The rate-pressure product combined model within 24 h on admission predicts the 30-day mortality rate in conservatively treated patients with intracerebral hemorrhage

作者全名：Zheng, Hui; Tang, Yuguang; Zhou, Hai; Ji, Xiang

作者地址：[Zheng, Hui; Tang, Yuguang; Zhou, Hai; Ji, Xiang] Chongqing Med Univ, Affiliated Hosp 2, Dept Neurosurg, Chongqing, Peoples R China

通信作者：Ji, X (通讯作者)，Chongqing Med Univ, Affiliated Hosp 2, Dept Neurosurg, Chongqing, Peoples R China.

来源：FRONTIERS IN NEUROLOGY

ESI学科分类：CLINICAL MEDICINE

WOS号：WOS:001251155500001

JCR分区：Q2

影响因子：2.7

年份：2024

卷号：15

期号：　

开始页：　

结束页：　

文献类型：Article

关键词：intracerebral hemorrhage; rate-pressure product; ICH score; prognostic model; GCS-Glasgow Coma Scale

摘要：Background and objectives Recently, some literature has proposed new indicators such as rate-pressure product, platelet-to-lymphocyte ratio, neutrophil-to-lymphocyte ratio, etc. However, there has been no literature that has utilized these new indicators to establish a predictive model for assessing the risk of mortality in patients within 24 h on admission. Therefore, this study aims to build a predictive model that can rapidly assess the likelihood of mortality in patients within 24 h of admission.Methods The datasets used in this study are available from the corresponding author upon reasonable request. Patients were randomly assigned to the training or validation cohort based on a ratio of 7:3, which was implemented as internal validations for the final predictive models. In the training set, least absolute shrinkage and selection operator (LASSO) regression was employed to select predictive factors, followed by both univariate and subsequent multivariate analysis. The predictive ability was assessed by the area under the receiver operating characteristic (ROC) curve.Results A total of 428 patients were included in our research. The final model included 4 independent predictors (Glasgow Coma Scale, hematoma volume, rate-pressure product, c-reactive protein) and was developed as a simple-to-use nomogram. The training set and internal validation set model's C-index are 0.933 and 0.954, demonstrating moderate predictive ability with regard to risks of mortality. Compared to ICH score (AUC: 0.910 and 0.925), the net reclassification index (NRI) is 0.298 (CI = -0.105 to 0.701, p: 0.147) and integrated discrimination improvement (IDI) is 0.089 (CI = -0.049 to 0.228, p: 0.209). Our model is equally excellent as the classic ICH score model.Conclusion We developed a model with four independent risk factors to predict the mortality of ICH patients. Our predictive model is effective in assessing the risk of mortality in patients within 24 h on admission, which might be worth considering in clinical settings after further external validation.

基金机构：　

基金资助正文：