Jiayu Tian, Ivonne Cabrera, Chukwuebuka Ojukwu, Nicholas Harrison

Derivation of a Multivariable Model to Assist Emergency Department Triage of Heart Failure Patients by Their Diuretic Treatment Needs

Introduction

Derivation of a multivariable model to assist emergency department triage of heart failure patients by their diuretic treatment needs. Novel model aids ED triage of heart failure patients by accurately predicting diuretic treatment needs. Improves disposition decisions, potentially reducing unnecessary hospitalizations significantly.

Abstract

Background: Emergency medicine physicians (EMP) treat 1 million patients with acute decompensated heart failure (ADHF) annually. After emergency department (ED) treatment, EMPs must determine the need for further intravenous loop diuretic (IVLD) therapy in dispositioning patients to home (no further IVLD treatment), short stay observation (≤24hrs treatment), or inpatient hospitalization (>48 hours treatment). We hypothesized that EMPs overestimate IVLD needs, resulting in unnecessary admission, and derived a multivariable prediction model to aid EMP decision making. Methods: We prospectively enrolled 63 patients with ADHF. The primary predicted outcome was the number of guideline-based doses of IVLD (1 dose = 1x home furosemide dose) received during the total acute care encounter. Variables available prior to ED disposition (labs, imaging, risk-scores, structured physical exam {edema, JVP, orthopnea grade, hepatojuglar reflux}, patient symptom scores) were used to derive a multivariable prediction model with linear regression. Control predictor models included A) ED physical exam + symptom score + natriuretic peptide (NP) and B) EMP disposition decision adjusted for risk of 30-day serious adverse events. Models were compared by adjusted R2. Results: EMPs admitted 57 patients for full hospitalization, 5 for observation, and did not discharge any patients directly after ED IVLD treatment. Total-encounter IVLD requirements were median 2.5 guideline-standardized doses (IQR:0.8-4.5). ED disposition was poorly correlated with post-ED treatment needs, explaining only 2.1% of variance in IVLD requirements (i.e. R2=0.021). Physical exam, symptom score, and NP explained 24.7% of IVLD requirements. The new model (predictors: NP, BUN, sodium, troponin, heart rate, blood pressure, chest x-ray, medication adherence, edema severity) explained 54.7% of IVLD requirements. Conclusion: EMPs may increase unnecessary hospitalizations by overestimating post-ED IVLD treatment needs. Our novel model, pending external validation in a new >5000 patient sample, was 26 times more accurate than risk-adjusted ED disposition and twice as accurate as physical exam/symptom score/NPs.

Review

This paper addresses a significant challenge in emergency medicine: accurately triaging patients with acute decompensated heart failure (ADHF) based on their need for ongoing intravenous loop diuretic (IVLD) therapy. The authors effectively highlight the clinical problem, positing that emergency medicine physicians (EMPs) may overestimate diuretic needs, leading to unnecessary hospital admissions for patients who could be managed in observation or even discharged home. The stated objective to derive a multivariable prediction model to improve this decision-making process is highly relevant, given the substantial number of ADHF patients seen annually in emergency departments. The methodology involved a prospective enrollment of 63 ADHF patients, with the primary outcome being the total number of guideline-based IVLD doses received during their acute care encounter. Using a range of pre-disposition variables, including labs, imaging, physical exam findings, and symptom scores, the study derived a linear regression model. The results demonstrate a clear need for improved decision support, as EMPs' current disposition decisions showed a very weak correlation with actual IVLD requirements (R2=0.021). While a model incorporating physical exam, symptom scores, and natriuretic peptides explained 24.7% of the variance, the novel model, integrating predictors such as NP, BUN, sodium, troponin, heart rate, blood pressure, chest x-ray, medication adherence, and edema severity, significantly improved predictive power, explaining 54.7% of the variance in IVLD requirements. While the findings are promising, indicating that the novel model is substantially more accurate than current practice and existing simpler models, the study's primary limitation is its small sample size of 63 patients. Deriving a multivariable model from such a limited cohort may lead to overfitting and limits the generalizability of the findings. The single-center nature of the study further compounds this concern. Nevertheless, the paper's strength lies in identifying a set of readily available clinical parameters that, when combined, offer a substantially improved prediction of post-ED diuretic needs. The authors appropriately acknowledge the critical next step of external validation in a much larger cohort (>5000 patients), which will be essential to confirm the robustness and clinical utility of this model in reducing unnecessary hospitalizations and optimizing patient care for ADHF patients.

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