Development of the Neutrophil-to-Platelet Ratio (NPR) Integrated with Machine Learning for Predicting Early Mortality After Mechanical Thrombectomy in Acute Ischemic Stroke

Journal of Inflammation Research 2026 Open access

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Authors: Shaohuai Xia, Junhong Hu, Jing Wu, Yingye Liao, Guifeng Liang, Jinping Li, Xiaoguang Fan, Xuewei Xia, Xinrong Zhong, Li Chen
DOI: 10.2147/jir.s563668
Cited by: 0
References: 59

Abstract

Purpose: This study aimed to evaluate the predictive value of inflammatory markers, particularly the neutrophil-to-platelet ratio (NPR), combined with clinical parameters for early mortality following mechanical thrombectomy (MT) in patients with large artery occlusive acute ischemic stroke (LAO-AIS), to guide timely clinical interventions. Patients and methods: This retrospective study analyzed 320 LAO-AIS patients who underwent MT between January 2023 and January 2025. Missing data (

Fields of Study & Subjects

Acute Ischemic Stroke Management Inflammatory Biomarkers in Disease Prognosis Artificial Intelligence in Healthcare

Publication details

Journal / source
Journal of Inflammation Research
Volume
Volume 19
Pages
1–20
Publication date
1 January 2026
Language
EN