Semantic Visualization in Functional Recovery Prediction of Intravenous Thrombolysis following Acute Ischemic Stroke in Patients by Using Biostatistics: An Exploratory Study
(1) Background: Intravenous thrombolysis following acute ischemic stroke (AIS) can reduce disability and increase the survival rate. We designed a functional recovery analysis by using semantic visualization to predict the recovery probability in AIS patients receiving intravenous thrombolysis; (2)...
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MDPI AG
2023-04-01
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| Series: | Journal of Personalized Medicine |
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| Online Access: | https://www.mdpi.com/2075-4426/13/4/624 |
| _version_ | 1797604772298096640 |
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| author | Chih-Chun Hsiao Chun-Gu Cheng Cheng-Chueh Chen Hung-Wen Chiu Hui-Chen Lin Chun-An Cheng |
| author_facet | Chih-Chun Hsiao Chun-Gu Cheng Cheng-Chueh Chen Hung-Wen Chiu Hui-Chen Lin Chun-An Cheng |
| author_sort | Chih-Chun Hsiao |
| collection | DOAJ |
| description | (1) Background: Intravenous thrombolysis following acute ischemic stroke (AIS) can reduce disability and increase the survival rate. We designed a functional recovery analysis by using semantic visualization to predict the recovery probability in AIS patients receiving intravenous thrombolysis; (2) Methods: We enrolled 131 AIS patients undergoing intravenous thrombolysis from 2011 to 2015 at the Medical Center in northern Taiwan. An additional 54 AIS patients were enrolled from another community hospital. A modified Rankin Score ≤2 after 3 months of follow-up was defined as favorable recovery. We used multivariable logistic regression with forward selection to construct a nomogram; (3) Results: The model included age and the National Institutes of Health Stroke Scale (NIHSS) score as immediate pretreatment parameters. A 5.23% increase in the functional recovery probability occurred for every 1-year reduction in age, and a 13.57% increase in the functional recovery probability occurred for every NIHSS score reduction. The sensitivity, specificity, and accuracy of the model in the validation dataset were 71.79%, 86.67%, and 75.93%, respectively, and the area under the receiver operating characteristic curve (AUC) was 0.867; (4) Conclusions: Semantic visualization-based functional recovery prediction models may help physicians assess the recovery probability before patients undergo emergency intravenous thrombolysis. |
| first_indexed | 2024-03-11T04:51:29Z |
| format | Article |
| id | doaj.art-e91f10d1ef6f404bad5f7d45c557e3e1 |
| institution | Directory Open Access Journal |
| issn | 2075-4426 |
| language | English |
| last_indexed | 2024-03-11T04:51:29Z |
| publishDate | 2023-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Personalized Medicine |
| spelling | doaj.art-e91f10d1ef6f404bad5f7d45c557e3e12023-11-17T19:59:46ZengMDPI AGJournal of Personalized Medicine2075-44262023-04-0113462410.3390/jpm13040624Semantic Visualization in Functional Recovery Prediction of Intravenous Thrombolysis following Acute Ischemic Stroke in Patients by Using Biostatistics: An Exploratory StudyChih-Chun Hsiao0Chun-Gu Cheng1Cheng-Chueh Chen2Hung-Wen Chiu3Hui-Chen Lin4Chun-An Cheng5Department of Nursing, Taoyuan Armed Forces General Hospital, Taoyuan 32549, TaiwanDepartment of Emergency Medicine, Taoyuan Armed Forces General Hospital, Taoyuan 32549, TaiwanDepartment of General Surgery, China Medical University Beigang Hospital, Yunlin 65152, TaiwanGraduate Institute of Medical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei 11031, TaiwanSchool of Nursing, College of Nursing, Taipei Medical University, Taipei 11031, TaiwanDepartment of Neurology, Tri-Service General Hospital, National Defense Medical Center, Taipei 11490, Taiwan(1) Background: Intravenous thrombolysis following acute ischemic stroke (AIS) can reduce disability and increase the survival rate. We designed a functional recovery analysis by using semantic visualization to predict the recovery probability in AIS patients receiving intravenous thrombolysis; (2) Methods: We enrolled 131 AIS patients undergoing intravenous thrombolysis from 2011 to 2015 at the Medical Center in northern Taiwan. An additional 54 AIS patients were enrolled from another community hospital. A modified Rankin Score ≤2 after 3 months of follow-up was defined as favorable recovery. We used multivariable logistic regression with forward selection to construct a nomogram; (3) Results: The model included age and the National Institutes of Health Stroke Scale (NIHSS) score as immediate pretreatment parameters. A 5.23% increase in the functional recovery probability occurred for every 1-year reduction in age, and a 13.57% increase in the functional recovery probability occurred for every NIHSS score reduction. The sensitivity, specificity, and accuracy of the model in the validation dataset were 71.79%, 86.67%, and 75.93%, respectively, and the area under the receiver operating characteristic curve (AUC) was 0.867; (4) Conclusions: Semantic visualization-based functional recovery prediction models may help physicians assess the recovery probability before patients undergo emergency intravenous thrombolysis.https://www.mdpi.com/2075-4426/13/4/624functional recoveryintravenous thrombolysisacute ischemic stroke |
| spellingShingle | Chih-Chun Hsiao Chun-Gu Cheng Cheng-Chueh Chen Hung-Wen Chiu Hui-Chen Lin Chun-An Cheng Semantic Visualization in Functional Recovery Prediction of Intravenous Thrombolysis following Acute Ischemic Stroke in Patients by Using Biostatistics: An Exploratory Study Journal of Personalized Medicine functional recovery intravenous thrombolysis acute ischemic stroke |
| title | Semantic Visualization in Functional Recovery Prediction of Intravenous Thrombolysis following Acute Ischemic Stroke in Patients by Using Biostatistics: An Exploratory Study |
| title_full | Semantic Visualization in Functional Recovery Prediction of Intravenous Thrombolysis following Acute Ischemic Stroke in Patients by Using Biostatistics: An Exploratory Study |
| title_fullStr | Semantic Visualization in Functional Recovery Prediction of Intravenous Thrombolysis following Acute Ischemic Stroke in Patients by Using Biostatistics: An Exploratory Study |
| title_full_unstemmed | Semantic Visualization in Functional Recovery Prediction of Intravenous Thrombolysis following Acute Ischemic Stroke in Patients by Using Biostatistics: An Exploratory Study |
| title_short | Semantic Visualization in Functional Recovery Prediction of Intravenous Thrombolysis following Acute Ischemic Stroke in Patients by Using Biostatistics: An Exploratory Study |
| title_sort | semantic visualization in functional recovery prediction of intravenous thrombolysis following acute ischemic stroke in patients by using biostatistics an exploratory study |
| topic | functional recovery intravenous thrombolysis acute ischemic stroke |
| url | https://www.mdpi.com/2075-4426/13/4/624 |
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