Evidence map›Paper›PMID 40706028›Full record

ArticleJournal of medical Internet research2025

Predicting In-Hospital Mortality in Intensive Care Unit Patients Using Causal SurvivalNet With Serum Chloride and Other Causal Factors: Cross-Country Study.

Jing Wang, Qixiu Li, Can Xie, Xiaofei Li, Huikao Wang, Wei Xu, Ruyan Lv, Xiaobing Zhai, Ping Xu, Kefeng Li and 1 more

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Jing Wang *Department of Critical Care Medicine, Yantai Yuhuangding Hospital, Qingdao University, Yantai, China.ORCID https://orcid.org/0009-0004-6092-0068
Qixiu Li *Department of Critical Care Medicine, Yantai Yuhuangding Hospital, Qingdao University, Yantai, China.ORCID https://orcid.org/0009-0008-6520-2128
Can XieFaculty of Applied Science, Macao Polytechnic University, Macao, Macao.ORCID https://orcid.org/0009-0000-4076-4388
Xiaofei LiDepartment of Critical Care Medicine, Yantai Yuhuangding Hospital, Qingdao University, Yantai, China.ORCID https://orcid.org/0009-0001-5915-8414
Huikao WangDepartment of Critical Care Medicine, Yantai Yuhuangding Hospital, Qingdao University, Yantai, China.ORCID https://orcid.org/0009-0003-9581-062X
Wei XuFaculty of Applied Science, Macao Polytechnic University, Macao, Macao.ORCID https://orcid.org/0000-0003-3708-6816
Ruyan LvDepartment of Critical Care Medicine, Yantai Yuhuangding Hospital, Qingdao University, Yantai, China.ORCID https://orcid.org/0009-0003-0997-7344
Xiaobing ZhaiFaculty of Applied Science, Macao Polytechnic University, Macao, Macao.ORCID https://orcid.org/0000-0002-4575-7360
Ping XuEmergency Department, Zigong Fourth People's Hospital, Zigong, China.ORCID https://orcid.org/0000-0003-1379-4295
Kefeng Li *Faculty of Applied Science, Macao Polytechnic University, Macao, Macao.ORCID https://orcid.org/0000-0002-7233-4347
Xi-Cheng Song *Department of Otolaryngology Head and Neck Surgery, Yantai Yuhuangding Hospital, Qingdao University, Yantai, China.ORCID https://orcid.org/0000-0002-9789-1318

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIncorporating 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.

objectiveQuantitative 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.

methodsA 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.

resultsCausal 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.

conclusionsUsing initial serum chloride levels enhances prognostic accuracy and facilitates tailored treatment plans for ICU patients in critical care settings.

Indexed as

ChloridesHospital MortalityIntensive Care UnitsAgedChinaCohort StudiesDeep LearningFemaleHumansMaleMiddle AgedPrognosisChloridesCausal SurvivalNetdeep learningelectrolyte imbalanceICUintensive care unitprognosisthreshold

Identifiers

PMID40706028
PMCPMC12332460

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.