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已发表论文
中性粒细胞-血小板比值（NPR）结合机器学习预测急性缺血性卒中机械取栓后早期死亡
Authors Xia S , Hu J, Wu J, Liao Y, Liang G, Li J, Fan X, Xia X, Zhong X, Chen L
Received 11 September 2025
Accepted for publication 16 December 2025
Published 19 January 2026 Volume 2026:19 563668
DOI https://doi.org/10.2147/JIR.S563668
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Professor Ning Quan
Shaohuai Xia,1,* Junhong Hu,2,* Jing Wu,1 Yingye Liao,2 Guifeng Liang,3 Jinping Li,4 Xiaoguang Fan,2 Xuewei Xia,2 Xinrong Zhong,2 Li Chen5
1Department of Neuro-Oncology, Beijing Xiaotangshan Hospital, Beijing, 100000, People’s Republic of China; 2Department of Neurosurgery, The First Affiliated Hospital of Guilin Medical University, Guilin, Guangxi, 541001, People’s Republic of China; 3Diecai District Maternal and Child Health Hospital of Guilin City, Guilin, Guangxi, 541001, People’s Republic of China; 4Reproductive Center of The 924th Hospital of The Joint Logistic Support Force of The Chinese People’s Liberation Army, Guilin, Guangxi, 541001, People’s Republic of China; 5Department of Neurosurgery, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Affiliated Provincial Hospital of Fuzhou University, Fuzhou, 350001, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Li Chen, Department of Neurosurgery, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Affiliated Provincial Hospital of Fuzhou University, Fuzhou, 350001, People’s Republic of China, Email fjmuchenli@163.com
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 (< 15%) were imputed. Boruta feature selection identified variables for multiple logistic regression. The dataset was randomly divided into training and test sets (7:3). A nomogram was constructed, and four machine learning algorithms—Decision Tree (DT), Extreme Gradient Boosting (XGBoost), Support Vector Machine (SVM), and Naive Bayes (NB)—were developed and validated.
Results: Early mortality occurred in 67 cases. Multivariate analysis identified six independent predictors: standardized NPR (NPR_std; OR = 4.51, P < 0.001), age (OR = 1.10, P < 0.001), decompressive craniectomy (DC; OR = 0.19, P < 0.001), responsible artery location (OR = 0.34, P = 0.006), lymphocyte count (LYM; OR = 2.14, P = 0.008), and prothrombin time (PT; OR = 1.31, P = 0.011). The nomogram showed high reliability. XGBoost achieved superior predictive performance, with SHapley Additive exPlanations (SHAP) analysis confirming NPR_std as the most important predictor.
Conclusion: The neutrophil-to-platelet ratio (NPR) is an independent predictor of early mortality after MT in LAO-AIS patients. The predictive model provides valuable guidance for clinicians to adjust treatment strategies early.
Keywords: stroke, mechanical thrombectomy, prognosis, early mortality, neutrophil-to-platelet ratio
1Department of Neuro-Oncology, Beijing Xiaotangshan Hospital, Beijing, 100000, People’s Republic of China; 2Department of Neurosurgery, The First Affiliated Hospital of Guilin Medical University, Guilin, Guangxi, 541001, People’s Republic of China; 3Diecai District Maternal and Child Health Hospital of Guilin City, Guilin, Guangxi, 541001, People’s Republic of China; 4Reproductive Center of The 924th Hospital of The Joint Logistic Support Force of The Chinese People’s Liberation Army, Guilin, Guangxi, 541001, People’s Republic of China; 5Department of Neurosurgery, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Affiliated Provincial Hospital of Fuzhou University, Fuzhou, 350001, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Li Chen, Department of Neurosurgery, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Affiliated Provincial Hospital of Fuzhou University, Fuzhou, 350001, People’s Republic of China, Email fjmuchenli@163.com
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 (< 15%) were imputed. Boruta feature selection identified variables for multiple logistic regression. The dataset was randomly divided into training and test sets (7:3). A nomogram was constructed, and four machine learning algorithms—Decision Tree (DT), Extreme Gradient Boosting (XGBoost), Support Vector Machine (SVM), and Naive Bayes (NB)—were developed and validated.
Results: Early mortality occurred in 67 cases. Multivariate analysis identified six independent predictors: standardized NPR (NPR_std; OR = 4.51, P < 0.001), age (OR = 1.10, P < 0.001), decompressive craniectomy (DC; OR = 0.19, P < 0.001), responsible artery location (OR = 0.34, P = 0.006), lymphocyte count (LYM; OR = 2.14, P = 0.008), and prothrombin time (PT; OR = 1.31, P = 0.011). The nomogram showed high reliability. XGBoost achieved superior predictive performance, with SHapley Additive exPlanations (SHAP) analysis confirming NPR_std as the most important predictor.
Conclusion: The neutrophil-to-platelet ratio (NPR) is an independent predictor of early mortality after MT in LAO-AIS patients. The predictive model provides valuable guidance for clinicians to adjust treatment strategies early.
Keywords: stroke, mechanical thrombectomy, prognosis, early mortality, neutrophil-to-platelet ratio