Wang Jing, Li Qixiu, Xie Can, Li Xiaofei, Wang Huikao, Xu Wei, Lv Ruyan, Zhai Xiaobing, Xu Ping, Li Kefeng, Song Xi-Cheng
Department of Critical Care Medicine, Yantai Yuhuangding Hospital, Qingdao University, Yantai, China.
Faculty of Applied Science, Macao Polytechnic University, Macao, Macao.
J Med Internet Res. 2025 Jul 24;27:e70118. doi: 10.2196/70118.
Incorporating initial serum chloride levels as a prognostic indicator in the intensive care environment has the potential to refine risk stratification and tailor treatment strategies, leading to more efficient use of clinical resources and improved patient outcomes.
Quantitative analysis of the relationship between serum chloride levels at intensive care unit (ICU) admission and in-hospital mortality, and the establishment of a personalized survival curve prediction deep learning model to enhance risk stratification and clinical decision-making.
A large-scale, cross-country, multicohort study of 189,462 ICU patients from four cohorts was conducted: 70,370 from Medical Information Mart for Intensive Care IV (MIMIC-IV), 112,457 from eICU Collaborative Research Database (eICU-CRD; 2 US cohorts), 4653 from Yantai Yuhuangding Hospital, and 1982 patients from Zigong Fourth People's Hospital (2 Chinese cohorts). We collected demographics, underlying diseases, ICU complications, electrolyte levels, biochemical parameters, and vital signs at ICU admission, along with length of stay and in-hospital survival outcomes. Causal graph analysis pinpointed clinical variables linked to mortality. Nonlinear associations between chloride levels and mortality were evaluated using restricted cubic splines and Cox proportional hazards models, validated with the Cox frailty model, Kaplan-Meier curves, and sensitivity analyses. A deep learning model was created for individualized survival predictions.
Causal inference revealed a significant association between admission serum chloride levels and 28-day mortality. The median serum chloride level at ICU admission was 104 (IQR 100-108) mEq/L. In analyzing all 42 variables, restricted cubic splines identified thresholds at 103 mEq/L and 115 mEq/L, categorizing patients into three groups: ≤103 mEq/L, 103-115 mEq/L, and >115 mEq/L. Cox proportional hazards models revealed higher death risks for patients outside this range, with hazard ratios (HRs) of 1.36 (95% CI 1.29-1.43) for ≤103 mEq/L and 1.27 (95% CI 1.14-1.41) for >115 mEq/L. Four cross-cohort validations confirmed these critical ranges. For the eICU-CRD dataset, the HRs for the key intervals are 1.30 (95% CI 1.24-1.36) and 0.97 (95% CI 0.89-1.06). In the Yantai Yuhuangding Hospital affiliated with Qingdao University (YHD-HOSP) dataset, the HRs for the key intervals are 1.23 (95% CI 1.09-1.38) and 1.58 (95% CI 1.27-1.96). In the Sichuan Zigong Fourth People's Hospital (SCZG-HOSP) dataset, the HR for the key interval is 2.20 (95% CI 1.43-3.39). The Causal SurvivalNet accurately predicted individual survival curves using admission chloride levels and other factors, achieving Brier scores of 0.09, 0.12, and 0.15. Results from cohort analyses in both China and the United States consistently and closely correlate the critical range of chloride with the prognosis of ICU patients.
Using initial serum chloride levels enhances prognostic accuracy and facilitates tailored treatment plans for ICU patients in critical care settings.
在重症监护环境中，将初始血清氯水平作为预后指标，有可能优化风险分层并制定个性化治疗策略，从而更有效地利用临床资源并改善患者预后。
定量分析重症监护病房（ICU）入院时血清氯水平与院内死亡率之间的关系，并建立个性化生存曲线预测深度学习模型，以加强风险分层和临床决策。
对来自四个队列的189,462例ICU患者进行了一项大规模、跨国、多队列研究：70,370例来自重症监护医学信息集市IV（MIMIC-IV），112,457例来自电子ICU协作研究数据库（eICU-CRD；2个美国队列），4653例来自烟台毓璜顶医院，1982例来自自贡市第四人民医院（2个中国队列）。我们收集了患者的人口统计学资料、基础疾病、ICU并发症、电解质水平、生化参数以及ICU入院时的生命体征，以及住院时间和院内生存结局。因果图分析确定了与死亡率相关的临床变量。使用受限立方样条和Cox比例风险模型评估氯水平与死亡率之间的非线性关联，并通过Cox脆弱模型、Kaplan-Meier曲线和敏感性分析进行验证。创建了一个深度学习模型用于个性化生存预测。
因果推断显示入院时血清氯水平与28天死亡率之间存在显著关联。ICU入院时血清氯水平的中位数为104（四分位间距100-108）mEq/L。在分析所有42个变量时，受限立方样条确定了103 mEq/L和115 mEq/L的阈值，将患者分为三组：≤103 mEq/L、103-115 mEq/L和>115 mEq/L。Cox比例风险模型显示，超出此范围的患者死亡风险更高，≤103 mEq/L组的风险比（HR）为1.36（95%置信区间1.29-1.43），>115 mEq/L组的HR为1.27（95%置信区间1.14-1.41）。四项跨队列验证证实了这些关键范围。对于eICU-CRD数据集，关键区间的HR分别为1.30（95%置信区间1.24-1.36）和0.97（95%置信区间0.89-1.06）。在青岛大学附属烟台毓璜顶医院（YHD-HOSP）数据集，关键区间的HR分别为1.23（95%置信区间1.09-1.38）和1.58（95%置信区间1.27-1.96）。在四川自贡市第四人民医院（SCZG-HOSP）数据集，关键区间的HR为2.20（95%置信区间1.43-3.39）。因果生存网络（Causal SurvivalNet）使用入院时的氯水平和其他因素准确预测了个体生存曲线，Brier评分为0.09、0.12和0.15。中国和美国队列分析的结果一致且紧密地将氯的关键范围与ICU患者的预后相关联。
使用初始血清氯水平可提高预后准确性，并有助于为重症监护环境中的ICU患者制定个性化治疗方案。
