Wang Shuai, Zhang Wei, Li Jingjing, Yang Xinxin, Wang Yuqiao
Department of Neurology, The First Clinical Medical College of Xuzhou Medical University, Xuzhou, China.
Department of Neurology, Affiliated Hospital of Xuzhou Medical University, Xuzhou, China.
Front Neurol. 2025 Aug 12;16:1606436. doi: 10.3389/fneur.2025.1606436. eCollection 2025.
The aim of this study was to investigate the impact of the Pan-Immune-Inflammation Value (PIV) on the prognosis of spontaneous intracerebral hemorrhage (ICH) and to develop and validate a nomogram for identifying patients with a poor prognosis following ICH.
We retrospectively collected the clinical data of 742 patients with ICH admitted to the Affiliated Hospital of Xuzhou Medical University from September 2018 to March 2024. A modified Rankin Scale score > 3 at 90 days after discharge was defined as a poor short-term prognosis. The enrolled patients were randomly assigned to a training cohort and a validation cohort in a 7:3 ratio. In the training cohort, risk factors associated with poor short-term prognosis were identified through univariate and multivariate logistic regression analyses. Based on these risk factors, a nomogram was developed and validated.
Of the 742 ICH patients included in this study, 519 were assigned to the training cohort and 223 to the validation cohort. Multivariate logistic regression analysis identified several risk factors for poor prognosis of ICH: brainstem hemorrhage (OR = 3.17, 95% CI = 1.80-5.59, < 0.01), reduced activated partial thromboplastin time (APTT) (OR = 0.94, 95% CI = 0.89-0.99, = 0.047), large bleeding volume (OR = 1.06, 95% CI = 1.04-1.09, < 0.01), low Glasgow Coma Scale (GCS) score (OR = 0.76, 95% CI = 0.70-0.82, < 0.01), and high PIV level (OR = 1.01, 95% CI = 1.01-1.01, < 0.01). A nomogram was constructed based on these factors. The area under the receiver operating characteristic curve was 0.86, indicating good discrimination ability. The Hosmer-Lemeshow goodness-of-fit test for the validation cohort demonstrated that the model had satisfactory calibration. Decision curve analysis revealed that the nomogram had clinical utility across a wide range of threshold probabilities.
A high PIV level, large bleeding volume, and low GCS score are significant risk factors for poor prognosis in patients with ICH. The nomogram based on these factors demonstrates robust predictive performance.
本研究旨在探讨全免疫炎症值（PIV）对自发性脑出血（ICH）预后的影响，并开发和验证一种用于识别脑出血后预后不良患者的列线图。
我们回顾性收集了2018年9月至2024年3月在徐州医科大学附属医院住院的742例脑出血患者的临床资料。出院后90天改良Rankin量表评分>3被定义为短期预后不良。将纳入的患者按7:3的比例随机分为训练队列和验证队列。在训练队列中，通过单因素和多因素逻辑回归分析确定与短期预后不良相关的危险因素。基于这些危险因素，开发并验证了列线图。
本研究纳入的742例ICH患者中，519例被分配到训练队列，223例被分配到验证队列。多因素逻辑回归分析确定了ICH预后不良的几个危险因素：脑干出血（OR = 3.17，95%CI = 1.80 - 5.59，P < 0.01）、活化部分凝血活酶时间（APTT）缩短（OR = 0.94，95%CI = 0.89 - 0.99，P = 0.047）、出血量较大（OR = 1.06，95%CI = 1.04 - 1.09，P < 0.01）、格拉斯哥昏迷量表（GCS）评分较低（OR = 0.76，95%CI = 0.70 - 0.82，P < 0.01）和PIV水平较高（OR = 1.01，95%CI = 1.01 - 1.01，P < 0.01）。基于这些因素构建了列线图。受试者工作特征曲线下面积为0.86，表明具有良好的区分能力。验证队列的Hosmer-Lemeshow拟合优度检验表明该模型具有满意的校准。决策曲线分析显示，列线图在广泛的阈值概率范围内具有临床实用性。
PIV水平较高、出血量较大和GCS评分较低是ICH患者预后不良的重要危险因素。基于这些因素的列线图显示出强大的预测性能。
