First-Trimester Neutrophil Percentage-to-Albumin Ratio Adds Meaningful Additive Prognostic Utility for Early-Onset...

Background: Early-onset preeclampsia (EO-PE) remains a major cause of maternal and perinatal morbidity and mortality, and early risk stratification is still limited by the lack of simple and widely accessible biomarkers. The neutrophil percentage-to-albumin ratio (NPAR) has emerged as a composite marker reflecting systemic inflammation and endothelial dysfunction. Methods: In this retrospective, nested case-control study (n = 1176), we evaluated the predictive performance of first-trimester NPAR for EO-PE (n = 168) versus frequency-matched normotensive controls (n = 840) and its incremental value beyond established clinical and hemodynamic parameters. Multivariable models were adjusted for gestational age at sampling, and internal validation was performed via bootstrapping. Results: NPAR demonstrated superior discrimination (AUC = 0.848) compared with NLR (AUC = 0.629) and MAP (AUC = 0.614) (p < 0.001 for both). At the optimal cutoff of 16.52, NPAR showed a sensitivity of 81.5% (95% CI: 74.8-87.1%) and a specificity of 76.0% (95% CI: 72.9-78.9%), yielding a prevalence-adjusted positive predictive value (PPV) of 6.5% and a negative predictive value (NPV) of 99.5% based on Bayes' Theorem. In multivariable analysis, NPAR remained independently associated with EO-PE (aOR 2.25, 95% CI 1.81-2.80; p < 0.001, per 1 SD increase). The addition of NPAR significantly improved model performance, increasing the AUC from 0.612 to 0.830 (DeLong p < 0.001), with robust bootstrap stability. Conclusions: First-trimester NPAR stands out as a potential independent clinical risk vector for early-onset preeclampsia and may offer meaningful additive prognostic utility beyond conventional clinical parameters. Given its low cost and routine availability, it may represent an accessible framework for initial frontline triage in early pregnancy risk stratification, particularly in resource-limited clinical settings where advanced multi-marker screening algorithms are unavailable. Rigorous external validation in prospective, multicenter longitudinal cohorts remains an absolute prerequisite before routine implementation in clinical management pathways.