Utilizing Quality of Life Adjusted Days Alive and Out of Hospital in Heart Failure Clinical Trials
Bibliographic record
Abstract
BACKGROUND: In heart failure (HF) trials, there has been an emphasis on utilizing more patient-centered outcomes, including quality of life (QoL) and days alive and out of hospital. We aimed to explore the impact of QoL adjusted days alive and out of hospital as an outcome in 2 HF clinical trials. METHODS: Using data from 2 trials in HF (Guiding Evidence Based Therapy Using Biomarker Intensified Treatment in Heart Failure [GUIDE-IT] and Study of Dietary Intervention under 100 mmol in Heart Failure [SODIUM-HF]), we determined treatment differences using percentage days alive and out of hospital (%DAOH) adjusted for QoL at 18 months as the primary outcome. For each participant, %DAOH was calculated as a ratio between days alive and out of hospital/total follow-up. Using a regression model, %DAOH was subsequently adjusted for QoL measured by the Kansas City Cardiomyopathy Questionnaire Overall Summary Score. RESULTS: In the GUIDE-IT trial, 847 participants had a median baseline Kansas City Cardiomyopathy Questionnaire Overall Summary Score of 59.0 (interquartile range, 40.8-74.3), which did not change over 18 months. %DAOH was 90.76%±22.09% in the biomarker-guided arm and 88.56%±25.27% in the usual care arm. No significant difference in QoL adjusted %DAOH was observed (1.09% [95% CI, -1.57% to 3.97%]). In the SODIUM-HF trial, 796 participants had a median baseline Kansas City Cardiomyopathy Questionnaire Overall Summary Score of 69.8 (interquartile range, 49.3-84.3), which did not change over 18 months. %DAOH was 95.69%±16.31% in the low-sodium arm and 95.95%±14.76% in the usual care arm. No significant difference was observed (1.91% [95% CI, -0.85% to 4.77%]). CONCLUSIONS: In 2 large HF clinical trials, adjusting %DAOH for QoL was feasible and may provide complementary information on treatment effects in clinical trials.
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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 | 0.188 | 0.172 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.011 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".