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Predicting mortality in acute ischaemic stroke treated with mechanical thrombectomy: analysis of a multicentre prospective registry

OBJECTIVES: We aimed to determine predictors of mortality within 90 days and develop a simple score for patients with mechanical thrombectomy (MT). DESIGN: Analysis of a multicentre prospective registry. SETTING: In six participating centres, patients who had an acute ischaemic stroke (AIS) treated...

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Autores principales: Li, Hao, Ye, Shi-sheng, Wu, Yuan-Ling, Huang, Sheng-Ming, Li, Yong-Xin, Lu, Kui, Huang, Jing-Bo, Chen, Lve, Li, Hong-Zhuang, Wu, Wen-Jun, Wu, Zhi-Lin, Wu, Jian-Zhou, Zhong, Wang-Tao, Xian, Wen-Chuan, Liao, Feng, Tung, Tao-Hsin, Wu, Qiao-Ling, Chen, Hai, Yuan, Li, Yang, Zhi, Huang, Li-An
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8021751/
https://www.ncbi.nlm.nih.gov/pubmed/33795300
http://dx.doi.org/10.1136/bmjopen-2020-043415
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author Li, Hao
Ye, Shi-sheng
Wu, Yuan-Ling
Huang, Sheng-Ming
Li, Yong-Xin
Lu, Kui
Huang, Jing-Bo
Chen, Lve
Li, Hong-Zhuang
Wu, Wen-Jun
Wu, Zhi-Lin
Wu, Jian-Zhou
Zhong, Wang-Tao
Xian, Wen-Chuan
Liao, Feng
Tung, Tao-Hsin
Wu, Qiao-Ling
Chen, Hai
Yuan, Li
Yang, Zhi
Huang, Li-An
author_facet Li, Hao
Ye, Shi-sheng
Wu, Yuan-Ling
Huang, Sheng-Ming
Li, Yong-Xin
Lu, Kui
Huang, Jing-Bo
Chen, Lve
Li, Hong-Zhuang
Wu, Wen-Jun
Wu, Zhi-Lin
Wu, Jian-Zhou
Zhong, Wang-Tao
Xian, Wen-Chuan
Liao, Feng
Tung, Tao-Hsin
Wu, Qiao-Ling
Chen, Hai
Yuan, Li
Yang, Zhi
Huang, Li-An
author_sort Li, Hao
collection PubMed
description OBJECTIVES: We aimed to determine predictors of mortality within 90 days and develop a simple score for patients with mechanical thrombectomy (MT). DESIGN: Analysis of a multicentre prospective registry. SETTING: In six participating centres, patients who had an acute ischaemic stroke (AIS) treated by MT between March 2017 and May 2018 were documented prospectively. PARTICIPANTS: 224 patients with AIS were treated by MT. RESULTS: Of 224 patients, 49 (21.9%) patients died, and 87 (38.8%) were independent. Variables associated with 90-day mortality were age, previous stroke, admission National Institutes of Health Stroke Scale (NIHSS), fasting blood glucose and occlusion site. Logistic regression identified four variables independently associated with 90-day mortality: age ≥80 years (OR 3.26, 95% CI 1.45 to 7.33), previous stroke (OR 2.33, 95% CI 1.04 to 5.21), admission NIHSS ≥18 (OR 2.37, 95% CI 1.13 to 4.99) and internal carotid artery or basilar artery occlusion (OR 2.92, 95% CI 1.34 to 6.40). Using these data, we developed predicting 90-day mortality of AIS with MT (PRACTICE) score ranging from 0 to 6 points. The receiver operator curve analysis found that PRACTICE score (area under the curve (AUC)=0.744, 95% CI 0.669 to 0.820) was numerically better than iScore (AUC=0.661, 95% CI 0.577 to 0.745) and Predicting Early Mortality of Ischemic Stroke score (AUC=0.638, 95% CI 0.551 to 0.725) for predicting 90-day mortality. CONCLUSIONS: We developed a simple score to estimate the 90-day mortality of patients who had an AIS treated with MT. But the score needs to be prospectively validated. TRIAL REGISTRATION NUMBER: Chinese Clinical Trial Registry (ChiCTR-OOC-17013052).
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spelling pubmed-80217512021-04-26 Predicting mortality in acute ischaemic stroke treated with mechanical thrombectomy: analysis of a multicentre prospective registry Li, Hao Ye, Shi-sheng Wu, Yuan-Ling Huang, Sheng-Ming Li, Yong-Xin Lu, Kui Huang, Jing-Bo Chen, Lve Li, Hong-Zhuang Wu, Wen-Jun Wu, Zhi-Lin Wu, Jian-Zhou Zhong, Wang-Tao Xian, Wen-Chuan Liao, Feng Tung, Tao-Hsin Wu, Qiao-Ling Chen, Hai Yuan, Li Yang, Zhi Huang, Li-An BMJ Open Neurology OBJECTIVES: We aimed to determine predictors of mortality within 90 days and develop a simple score for patients with mechanical thrombectomy (MT). DESIGN: Analysis of a multicentre prospective registry. SETTING: In six participating centres, patients who had an acute ischaemic stroke (AIS) treated by MT between March 2017 and May 2018 were documented prospectively. PARTICIPANTS: 224 patients with AIS were treated by MT. RESULTS: Of 224 patients, 49 (21.9%) patients died, and 87 (38.8%) were independent. Variables associated with 90-day mortality were age, previous stroke, admission National Institutes of Health Stroke Scale (NIHSS), fasting blood glucose and occlusion site. Logistic regression identified four variables independently associated with 90-day mortality: age ≥80 years (OR 3.26, 95% CI 1.45 to 7.33), previous stroke (OR 2.33, 95% CI 1.04 to 5.21), admission NIHSS ≥18 (OR 2.37, 95% CI 1.13 to 4.99) and internal carotid artery or basilar artery occlusion (OR 2.92, 95% CI 1.34 to 6.40). Using these data, we developed predicting 90-day mortality of AIS with MT (PRACTICE) score ranging from 0 to 6 points. The receiver operator curve analysis found that PRACTICE score (area under the curve (AUC)=0.744, 95% CI 0.669 to 0.820) was numerically better than iScore (AUC=0.661, 95% CI 0.577 to 0.745) and Predicting Early Mortality of Ischemic Stroke score (AUC=0.638, 95% CI 0.551 to 0.725) for predicting 90-day mortality. CONCLUSIONS: We developed a simple score to estimate the 90-day mortality of patients who had an AIS treated with MT. But the score needs to be prospectively validated. TRIAL REGISTRATION NUMBER: Chinese Clinical Trial Registry (ChiCTR-OOC-17013052). BMJ Publishing Group 2021-04-01 /pmc/articles/PMC8021751/ /pubmed/33795300 http://dx.doi.org/10.1136/bmjopen-2020-043415 Text en © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Neurology
Li, Hao
Ye, Shi-sheng
Wu, Yuan-Ling
Huang, Sheng-Ming
Li, Yong-Xin
Lu, Kui
Huang, Jing-Bo
Chen, Lve
Li, Hong-Zhuang
Wu, Wen-Jun
Wu, Zhi-Lin
Wu, Jian-Zhou
Zhong, Wang-Tao
Xian, Wen-Chuan
Liao, Feng
Tung, Tao-Hsin
Wu, Qiao-Ling
Chen, Hai
Yuan, Li
Yang, Zhi
Huang, Li-An
Predicting mortality in acute ischaemic stroke treated with mechanical thrombectomy: analysis of a multicentre prospective registry
title Predicting mortality in acute ischaemic stroke treated with mechanical thrombectomy: analysis of a multicentre prospective registry
title_full Predicting mortality in acute ischaemic stroke treated with mechanical thrombectomy: analysis of a multicentre prospective registry
title_fullStr Predicting mortality in acute ischaemic stroke treated with mechanical thrombectomy: analysis of a multicentre prospective registry
title_full_unstemmed Predicting mortality in acute ischaemic stroke treated with mechanical thrombectomy: analysis of a multicentre prospective registry
title_short Predicting mortality in acute ischaemic stroke treated with mechanical thrombectomy: analysis of a multicentre prospective registry
title_sort predicting mortality in acute ischaemic stroke treated with mechanical thrombectomy: analysis of a multicentre prospective registry
topic Neurology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8021751/
https://www.ncbi.nlm.nih.gov/pubmed/33795300
http://dx.doi.org/10.1136/bmjopen-2020-043415
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