Comparative Performance of Risk Prediction Indices for Mortality or Readmission Following Heart Failure Hospitalization
Bibliographic record
Abstract
AIMS: Risk prediction indices used in worsening heart failure (HF) vary in complexity, performance, and the type of datasets in which they were validated. We compared the performance of seven risk prediction indices in a contemporary cohort of patients hospitalized for HF. METHODS AND RESULTS: We assessed the performance of the Length of stay and number of Emergency department visits in the prior 6 months (LE), Length of stay, number of Emergency department visits in the prior 6 months, and admission N-Terminal prohormone of brain natriuretic peptide (NT-proBNP (LENT), Length of stay, Acuity, Charlson co-morbidity index, and number of Emergency department visits in the prior 6 months (LACE), Get With The Guidelines Heart Failure (GWTG), Readmission Risk Score (RRS), Enhanced Feedback for Effective Cardiac Treatment model (EFFECT), and Acute Decompensated Heart Failure National Registry (ADHERE) risk indices among consecutive patients hospitalized for HF and discharged alive from January 2017 to December 2019 in a network of hospitals in England. The primary composite outcome was 30-day all-cause mortality or readmission. We assessed model discrimination and overall accuracy using the C-statistic (higher values, better) and Brier score (lower values, better), respectively. Among 1206 patients in the cohort, 45.0% were female, mean (SD) age was 76.6 (11.7) years, and mean (SD) left ventricular ejection fraction was 43.0% (11.6). At 30 days, 236 (19.6%) patients were readmitted and 28 (2.3%) patients died, with 264 (21.9%) patients experiencing either readmission or death. The LENT index offered the combination of greatest risk discrimination and accuracy for the primary composite outcome (C-statistic: 0.97; 95% CI 0.96, 0.98; 0.29; Brier score: 0.05). The LE (C-statistic: 0.95; 95% CI 0.93, 0.96; Brier score: 0.06) and LACE (C-statistic: 0.90; 95% CI 0.88, 0.92; Brier score 0.09) indices had high discrimination and accuracy. Discrimination and accuracy were modest with the RRS (C-statistic: 0.65; 95% CI 0.61, 0.69; Brier score: 0.16) and EFFECT (C-statistic: 0.64; 95% CI 0.60, 0.67; Brier score: 0.16) score; and poor with the GWTG-HF (C-statistic: 0.62; 95% CI 0.58, 0.66; Brier score: 0.17) and ADHERE (C-statistic: 0.54; 95% CI 0.50, 0.57; Brier score: 0.17) scores. CONCLUSIONS: In a study that compared the performance of seven risk prediction indices in a contemporary cohort of patients hospitalized for HF, the simple LENT index offered the greatest combination of discrimination and accuracy for the primary composite outcome of 30-day all-cause mortality or readmission. This three-variable index -using length of hospital stay, preceding emergency department visits and admission NT-proBNP level- is a practical and reliable way to assess prognosis following hospitalization for HF.
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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) | 0.001 | 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".