Shu Chang, Zheng Chenguang, Zhang Guobin
Tianjin Key Laboratory of Cerebral Vascular and Neurodegenerative Diseases, Tianjin Neurosurgical Institute, Tianjin Huanhu Hospital, Tianjin, China.
Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin, China.
Front Neurol. 2024 Jan 15;15:1287895. doi: 10.3389/fneur.2024.1287895. eCollection 2024.
We introduce the comprehensive inflammatory prognostic index (CIPI), a novel prognostic tool for critically ill cerebral infarction patients, designed to meet the urgent need for timely and convenient clinical decision-making in this high-risk patient group.
Using exploratory factor analysis on selected indices-neutrophil to lymphocyte ratio (NLR), systemic inflammation response index (SIRI), and systemic immune inflammation index (SIII)-we derived CIPI, a latent variable capturing their combined predictive power. Data from 1,022 patients in the Medical Information Mart for Intensive Care (MIMIC)-IV database were used to develop CIPI-based survival models, with the robustness and area under the receiver operating characteristic curve (AUC) performance of CIPI validated against an independent dataset of 326 patients from the MIMIC-III CareVue subset. The CIPI's predictive power for in-hospital and intensive care unit (ICU) mortality was assessed through Kaplan-Meier analysis, univariate and multivariate Cox regression models, and time-dependent AUC analysis. Linearity, subgroup sensitivity analyses and interaction effects with CIPI were also evaluated.
CIPI was an independent prognostic factor, demonstrating a statistically significant association with in-hospital and ICU mortality, when assessed as a continuous and a categorical variable. It showed a linear relationship with mortality rates and demonstrated stability across most subgroups, with no significant interactions observed. Its predictive capabilities for in-hospital and ICU mortality among critically ill cerebral infarction patients matched those of established prognostic indices in the MIMIC database.
Our study indicates that CIPI is a reliable and effective prognostic tool for critically ill cerebral infarction patients in predicting in-hospital and ICU mortality. Its straightforward calculation, rooted in routine blood tests, enhances its practicality, promising significant utility in clinical settings.
我们引入综合炎症预后指数（CIPI），这是一种针对重症脑梗死患者的新型预后工具，旨在满足这一高危患者群体对及时、便捷临床决策的迫切需求。
通过对选定指标——中性粒细胞与淋巴细胞比值（NLR）、全身炎症反应指数（SIRI）和全身免疫炎症指数（SIII）进行探索性因子分析，我们得出了CIPI，这是一个捕获它们综合预测能力的潜在变量。来自重症监护医学信息数据库（MIMIC）-IV数据库的1022例患者的数据用于建立基于CIPI的生存模型，CIPI的稳健性和受试者操作特征曲线下面积（AUC）性能在来自MIMIC-III CareVue子集的326例患者的独立数据集中得到验证。通过Kaplan-Meier分析、单变量和多变量Cox回归模型以及时间依赖性AUC分析评估CIPI对院内和重症监护病房（ICU）死亡率的预测能力。还评估了线性、亚组敏感性分析以及与CIPI的交互作用。
当作为连续变量和分类变量进行评估时，CIPI是一个独立的预后因素，与院内和ICU死亡率存在统计学上的显著关联。它与死亡率呈线性关系，在大多数亚组中表现出稳定性，未观察到显著的交互作用。其对重症脑梗死患者院内和ICU死亡率的预测能力与MIMIC数据库中已有的预后指标相当。
我们的研究表明，CIPI是预测重症脑梗死患者院内和ICU死亡率的可靠且有效的预后工具。其基于常规血液检查的简单计算增强了其实用性，有望在临床环境中发挥重要作用。
