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Prediction of in-hospital death following acute type A aortic dissection

BACKGROUND: Our goal was to create a prediction model for in-hospital death in Chinese patients with acute type A aortic dissection (ATAAD). METHODS: A retrospective derivation cohort was made up of 340 patients with ATAAD from Tianjin, and the retrospective validation cohort was made up of 153 pati...

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Autores principales: Chen, Junquan, Bai, Yunpeng, Liu, Hong, Qin, Mingzhen, Guo, Zhigang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10090540/
https://www.ncbi.nlm.nih.gov/pubmed/37064704
http://dx.doi.org/10.3389/fpubh.2023.1143160
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author Chen, Junquan
Bai, Yunpeng
Liu, Hong
Qin, Mingzhen
Guo, Zhigang
author_facet Chen, Junquan
Bai, Yunpeng
Liu, Hong
Qin, Mingzhen
Guo, Zhigang
author_sort Chen, Junquan
collection PubMed
description BACKGROUND: Our goal was to create a prediction model for in-hospital death in Chinese patients with acute type A aortic dissection (ATAAD). METHODS: A retrospective derivation cohort was made up of 340 patients with ATAAD from Tianjin, and the retrospective validation cohort was made up of 153 patients with ATAAD from Nanjing. For variable selection, we used least absolute shrinkage and selection operator analysis, and for risk scoring, we used logistic regression coefficients. We categorized the patients into low-, middle-, and high-risk groups and looked into the correlation with in-hospital fatalities. We established a risk classifier based on independent baseline data using a multivariable logistic model. The prediction performance was determined based on the receiver operating characteristic curve (ROC). Individualized clinical decision-making was conducted by weighing the net benefit in each patient by decision curve analysis (DCA). RESULTS: We created a risk prediction model using risk scores weighted by five preoperatively chosen variables [AUC: 0.7039 (95% CI, 0.643–0.765)]: serum creatinine (Scr), D-dimer, white blood cell (WBC) count, coronary heart disease (CHD), and blood urea nitrogen (BUN). Following that, we categorized the cohort's patients as low-, intermediate-, and high-risk groups. The intermediate- and high-risk groups significantly increased hospital death rates compared to the low-risk group [adjusted OR: 3.973 (95% CI, 1.496–10.552), P < 0.01; 8.280 (95% CI, 3.054–22.448), P < 0.01, respectively). The risk score classifier exhibited better prediction ability than the triple-risk categories classifier [AUC: 0.7039 (95% CI, 0.6425–0.7652) vs. 0.6605 (95% CI, 0.6013–0.7197); P = 0.0022]. The DCA showed relatively good performance for the model in terms of clinical application if the threshold probability in the clinical decision was more than 10%. CONCLUSION: A risk classifier is an effective strategy for predicting in-hospital death in patients with ATAAD, but it might be affected by the small number of participants.
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spelling pubmed-100905402023-04-13 Prediction of in-hospital death following acute type A aortic dissection Chen, Junquan Bai, Yunpeng Liu, Hong Qin, Mingzhen Guo, Zhigang Front Public Health Public Health BACKGROUND: Our goal was to create a prediction model for in-hospital death in Chinese patients with acute type A aortic dissection (ATAAD). METHODS: A retrospective derivation cohort was made up of 340 patients with ATAAD from Tianjin, and the retrospective validation cohort was made up of 153 patients with ATAAD from Nanjing. For variable selection, we used least absolute shrinkage and selection operator analysis, and for risk scoring, we used logistic regression coefficients. We categorized the patients into low-, middle-, and high-risk groups and looked into the correlation with in-hospital fatalities. We established a risk classifier based on independent baseline data using a multivariable logistic model. The prediction performance was determined based on the receiver operating characteristic curve (ROC). Individualized clinical decision-making was conducted by weighing the net benefit in each patient by decision curve analysis (DCA). RESULTS: We created a risk prediction model using risk scores weighted by five preoperatively chosen variables [AUC: 0.7039 (95% CI, 0.643–0.765)]: serum creatinine (Scr), D-dimer, white blood cell (WBC) count, coronary heart disease (CHD), and blood urea nitrogen (BUN). Following that, we categorized the cohort's patients as low-, intermediate-, and high-risk groups. The intermediate- and high-risk groups significantly increased hospital death rates compared to the low-risk group [adjusted OR: 3.973 (95% CI, 1.496–10.552), P < 0.01; 8.280 (95% CI, 3.054–22.448), P < 0.01, respectively). The risk score classifier exhibited better prediction ability than the triple-risk categories classifier [AUC: 0.7039 (95% CI, 0.6425–0.7652) vs. 0.6605 (95% CI, 0.6013–0.7197); P = 0.0022]. The DCA showed relatively good performance for the model in terms of clinical application if the threshold probability in the clinical decision was more than 10%. CONCLUSION: A risk classifier is an effective strategy for predicting in-hospital death in patients with ATAAD, but it might be affected by the small number of participants. Frontiers Media S.A. 2023-03-29 /pmc/articles/PMC10090540/ /pubmed/37064704 http://dx.doi.org/10.3389/fpubh.2023.1143160 Text en Copyright © 2023 Chen, Bai, Liu, Qin and Guo. 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 Public Health
Chen, Junquan
Bai, Yunpeng
Liu, Hong
Qin, Mingzhen
Guo, Zhigang
Prediction of in-hospital death following acute type A aortic dissection
title Prediction of in-hospital death following acute type A aortic dissection
title_full Prediction of in-hospital death following acute type A aortic dissection
title_fullStr Prediction of in-hospital death following acute type A aortic dissection
title_full_unstemmed Prediction of in-hospital death following acute type A aortic dissection
title_short Prediction of in-hospital death following acute type A aortic dissection
title_sort prediction of in-hospital death following acute type a aortic dissection
topic Public Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10090540/
https://www.ncbi.nlm.nih.gov/pubmed/37064704
http://dx.doi.org/10.3389/fpubh.2023.1143160
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