December 13, 2023JACC Heart Failure
A Phenomapping Tool and Clinical Score to Identify Low Diuretic Efficiency in Acute Decompensated Heart Failure
Key result
BAN-ADHF score accurately predicts poor diuretic efficiency in ADHF with a C-index of ~0.92.
- C-index 0.92
- P<0.001
- n=794
Why the study?
Strategies for the early identification of low diuretic efficiency in acute decompensated heart failure to inform decongestion therapies are lacking.
Does the BAN-ADHF score accurately identify low diuretic efficiency in patients with acute decompensated heart failure?
Study Design
Type
Observational (n=794)
Multicenter
Yes
Structured PICO
Does the BAN-ADHF score accurately identify low diuretic efficiency in patients with acute decompensated heart failure?
P
Population
794 patients with acute decompensated heart failure in a derivation cohort, with external validation in other pooled trials, to identify low diuretic efficiency.
E
Exposure
Machine learning-based phenomapping and integer-based diuresis score (BAN-ADHF score: blood urea nitrogen, creatinine, natriuretic peptide levels, atrial fibrillation, diastolic blood pressure, hypertension and home diuretic, and heart failure hospitalization)
C
Comparator
Measures of kidney function (creatinine or blood urea nitrogen), natriuretic peptide levels, or home diuretic dose
O
Outcome
Diuretic efficiency (urine output over the first 72 hours per total intravenous furosemide equivalent loop diuretic dose)surrogate
Main Result
Effect estimate: C-index 0.92
p-value: p=<0.001
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Key expert perspectives
Captured external expert commentary on this paper, strongest first. Original sources are linked where available.
“Inefficient diuretic response in hospitalized patients can hinder treatment progress and increase the risk of post-discharge rehospitalization and mortality. It's crucial to identify individuals with low diuretic efficiency early on to tailor decongestion strategies and improve clinical outcomes.”
“Today, a primary goal of treating ADHF is to relieve congestion using loop diuretic drugs. However, there is still uncertainty about the best dose of these agents to administer. Additionally, because of the heterogeneity of ADHF patients, a more personalized approach to predicting optimal dosing strategies is needed.”
Implication
The BAN-ADHF score is a highly discriminative, validated clinical tool for identifying patients with acute decompensated heart failure who have low diuretic efficiency and are at higher risk for prolonged hospitalization and in-hospital mortality.
Abstract
BACKGROUND: Individuals with acute decompensated heart failure (ADHF) have a varying response to diuretic therapy. Strategies for the early identification of low diuretic efficiency to inform decongestion therapies are lacking. OBJECTIVES: The authors sought to develop and externally validate a machine learning-based phenomapping approach and integer-based diuresis score to identify patients with low diuretic efficiency. METHODS: Participants with ADHF from ROSE-AHF, CARRESS-HF, and ATHENA-HF were pooled in the derivation cohort (n = 794). Multivariable finite-mixture model-based phenomapping was performed to identify phenogroups based on diuretic efficiency (urine output over the first 72 hours per total intravenous furosemide equivalent loop diuretic dose). Phenogroups were externally validated in other pooled ADHF trials (DOSE/ESCAPE). An integer-based diuresis score (BAN-ADHF score: blood urea nitrogen, creatinine, natriuretic peptide levels, atrial fibrillation, diastolic blood pressure, hypertension and home diuretic, and heart failure hospitalization) was developed and validated based on predictors of the diuretic efficiency phenogroups to estimate the probability of low diuretic efficiency using the pooled ADHF trials described earlier. The associations of the BAN-ADHF score with markers and symptoms of congestion, length of stay, in-hospital mortality, and global well-being were assessed using adjusted regression models. RESULTS: Clustering identified 3 phenogroups based on diuretic efficiency: phenogroup 1 (n = 370; 47%) had lower diuretic efficiency (median: 13.1 mL/mg; Q1-Q3: 7.7-19.4 mL/mg) than phenogroups 2 (n = 290; 37%) and 3 (n = 134; 17%) (median: 17.8 mL/mg; Q1-Q3: 10.8-26.1 mL/mg and median: 35.3 mL/mg; Q1-Q3: 17.5-49.0 mL/mg, respectively) (P < 0.001). The median urine output difference in response to 80 mg intravenous twice-daily furosemide between the lowest and highest diuretic efficiency group (phenogroup 1 vs 3) was 3,520 mL/d. The BAN-ADHF score demonstrated good model performance for predicting the lowest diuretic efficiency phenogroup membership (C-index: 0.92 in DOSE/ESCAPE validation cohort) that was superior to measures of kidney function (creatinine or blood urea nitrogen), natriuretic peptide levels, or home diuretic dose (DeLong P < 0.001 for all). Net urine output in response to 80 mg intravenous twice-daily furosemide among patients with a low vs high (5 vs 20) BAN-ADHF score was 2,650 vs 660 mL per 24 hours, respectively. Participants with higher BAN-ADHF scores had significantly lower global well-being, higher natriuretic peptide levels on discharge, a longer in-hospital stay, and a higher risk of in-hospital mortality in both derivation and validation cohorts. CONCLUSIONS: The authors developed and validated a phenomapping strategy and diuresis score for individuals with ADHF and differential response to diuretic therapy, which was associated with length of stay and mortality.
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Cite This Study
Segar et al. (2023) conducted an observational in Acute decompensated heart failure (n=794). BAN-ADHF score vs. Measures of kidney function, natriuretic peptide levels, or home diuretic dose was evaluated on Lowest diuretic efficiency phenogroup membership (C-index 0.92, p=<0.001). The BAN-ADHF score accurately predicted the lowest diuretic efficiency phenogroup in patients with acute decompensated heart failure (C-index 0.92, P<0.001 vs other measures).