Evidence map›Paper›PMID 40652186›Full record

ArticleBMC nephrology2025

Development and validation of a predictive model for upper gastrointestinal bleeding in peritoneal dialysis patients: a retrospective, multicenter cohort study.

Sijia Shang, Xing Zhang, Xiaojiang Zhan, Na Tian, Fenfen Peng, Yueqiang Wen, Xiaoyang Wang, Xiaoran Feng, Qian Zhou, Xianfeng Wu and 3 more

Abstract readMulticenter StudyValidation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC nephrology, 2025. 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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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

13 authors.

Sijia Shang *Department of Hematology, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Xing Zhang *Department of Hematology, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Xiaojiang ZhanDepartment of Nephrology, The First Affiliated Hospital, Nanchang University, Nanchang, China.
Na TianDepartment of Nephrology, General Hospital of Ningxia Medical University, Yinchuan, China.
Fenfen PengDepartment of Nephrology, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
Yueqiang WenDepartment of Nephrology, The Second Affiliated Hospital, Guangzhou Medical University, Guangzhou, China.
Xiaoyang WangDepartment of Nephrology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Xiaoran FengDepartment of Nephrology, Jiujiang No. 1 People's Hospital, Jiujiang, China.
Qian ZhouDepartment of Medical Statistics, Clinical Trials Unit, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Xianfeng WuDepartment of Nephrology, Shanghai Jiaotong University Affiliated Sixth People's Hospital, Shanghai, China.
Qingdong XuDepartment of Nephrology, Jiangmen Central Hospital, Jiangmen, China.
Hongrui Shi *Department of Hematology, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Ning Su *Department of Hematology, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China. Suning5@mail.sysu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe incidence of upper gastrointestinal bleeding (UGIB) in peritoneal dialysis (PD) patients was higher than that in the general population. Although there have been studies on the risk factors of UGIB in PD patients, few studies had established the model of UGIB in PD patients. The purpose of this study was to establish and verify a predictive model of UGIB in PD patients.

methodsThis retrospective study was conducted between February 1, 2007, and November 15, 2021. The patients were divided into training and validation sets in a 1:1 ratio. The least absolute shrinkage and selection operator (LASSO) regression was used to screen potential risk factors for UGIB. These risk factors were used to generate a prognostic nomogram. The nomogram model predictive performance was evaluated by receiver operating characteristic (ROC)curves, calibration curves and decision curve analysis (DCA).

resultsA total of 2107 eligible patients were included in this study. 114 patients suffered from UGIB. After LASSO regression analysis, five representative variables were included in the nomogram: the use of calcium, the use of proton pump inhibitors (PPIs), the history of UGIB, hemoglobin, and uric acid. The C-index of the training set was 0.859 (0.810-0.909), and the C-index of the validation set was 0.874 (0.829-0.919).

conclusionUsing Calcium and PPIs, the history of UGIB, hemoglobin, and uric acid were important predictors of UGIB in PD patients. The nomogram developed and validated in this study has the potential to become an effective tool for clinicians to predict UGIB in PD patients.

Indexed as

Gastrointestinal HemorrhageNomogramsPeritoneal DialysisAdultAgedFemaleHumansMaleMiddle AgedRetrospective StudiesRisk FactorsNomogramPeritoneal dialysisRisk factorsUpper gastrointestinal bleeding

Identifiers

PMID40652186
PMCPMC12255992

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