Evidence map›Paper›PMID 37740869›Full record

ArticleInternal and emergency medicine2024

Early warning system enables accurate mortality risk prediction for acute gastrointestinal bleeding admitted to intensive care unit.

Meng Jiang, Chang-Li Li, Xing-Chen Lin, Li-Gang Xu

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Article in Internal and emergency medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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4 authors.

Meng Jiang *Emergency and Trauma Center, The First Affiliated Hospital, Zhejiang University School of Medicine, #79 Qingchun Road, Hangzhou, 310003, Zhejiang, People's Republic of China. jmhust@zju.edu.cn.
Chang-Li Li *Department of FSTC Clinic, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China.
Xing-Chen LinEmergency and Trauma Center, The First Affiliated Hospital, Zhejiang University School of Medicine, #79 Qingchun Road, Hangzhou, 310003, Zhejiang, People's Republic of China.
Li-Gang XuDepartment of Traumatic Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430000, China.

Funding

China Postdoctoral Science Foundation 82000479National Natural Science Foundation of China 82000479
6 · The paper itself

Abstract

Acute gastrointestinal (GI) bleeding are potentially life-threatening conditions. Early risk stratification is important for triaging patients to the appropriate level of medical care and intervention. Patients admitted to intensive care unit (ICU) has a high mortality, but risk tool is scarce for these patients. This study aimed to develop and validate a risk score to improve the prognostication of death at the time of patient admission to ICU. We developed and internally validated a nomogram for mortality in patients with acute GI bleeding from the eICU Collaborative Research Database (eICU-CRD), and externally validated it in patients from the Medical Information Mart for Intensive Care III database (MIMIC-III) and Wuhan Tongji Hospital. The performance of the model was assessed by examining discrimination (C-index), calibration (calibration curves) and usefulness (decision curves). 4750 patients were included in the development cohort, with 1184 patients in the internal validation cohort, 1406 patients in the MIMIC-III validation cohort, and 342 patients in the Tongji validation cohort. The nomogram, which incorporated ten variables, showed good calibration and discrimination in the training and validation cohorts, yielded C-index ranged from 0.832 (95%CI 0.811-0.853) to 0.926 (95CI% 0.905-0.947). The nomogram-defined high-risk group had a higher mortality than the low-risk group (44.8% vs. 3.5%, P < 0.001; 41.4% vs 3.1%, P < 0.001;53.6% vs 7.5%, P < 0.001; 38.2% vs 4.2%, P < 0.001). The model performed better than the conventional Glasgow-Blatchford score, AIMS65 and the newer Oakland and Sengupta scores for mortality prediction in both the derivation and validation cohorts concerning discrimination and usefulness. Our nomogram is a reliable prognostic tool that might be useful to identify high-risk acute GI bleeding patients admitted to ICU.

Indexed as

Gastrointestinal HemorrhageHospitalizationHumansIntensive Care UnitsPrognosisRisk FactorsAcute gastrointestinal bleedingMortality predictionNomogramRisk factors

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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.