Evidence map›Paper›PMID 39580515›Full record

ArticleScientific reports2024

Development and validation of a dynamic nomogram for predicting in-hospital mortality in patients with gastrointestinal bleeding: a retrospective cohort study in the intensive care unit.

Kang Zou, Shu Huang, Wensen Ren, Huan Xu, Zhiying Liu, Wei Zhang, Lei Shi, Xinxin Pu, Yinqin Lv, Yan Peng and 2 more

Abstract readValidation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Kang Zou *Department of Gastroenterology, Yibin Second People's Hospital, Yibin, China.
Shu Huang *Department of Gastroenterology, the People's Hospital of Lianshui, Huaian, China.
Wensen Ren *Department of Gastroenterology, the Affiliated Hospital of Southwest Medical University, Street Taiping No.25, Region Jiangyang, Luzhou, 646099, Sichuan Province, China.
Huan XuDepartment of Gastroenterology, the Affiliated Hospital of Southwest Medical University, Street Taiping No.25, Region Jiangyang, Luzhou, 646099, Sichuan Province, China.
Zhiying LiuYibin City Health Committee, Yibin, China.
Wei ZhangDepartment of Gastroenterology, the Affiliated Hospital of Southwest Medical University, Street Taiping No.25, Region Jiangyang, Luzhou, 646099, Sichuan Province, China.
Lei ShiDepartment of Gastroenterology, the Affiliated Hospital of Southwest Medical University, Street Taiping No.25, Region Jiangyang, Luzhou, 646099, Sichuan Province, China.
Xinxin PuDepartment of Gastroenterology, the Affiliated Hospital of Southwest Medical University, Street Taiping No.25, Region Jiangyang, Luzhou, 646099, Sichuan Province, China.
Yinqin LvDepartment of Gastroenterology, the Affiliated Hospital of Southwest Medical University, Street Taiping No.25, Region Jiangyang, Luzhou, 646099, Sichuan Province, China.
Yan PengDepartment of Gastroenterology, the Affiliated Hospital of Southwest Medical University, Street Taiping No.25, Region Jiangyang, Luzhou, 646099, Sichuan Province, China.
Fangfang YuanDepartment of Intensive Care Unit, The 3Rd Xiangya Hospital, Central South University, Street Tongzipo No.138, Region Yuelu, Changsha, 410000, China. yffznxy@csu.edu.cn.
Xiaowei TangDepartment of Gastroenterology, the Affiliated Hospital of Southwest Medical University, Street Taiping No.25, Region Jiangyang, Luzhou, 646099, Sichuan Province, China. solitude5834@hotmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The study aims to develop and validate a predictive model for effectively predicting in-hospital mortality in patients admitted to the intensive care unit due to Gastrointestinal bleeding (GIB). A retrospective cohort study was conducted, including data from patients in the Electronic Intensive Care Unit Collaborative Research Database (eICU-CRD) and Medical Information Mart for Intensive Care-IV Database (MIMIC-IV) with a diagnosis of GIB. Patients from the eICU-CRD were randomly allocated into both development and validation sets, and those from MIMIC-IV were assigned as an external validation group. Multivariate logistic regression was employed to create a predictive model, which was depicted as a nomogram. This study included a total of 2929 patients with GIB from the eICU-CRD and 718 patients from the MIMIC-IV. To access the dynamic nomogram, please use the following link: https://kangzou.shinyapps.io/DynNomapp_GIB/ . The area under the receiver operating characteristic curve for the nomogram was 0.893 in the development set, 0.860 in the internal validation set, and 0.781 in the external validation set. The mortality rate was 25.7% in the high-risk group (nomogram scores > 101.974) and 2.8% in the low-risk group (nomogram scores ≤ 101.974). The nomogram exhibited excellent discrimination, calibration, and clinical utility in predicting in-hospital mortality among patients admitted to the intensive care unit with GIB.

Indexed as

Gastrointestinal HemorrhageHospital MortalityIntensive Care UnitsNomogramsAgedAged, 80 and overFemaleHumansMaleMiddle AgedPrognosisRetrospective StudiesROC Curve

Identifiers

PMID39580515
PMCPMC11585621

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