Risk stratification for heart transplant listing or death in patients with heart failure profile C - a classification and regression tree CART analysis
Bibliographic record
Abstract
Abstract Introduction Estimating prognostic risk in acute heart failure (HF) is crucial for guiding clinical decision-making, especially in patients receiving inotropic support who may require heart transplantation (HT). Exhaled Breath Acetone (EBA), a biomarker of prognosis that reflects metabolic changes in HF, could be useful in risk assessment for this population. Objective To develop a practical bedside tool to predict the need for listing for HT or the risk of death in patients admitted to emergency room in acute decompensated HF (ADHF) hemodynamic C profile. Methods This was a prospective, observational, single-center study. We used the classification and regression tree (CART) methodology to identify the strongest predictors of listing for HT or death within six months. A total of six variables, previously analyzed using the Cox proportional hazards model, were tested for inclusion in the CART model, and the cutoff point was determined using the ROC curve. Final models were developed and adjusted to ensure that at least 10% of the sample was included in each branch. Results Between January 2019 and August 2023, 276 patients were included. Most patients were male (67%), with mean age of 55 (±13) years-old. The mean left ventricle ejection fraction (LVEF) was 25(±5)%, and the most prevalent etiologies were idiopathic (30%), Chagas disease (20%), and ischemic heart disease (20%) (table 1). Listing for HT or death was observed in 59% of the cohort. The variables included and their respective cutoff values were B-Type Natriuretic Peptide (BNP) (2214 pg/mL), sodium (137.5 mmol/L), LVEF (24.5%), creatinine (2.1 mg/dL), and EBA (4.3 µg/L) at admission. The risk ranged from 38% to 61% in patients with BNP levels below the cutoff, depending on LVEF and creatinine values. However, when BNP levels were higher than the cutoff, the risk varied according to sodium and EBA levels. BNP >2214 pg/mL and sodium < or = 137.5 mmol/L resulted in the highest risk in the cohort (89%). However, when high levels of BNP were associated with sodium levels >137.5 mmol/L, the risk varied according to EBA levels: 38% if EBA< or =4.3 µg/L and 75% if EBA>4.3 µg/L (Figure 1). Conclusion Our findings confirmed that HF patients receiving inotropic support are at high risk of being listed for HT or progressing to death and can be identified using laboratory and echocardiographic data obtained at admission. In this cohort, EBA provided additional prognostic value to known predictors. The risk tree offers a practical bedside tool for severity stratification in HF patients in hemodynamic profile C. These results can be used in the future for validation in other populations.Risk tree for HF patients C profile Baseline
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".