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Precise Thrombolytic Treatment for Stroke Using AI-based Algorithms: a Real-world Study

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Title: Precise Thrombolytic Treatment for Stroke Using AI-based Algorithms: a Real-world Study
Authors: SHEN Huiwen, LIN Yongzhong, CHEN Shuliang, ZHANG Lihong, MA Chunye, MA Deyuan, ZHANG Ce
Source: Zhongguo quanke yixue, Vol 26, Iss 17, Pp 2070-2077 (2023)
Publisher Information: Chinese General Practice Publishing House Co., Ltd, 2023.
Publication Year: 2023
Collection: LCC:Medicine
Subject Terms: ischemic stroke, thrombolytic drugs, artificial intelligence algorithm, wide&deep model, precision treatment, Medicine
More Details: Background The thrombolytic effect for ischemic stroke (IS) is affected by complex factors, such as acute onset of stroke, short therapeutic time window, various individual patient factors, treatment model, types and doses of medicines as well as mode of administration. To identify the influencing factors of thrombolytic effect, most existing studies adopt statistical methods, while rare studies use artificial intelligence (AI) -based algorithms.Objective To establish models using AI-based algorithms for IS patients based on the real-world data including general patient characteristics, medication model and recovery effects, to achieve precise individualized thrombolytic treatment and provide data support for clinical prescription decisions.Methods A retrospective design was used. The clinical information of IS patients (n=55 621) was extracted from the Yidu Cloud scientific research big data server system of the Second Affiliated Hospital of Dalian Medical University from January 1, 2001 to December 31, 2021, among whom 1 855 with complete information were enrolled according to the inclusion criteria. Thrombolysis effect was evaluated by comparing the National Institutes of Health Stroke Scale (NIHSS) score measured at admission and discharge, and those with an improvement in the NIHSS score by ≥4 points and
Document Type: article
File Description: electronic resource
Language: Chinese
ISSN: 1007-9572
Relation: https://www.chinagp.net/fileup/1007-9572/PDF/20230048.pdf; https://doaj.org/toc/1007-9572
DOI: 10.12114/j.issn.1007-9572.2023.0048
Access URL: https://doaj.org/article/6be311967d844906b1b4876120974852
Accession Number: edsdoj.6be311967d844906b1b4876120974852
Database: Directory of Open Access Journals
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  Data: Zhongguo quanke yixue, Vol 26, Iss 17, Pp 2070-2077 (2023)
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  Data: Chinese General Practice Publishing House Co., Ltd, 2023.
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  Data: 2023
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  Data: <searchLink fieldCode="DE" term="%22ischemic+stroke%22">ischemic stroke</searchLink><br /><searchLink fieldCode="DE" term="%22thrombolytic+drugs%22">thrombolytic drugs</searchLink><br /><searchLink fieldCode="DE" term="%22artificial+intelligence+algorithm%22">artificial intelligence algorithm</searchLink><br /><searchLink fieldCode="DE" term="%22wide%26deep+model%22">wide&deep model</searchLink><br /><searchLink fieldCode="DE" term="%22precision+treatment%22">precision treatment</searchLink><br /><searchLink fieldCode="DE" term="%22Medicine%22">Medicine</searchLink>
– Name: Abstract
  Label: Description
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  Data: Background The thrombolytic effect for ischemic stroke (IS) is affected by complex factors, such as acute onset of stroke, short therapeutic time window, various individual patient factors, treatment model, types and doses of medicines as well as mode of administration. To identify the influencing factors of thrombolytic effect, most existing studies adopt statistical methods, while rare studies use artificial intelligence (AI) -based algorithms.Objective To establish models using AI-based algorithms for IS patients based on the real-world data including general patient characteristics, medication model and recovery effects, to achieve precise individualized thrombolytic treatment and provide data support for clinical prescription decisions.Methods A retrospective design was used. The clinical information of IS patients (n=55 621) was extracted from the Yidu Cloud scientific research big data server system of the Second Affiliated Hospital of Dalian Medical University from January 1, 2001 to December 31, 2021, among whom 1 855 with complete information were enrolled according to the inclusion criteria. Thrombolysis effect was evaluated by comparing the National Institutes of Health Stroke Scale (NIHSS) score measured at admission and discharge, and those with an improvement in the NIHSS score by ≥4 points and
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      – Text: Chinese
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        PageCount: 8
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    Subjects:
      – SubjectFull: ischemic stroke
        Type: general
      – SubjectFull: thrombolytic drugs
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      – SubjectFull: artificial intelligence algorithm
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