Early Detection of Heart Failure in Primary Care: Evaluating a Frailty–BNP Screening Pathway for Improved Outcomes

Abstract

An estimated 64-million people suffer from heart failure; a significant global burden with an annual mortality rate of 10%. Even with advancements in treatment, individuals go from ventricular dysfunction to overt heart failure asymptomatically, making late detection a barrier to best possible outcomes. A primary-care approach for detecting early cardiac dysfunction prior to symptomatic deterioration is to combine frailty assessment with B-type natriuretic peptide or N-terminal proBNP screening.  The purpose of this research was to ascertain whether combining frailty assessment with BNP or NT-proBNP testing could improve early diagnosis of heart failure and lower hospitalization rates in primary-care.

 Following PRISMA-Narrative guidelines, this research synthesized data published from 2020-2025 in PubMed, Scopus, and Google Scholar. The diagnostic accuracy, predictive value, hospitalization, and system viability of studies using frailty indices (Clinical Frailty Scale, Fried Phenotype, Edmonton Frail Scale) and BNP/NT-proBNP tests were evaluated. The results were placed within preventive frameworks of the ESC (2023) and AHA (2025).

A 2.3-fold increase in hospitalizations and 1.8-fold increase in death were associated with frailty prevalence in preclinical or early HF, which varied from 25 to 35%.  For asymptomatic LV dysfunction, BNP and NT-proBNP demonstrated a combined diagnostic sensitivity of 90% and specificity of 85% (AUC 0.88–0.93).  The shift to symptomatic HF was predicted by thresholds of BNP ≥ 35 pg/mL or NT-proBNP ≥ 125 pg/mL. Integrated frailty plus BNP pathways reduced unnecessary echocardiography by 20–25%, shortened time-to-diagnosis by 4–6 weeks, and increased new HF detection by about three times within a year. 

A statistically verified approach for early HF detection in primary care is provided by combining frailty screening with natriuretic-peptide testing. This strategy improves diagnostic accuracy, speeds up intervention, and lessens strain on hospitals. To verify long-term scalability and policy impact, extensive multicenter validation and global health-economic modeling is necessary.