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Exploration of a nomogram prediction model of 30-day survival in adult ECMO patients

OBJECTIVE: To investigate the factors of 30-day survival in ECMO patients, establish a nomogram model, and evaluate the predictive value of the model. METHODS: A total of 105 patients with extracorporeal membrane oxygenation (ECMO) were admitted to the Department of Critical Care Medicine, The First...

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Autores principales: Cui, Liangwen, Zha, Yutao, Zhang, Cheng, Zhang, Hui, Yu, Chao, Rui, Huang, Shao, Min, Liu, Nian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10011074/
https://www.ncbi.nlm.nih.gov/pubmed/36926323
http://dx.doi.org/10.3389/fmed.2023.1062918
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author Cui, Liangwen
Zha, Yutao
Zhang, Cheng
Zhang, Hui
Yu, Chao
Rui, Huang
Shao, Min
Liu, Nian
author_facet Cui, Liangwen
Zha, Yutao
Zhang, Cheng
Zhang, Hui
Yu, Chao
Rui, Huang
Shao, Min
Liu, Nian
author_sort Cui, Liangwen
collection PubMed
description OBJECTIVE: To investigate the factors of 30-day survival in ECMO patients, establish a nomogram model, and evaluate the predictive value of the model. METHODS: A total of 105 patients with extracorporeal membrane oxygenation (ECMO) were admitted to the Department of Critical Care Medicine, The First Affiliated Hospital of Anhui Medical University, from January 2018 to March 2021. Cox regression analysis screened out the risk factors. Based on the results of multivariate analysis, the nomogram model was established by using R software, and the discrimination of the model was verified by bootstrap and calibration. RESULTS: The results showed that sex, acute physiology and chronic health evaluation (APACHE) II score, disseminated intravascular coagulation (DIC) score before ECMO initiation and average daily dose of norepinephrine were independent risk factors for prognosis. Verify that the nomogram model is verified by bootstrap internally, and the corrected C-index is C-index: 0.886, showing a good degree of discrimination. The calibration curve (calibration) showed that the nomogram model had good agreement. The decision curve analysis(DCA) curve shows good clinical validity above the two extreme curves. Kaplan–Meier curves were drawn for patients in the tertile and compared with the first and second groups. The third group predicted the worst 30-day prognosis for ECMO patients. CONCLUSION: The nomogram prediction model constructed based on the sex, APACHE II and DIC score, average daily dose of norepinephrine can effectively screen out the factors affecting the prognosis and provide a reference for individualized treatment of ECMO patients.
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spelling pubmed-100110742023-03-15 Exploration of a nomogram prediction model of 30-day survival in adult ECMO patients Cui, Liangwen Zha, Yutao Zhang, Cheng Zhang, Hui Yu, Chao Rui, Huang Shao, Min Liu, Nian Front Med (Lausanne) Medicine OBJECTIVE: To investigate the factors of 30-day survival in ECMO patients, establish a nomogram model, and evaluate the predictive value of the model. METHODS: A total of 105 patients with extracorporeal membrane oxygenation (ECMO) were admitted to the Department of Critical Care Medicine, The First Affiliated Hospital of Anhui Medical University, from January 2018 to March 2021. Cox regression analysis screened out the risk factors. Based on the results of multivariate analysis, the nomogram model was established by using R software, and the discrimination of the model was verified by bootstrap and calibration. RESULTS: The results showed that sex, acute physiology and chronic health evaluation (APACHE) II score, disseminated intravascular coagulation (DIC) score before ECMO initiation and average daily dose of norepinephrine were independent risk factors for prognosis. Verify that the nomogram model is verified by bootstrap internally, and the corrected C-index is C-index: 0.886, showing a good degree of discrimination. The calibration curve (calibration) showed that the nomogram model had good agreement. The decision curve analysis(DCA) curve shows good clinical validity above the two extreme curves. Kaplan–Meier curves were drawn for patients in the tertile and compared with the first and second groups. The third group predicted the worst 30-day prognosis for ECMO patients. CONCLUSION: The nomogram prediction model constructed based on the sex, APACHE II and DIC score, average daily dose of norepinephrine can effectively screen out the factors affecting the prognosis and provide a reference for individualized treatment of ECMO patients. Frontiers Media S.A. 2023-02-28 /pmc/articles/PMC10011074/ /pubmed/36926323 http://dx.doi.org/10.3389/fmed.2023.1062918 Text en Copyright © 2023 Cui, Zha, Zhang, Zhang, Yu, Rui, Shao and Liu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Medicine
Cui, Liangwen
Zha, Yutao
Zhang, Cheng
Zhang, Hui
Yu, Chao
Rui, Huang
Shao, Min
Liu, Nian
Exploration of a nomogram prediction model of 30-day survival in adult ECMO patients
title Exploration of a nomogram prediction model of 30-day survival in adult ECMO patients
title_full Exploration of a nomogram prediction model of 30-day survival in adult ECMO patients
title_fullStr Exploration of a nomogram prediction model of 30-day survival in adult ECMO patients
title_full_unstemmed Exploration of a nomogram prediction model of 30-day survival in adult ECMO patients
title_short Exploration of a nomogram prediction model of 30-day survival in adult ECMO patients
title_sort exploration of a nomogram prediction model of 30-day survival in adult ecmo patients
topic Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10011074/
https://www.ncbi.nlm.nih.gov/pubmed/36926323
http://dx.doi.org/10.3389/fmed.2023.1062918
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