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Circulating biomarker-based risk stratifications individualize arch repair strategy of acute Type A aortic dissection via the XGBoosting algorithm

AIMS: The incremental usefulness of circulating biomarkers from different pathological pathways for predicting mortality has not been evaluated in acute Type A aortic dissection (ATAAD) patients. We aim to develop a risk prediction model and investigate the impact of arch repair strategy on mortalit...

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Autores principales: Liu, Hong, Qian, Si-Chong, Han, Lu, Zhang, Ying-Yuan, Wu, Ying, Hong, Liang, Yang, Ji-Nong, Zhong, Ji-Sheng, Wang, Yu-Qi, Wu, Dong-Kai, Fan, Guo-Liang, Chen, Jun-Quan, Zhang, Sheng-Qiang, Peng, Xing-Xing, Tang, Zhi-Wei, Hamzah, Al-Wajih, Shao, Yong-Feng, Li, Hai-Yang, Zhang, Hong-Jia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9779759/
https://www.ncbi.nlm.nih.gov/pubmed/36710897
http://dx.doi.org/10.1093/ehjdh/ztac068
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author Liu, Hong
Qian, Si-Chong
Han, Lu
Zhang, Ying-Yuan
Wu, Ying
Hong, Liang
Yang, Ji-Nong
Zhong, Ji-Sheng
Wang, Yu-Qi
Wu, Dong-Kai
Fan, Guo-Liang
Chen, Jun-Quan
Zhang, Sheng-Qiang
Peng, Xing-Xing
Tang, Zhi-Wei
Hamzah, Al-Wajih
Shao, Yong-Feng
Li, Hai-Yang
Zhang, Hong-Jia
author_facet Liu, Hong
Qian, Si-Chong
Han, Lu
Zhang, Ying-Yuan
Wu, Ying
Hong, Liang
Yang, Ji-Nong
Zhong, Ji-Sheng
Wang, Yu-Qi
Wu, Dong-Kai
Fan, Guo-Liang
Chen, Jun-Quan
Zhang, Sheng-Qiang
Peng, Xing-Xing
Tang, Zhi-Wei
Hamzah, Al-Wajih
Shao, Yong-Feng
Li, Hai-Yang
Zhang, Hong-Jia
author_sort Liu, Hong
collection PubMed
description AIMS: The incremental usefulness of circulating biomarkers from different pathological pathways for predicting mortality has not been evaluated in acute Type A aortic dissection (ATAAD) patients. We aim to develop a risk prediction model and investigate the impact of arch repair strategy on mortality based on distinct risk stratifications. METHODS AND RESULTS: A total of 3771 ATAAD patients who underwent aortic surgery retrospectively included were randomly divided into training and testing cohorts at a ratio of 7:3 for the development and validation of the risk model based on multiple circulating biomarkers and conventional clinical factors. Extreme gradient boosting was used to generate the risk models. Subgroup analyses were performed by risk stratifications (low vs. middle–high risk) and arch repair strategies (proximal vs. extensive arch repair). Addition of multiple biomarkers to a model with conventional factors fitted an ABC risk model consisting of platelet–leucocyte ratio, mean arterial pressure, albumin, age, creatinine, creatine kinase-MB, haemoglobin, lactate, left ventricular end-diastolic dimension, urea nitrogen, and aspartate aminotransferase, with adequate discrimination ability {area under the receiver operating characteristic curve (AUROC): 0.930 [95% confidence interval (CI) 0.906–0.954] and 0.954, 95% CI (0.930–0.977) in the derivation and validation cohort, respectively}. Compared with proximal arch repair, the extensive repair was associated with similar mortality risk among patients at low risk [odds ratio (OR) 1.838, 95% CI (0.559–6.038); P = 0.316], but associated with higher mortality risk among patients at middle–high risk [OR 2.007, 95% CI (1.460–2.757); P < 0.0001]. CONCLUSION: In ATAAD patients, the simultaneous addition of circulating biomarkers of inflammatory, cardiac, hepatic, renal, and metabolic abnormalities substantially improved risk stratification and individualized arch repair strategy.
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spelling pubmed-97797592023-01-27 Circulating biomarker-based risk stratifications individualize arch repair strategy of acute Type A aortic dissection via the XGBoosting algorithm Liu, Hong Qian, Si-Chong Han, Lu Zhang, Ying-Yuan Wu, Ying Hong, Liang Yang, Ji-Nong Zhong, Ji-Sheng Wang, Yu-Qi Wu, Dong-Kai Fan, Guo-Liang Chen, Jun-Quan Zhang, Sheng-Qiang Peng, Xing-Xing Tang, Zhi-Wei Hamzah, Al-Wajih Shao, Yong-Feng Li, Hai-Yang Zhang, Hong-Jia Eur Heart J Digit Health Original Article AIMS: The incremental usefulness of circulating biomarkers from different pathological pathways for predicting mortality has not been evaluated in acute Type A aortic dissection (ATAAD) patients. We aim to develop a risk prediction model and investigate the impact of arch repair strategy on mortality based on distinct risk stratifications. METHODS AND RESULTS: A total of 3771 ATAAD patients who underwent aortic surgery retrospectively included were randomly divided into training and testing cohorts at a ratio of 7:3 for the development and validation of the risk model based on multiple circulating biomarkers and conventional clinical factors. Extreme gradient boosting was used to generate the risk models. Subgroup analyses were performed by risk stratifications (low vs. middle–high risk) and arch repair strategies (proximal vs. extensive arch repair). Addition of multiple biomarkers to a model with conventional factors fitted an ABC risk model consisting of platelet–leucocyte ratio, mean arterial pressure, albumin, age, creatinine, creatine kinase-MB, haemoglobin, lactate, left ventricular end-diastolic dimension, urea nitrogen, and aspartate aminotransferase, with adequate discrimination ability {area under the receiver operating characteristic curve (AUROC): 0.930 [95% confidence interval (CI) 0.906–0.954] and 0.954, 95% CI (0.930–0.977) in the derivation and validation cohort, respectively}. Compared with proximal arch repair, the extensive repair was associated with similar mortality risk among patients at low risk [odds ratio (OR) 1.838, 95% CI (0.559–6.038); P = 0.316], but associated with higher mortality risk among patients at middle–high risk [OR 2.007, 95% CI (1.460–2.757); P < 0.0001]. CONCLUSION: In ATAAD patients, the simultaneous addition of circulating biomarkers of inflammatory, cardiac, hepatic, renal, and metabolic abnormalities substantially improved risk stratification and individualized arch repair strategy. Oxford University Press 2022-11-01 /pmc/articles/PMC9779759/ /pubmed/36710897 http://dx.doi.org/10.1093/ehjdh/ztac068 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of the European Society of Cardiology. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Original Article
Liu, Hong
Qian, Si-Chong
Han, Lu
Zhang, Ying-Yuan
Wu, Ying
Hong, Liang
Yang, Ji-Nong
Zhong, Ji-Sheng
Wang, Yu-Qi
Wu, Dong-Kai
Fan, Guo-Liang
Chen, Jun-Quan
Zhang, Sheng-Qiang
Peng, Xing-Xing
Tang, Zhi-Wei
Hamzah, Al-Wajih
Shao, Yong-Feng
Li, Hai-Yang
Zhang, Hong-Jia
Circulating biomarker-based risk stratifications individualize arch repair strategy of acute Type A aortic dissection via the XGBoosting algorithm
title Circulating biomarker-based risk stratifications individualize arch repair strategy of acute Type A aortic dissection via the XGBoosting algorithm
title_full Circulating biomarker-based risk stratifications individualize arch repair strategy of acute Type A aortic dissection via the XGBoosting algorithm
title_fullStr Circulating biomarker-based risk stratifications individualize arch repair strategy of acute Type A aortic dissection via the XGBoosting algorithm
title_full_unstemmed Circulating biomarker-based risk stratifications individualize arch repair strategy of acute Type A aortic dissection via the XGBoosting algorithm
title_short Circulating biomarker-based risk stratifications individualize arch repair strategy of acute Type A aortic dissection via the XGBoosting algorithm
title_sort circulating biomarker-based risk stratifications individualize arch repair strategy of acute type a aortic dissection via the xgboosting algorithm
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9779759/
https://www.ncbi.nlm.nih.gov/pubmed/36710897
http://dx.doi.org/10.1093/ehjdh/ztac068
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