Evidence map›Paper›PMID 41087917›Full record

ArticleBMC cardiovascular disorders2025

Construction of a nomogram model for individualized prediction of extracorporeal membrane oxygenation weaning outcomes in cardiogenic shock.

Zhiming Kuang, Wenhao Yin, Shanbin Yuan, Lin Gao

Abstract readValidation Study
In one paragraph

Article in BMC cardiovascular disorders, 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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5 · Who and what money

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4 authors.

Zhiming KuangDepartment of Critical Care Medicine, Ganzhou People's Hospital, No. 16 Meiguan Avenue, Ganzhou City, Jiangxi Province, 341000, China.
Wenhao YinDepartment of Critical Care Medicine, Ganxian District People's Hospital, Ganzhou City, 341100, China.
Shanbin YuanDepartment of Critical Care Medicine, Xinfeng County People's Hospital, Ganzhou City, 341600, China.
Lin GaoDepartment of Critical Care Medicine, Ganzhou People's Hospital, No. 16 Meiguan Avenue, Ganzhou City, Jiangxi Province, 341000, China. a13711271812@126.com.

Funding

2022 Ganzhou City "Science and Technology+National Regional Center" Joint Plan Project 2002-YB1452
6 · The paper itself

Abstract

objectiveTo construct a nomogram prediction model for death in patients with cardiogenic shock after extracorporeal membrane oxygenation (ECMO) weaning.

methodsTotally 210 patients with cardiogenic shock treated with ECMO between January 2023 and October 2024 were included. They were randomly divided into the modeling group of 147 cases and the validation group of 63 cases complying with a 7:3 ratio. The modeling group was divided into the death group of 65 cases and the survival group of 82 cases based on the 28-day death status. Cox regression analysis was used to determine independent risk factors for death after ECMO weaning in patients with cardiogenic shock. R software was used to construct a nomogram prediction model to predict the likelihood of death in cardiogenic shock after ECMO weaning. The ROC curve and calibration curve were used to verify the discrimination and calibration of the nomogram prediction model, respectively; and the decision curve was used to analyze and evaluate clinical utility and net benefit.

resultsClinical data such as age, gender, and weight showed no statistically significant differences between the modeling group and the validation group (P > 0.05). The death group had significantly higher age, rates of obesity, CRRT, cardiac arrest before ECMO, preoperative lactate level, and intraoperative red blood cell volume compared to the survival group (P < 0.05). Increase in age, obesity, CRRT, cardiac arrest before ECMO, elevated preoperative lactate level, and increased intraoperative red blood cell volume were independent predictive factors for death after ECMO weaning in patients with cardiogenic shock (P < 0.05). The AUC of ROC curve for modeling group and the validation group was 0.994 and 0.966, respectively; the consistency between the predicted probability and the actual probability of the calibration curve was high, with Hosmer-Lemeshow test modeling group χ2 = 4.472, P = 0.619; validation group, χ2 = 3.813, P = 0.874; the clinical decision curve revealed that the nomogram prediction model had good net returns within the high-risk threshold probability range of 0.04 ~ 0.98.

conclusionThe nomogram model established in this study can effectively predict the likelihood of death in patients with cardiogenic shock after ECMO weaning, and provide reference for personalized treatment.

Indexed as

Decision Support TechniquesExtracorporeal Membrane OxygenationNomogramsShock, CardiogenicAdultAgedClinical Decision-MakingFemaleHumansMaleMiddle AgedPredictive Value of TestsReproducibility of ResultsRetrospective StudiesRisk AssessmentRisk FactorsCardiogenic shockExtracorporeal membrane oxygenationNomogramPrognosisRisk factors'

Identifiers

PMID41087917
PMCPMC12522465

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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.