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Published on: June 10, 2025
Association of the Neutrophil Percentage-to-Albumin Ratio with All-Cause Mortality in Patients with Heart Failure: A
Dhruvil Patel1, Sankalp Acharya2, Sanket Patel3
1From the Department of Internal Medicine, Trinity Health Oakland/Wayne State University, Pontiac, MI.
Abstract:
Heart failure is characterized by complex interactions between systemic inflammation and impaired nutritional status, both of which contribute to adverse clinical outcomes. The neutrophil percentage-to-albumin ratio (NPAR), derived from routinely available laboratory parameters, integrates these pathways; however, its prognostic significance in heart failure has not been systematically evaluated. We conducted a systematic review and meta-analysis to examine the association between baseline NPAR and all-cause mortality in adult patients with heart failure. A comprehensive search of PubMed, Embase, Web of Science, and Cochrane Central was performed to identify relevant studies. Pooled hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated using a random-effects model. Dose-response, sensitivity, and publication bias analyses were conducted, and risk of bias was assessed using the Quality in Prognosis Studies tool. Seven studies comprising 11,543 patients were included. Higher baseline NPAR was significantly associated with increased all-cause mortality (HR, 1.65; 95% CI, 1.44-1.90; P < 0.001), with moderate heterogeneity (I2 = 59%). A graded dose-response relationship was observed, with progressively higher mortality risk across increasing NPAR categories (P for trend < 0.001). Results remained robust in sensitivity analyses, with no evidence of significant publication bias (Egger P = 0.11). Certainty of evidence was rated as moderate using Grading of Recommendations Assessment, Development and Evaluation criteria. In conclusion, elevated NPAR is associated with increased mortality risk in heart failure. As a zero-cost biomarker derived from routine admission laboratories, NPAR captures the inflammation-malnutrition axis and may complement existing risk stratification frameworks, particularly in resource-limited settings.
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