Pan-immune-inflammation value predicts in-hospital mortality in patients with acute ischemic stroke admitted to the intensive care units
10.3760/cma.j.issn.1673-4165.2023.10.003
- VernacularTitle:泛免疫炎症值预测收住重症监护病房的急性缺血性卒中患者的院内死亡
- Author:
Xiaoqin WANG
1
;
Manxia WANG
;
Jinping WANG
;
Huihui CUI
;
Zitong XU
Author Information
1. 兰州大学第二临床医学院，兰州 730000
- Keywords:
Ischemic stroke;
Intensive care units;
Hospital mortality;
Inflammation;
Leukocyte count;
Lymphocyte count;
Platelet count;
Predictive value of tests
- From:
International Journal of Cerebrovascular Diseases
2023;31(10):736-743
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the predictive value of pan-immune-inflammation value (PIV) for in-hospital mortality in patients with acute ischemic stroke (AIS) admitted to intensive care unit (ICU).Methods:The clinical data of the first-ever AIS patients admitted to the ICU in the Medical Information Mart for Intensive Care (MIMIC) -Ⅳ of the United States were retrospectively included and analyzed. According to whether the patients died in the hospital, they were divided into a survival group and a death group, and the differences in baseline data between the two groups were compared. Multivariate logistic regression model was used to analyze independent influencing factors of in-hospital mortality in patients. Receiver operating characteristic curve was used to evaluate the predictive value of PIV on in-hospital mortality. Results:A total of 1 068 first-ever AIS patients admitted to the ICU were included, with a median age of 69 years. There were 543 males (50.84%), and 182 (17.05%) experienced in-hospital mortality. Multivariate logistic regression analysis showed that after adjusting for potential confounding factors, a higher PIV (>1 555.71) was an independent risk factor for in-hospital mortality in patients (odds ratio 1.924, 95% confidence interval 1.093-3.387; P=0.023). The receiver operating characteristic curve analysis showed that the area under the curve for predicting in-hospital mortality by PIV was 0.605 (95% confidence interval 0.556-0.654), with an optimal cutoff value of 1 199.93. The sensitivity and specificity for predicting in-hospital mortality were 48.9% and 70.2%, respectively. Conclusions:A higher PIV is an independent risk factor for in-hospital mortality in AIS patients admitted to ICU, which may help identify AIS patients with a higher risk of in-hospital mortality in the ICU.
