Abstract
BACKGROUND: SODIUM-HF (Study of Dietary Intervention of Sodium Under100 mmol in Heart Failure) compared usual care with dietary sodium restriction in patients with heart failure (HF) and produced neutral results for the primary endpoint. Heterogeneity in treatment effects (HTE) analysis could enhance the original findings. OBJECTIVE: Explore the presence of HTE in the SODIUM-HF trial using a risk-effect-based approach. METHODS: HTE was assessed using a risk-based approach based on the Meta-Analysis Global Group in Chronic (MAGGIC) HF risk score. Interaction between MAGGIC quartiles and outcomes was assessed using a Bayesian regression model with neutral priors. The primary endpoint was the same for the original trial (composite of cardiovascular-related admission to hospital, cardiovascular-related emergency department visit, or all-cause death within 12 months in the intention-to-treat population); KCCQ was the secondary endpoint. RESULTS: Were included 806 patients. MAGGIC quartiles used for the risk-based analyses were 0.036 to 0.102 (low), >0.102 to 0.147 (medium-low), >0.147 to 0.209 (medium-high), and >0.209 to 0.591 (high). There was very strong evidence for the interaction between MAGGIC quartile and intervention (Bayes factor of 68). There was a strong suggestion of association between intervention arm and a lower occurrence of the primary endpoint for the medium-low MAGGIC quartile (>0.98 probability), and a suggestion that the intervention was associated with more frequent occurrence of the primary endpoint in the high MAGGIC quartile (probability of benefit of 0.06). Suggestion of HTE was also found for KCCQ with a strong suggestion of benefit for the intervention for those in the lowest MAGGIC quartiles. CONCLUSIONS: HTE effects in the SODIUM-HF trial is probable. Further trials in sodium retention may benefit by incorporating this information.
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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 | 0.045 | 0.092 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.032 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.021 | 0.001 |
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".