Clinical Prediction Model for Screening Acute Ischemic Stroke Patients With More Than 10 Cerebral Microbleeds
BackgroundHemorrhagic transformation is one of the most serious complications in intravenous thrombolysis. Studies show that the existence of more than 10 cerebral microbleeds is strongly associated with hemorrhagic transformation. The current study attempts to develop and validate a clinical predic...
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| Format: | Article |
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Frontiers Media S.A.
2022-04-01
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| Series: | Frontiers in Neurology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fneur.2022.833952/full |
| _version_ | 1818394157228490752 |
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| author | Yifan Li Haifeng Gao Dongsen Zhang Xuan Gao Lin Lu Chunqin Liu Qian Li Chunzhi Miao Hongying Ma Yongqiu Li |
| author_facet | Yifan Li Haifeng Gao Dongsen Zhang Xuan Gao Lin Lu Chunqin Liu Qian Li Chunzhi Miao Hongying Ma Yongqiu Li |
| author_sort | Yifan Li |
| collection | DOAJ |
| description | BackgroundHemorrhagic transformation is one of the most serious complications in intravenous thrombolysis. Studies show that the existence of more than 10 cerebral microbleeds is strongly associated with hemorrhagic transformation. The current study attempts to develop and validate a clinical prediction model of more than 10 cerebral microbleeds.MethodsWe reviewed the computed tomography markers of cerebral small vessel diseases and the basic clinical information of acute ischemic stroke patients who were investigated using susceptibility weighted imaging from 2018 to 2021. A clinical prediction model of more than 10 cerebral microbleeds was established. Discrimination, calibration, and the net benefit of the model were assessed. Finally, a validation was conducted to evaluate the accuracy and stability of the model.ResultsThe multivariate logistic regression model showed hypertension, and some computed tomography markers (leukoaraiosis, lacunar infarctions, brain atrophy) were independent risk factors of more than 10 cerebral microbleeds. These risk factors were used for establishing the clinical prediction model. The area under the receiver operating characteristic curve (AUC) was 0.894 (95% CI: 0.870–0.919); Hosmer–Lemeshow chi-squared test yielded χ2 = 3.946 (P = 0.862). The clinical decision cure of the model was higher than the two extreme lines. The simplified score of the model ranged from 0 to 12. The model in the internal and external validation cohort also had good discrimination (AUC 0.902, 95% CI: 0.868–0.937; AUC 0.914, 95% CI: 0.882–0.945) and calibration (P = 0.157, 0.247), and patients gained a net benefit from the model.ConclusionsWe developed and validated a simple scoring tool for acute ischemic stroke patients with more than 10 cerebral microbleeds; this tool may be beneficial for paradigm decision regarding intravenous recombinant tissue plasminogen activator therapy of acute ischemic stroke. |
| first_indexed | 2024-12-14T05:56:44Z |
| format | Article |
| id | doaj.art-e97c95fadf4b46c0aba56fbf3012120b |
| institution | Directory Open Access Journal |
| issn | 1664-2295 |
| language | English |
| last_indexed | 2024-12-14T05:56:44Z |
| publishDate | 2022-04-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Neurology |
| spelling | doaj.art-e97c95fadf4b46c0aba56fbf3012120b2022-12-21T23:14:33ZengFrontiers Media S.A.Frontiers in Neurology1664-22952022-04-011310.3389/fneur.2022.833952833952Clinical Prediction Model for Screening Acute Ischemic Stroke Patients With More Than 10 Cerebral MicrobleedsYifan Li0Haifeng Gao1Dongsen Zhang2Xuan Gao3Lin Lu4Chunqin Liu5Qian Li6Chunzhi Miao7Hongying Ma8Yongqiu Li9Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, ChinaDepartment of Neurology, Tangshan Gongren Hospital, Tangshan, ChinaDepartment of Neurology, Tangshan Gongren Hospital, Tangshan, ChinaDepartment of Neurology, Tangshan Gongren Hospital, Tangshan, ChinaDepartment of Neurology, Tangshan Gongren Hospital, Tangshan, ChinaDepartment of Neurology, Tangshan Gongren Hospital, Tangshan, ChinaDepartment of Neurology, Tangshan Gongren Hospital, Tangshan, ChinaDepartment of Neurology, Tangshan Gongren Hospital, Tangshan, ChinaDepartment of Neurology, Tangshan Gongren Hospital, Tangshan, ChinaDepartment of Neurology, Tangshan Gongren Hospital, Tangshan, ChinaBackgroundHemorrhagic transformation is one of the most serious complications in intravenous thrombolysis. Studies show that the existence of more than 10 cerebral microbleeds is strongly associated with hemorrhagic transformation. The current study attempts to develop and validate a clinical prediction model of more than 10 cerebral microbleeds.MethodsWe reviewed the computed tomography markers of cerebral small vessel diseases and the basic clinical information of acute ischemic stroke patients who were investigated using susceptibility weighted imaging from 2018 to 2021. A clinical prediction model of more than 10 cerebral microbleeds was established. Discrimination, calibration, and the net benefit of the model were assessed. Finally, a validation was conducted to evaluate the accuracy and stability of the model.ResultsThe multivariate logistic regression model showed hypertension, and some computed tomography markers (leukoaraiosis, lacunar infarctions, brain atrophy) were independent risk factors of more than 10 cerebral microbleeds. These risk factors were used for establishing the clinical prediction model. The area under the receiver operating characteristic curve (AUC) was 0.894 (95% CI: 0.870–0.919); Hosmer–Lemeshow chi-squared test yielded χ2 = 3.946 (P = 0.862). The clinical decision cure of the model was higher than the two extreme lines. The simplified score of the model ranged from 0 to 12. The model in the internal and external validation cohort also had good discrimination (AUC 0.902, 95% CI: 0.868–0.937; AUC 0.914, 95% CI: 0.882–0.945) and calibration (P = 0.157, 0.247), and patients gained a net benefit from the model.ConclusionsWe developed and validated a simple scoring tool for acute ischemic stroke patients with more than 10 cerebral microbleeds; this tool may be beneficial for paradigm decision regarding intravenous recombinant tissue plasminogen activator therapy of acute ischemic stroke.https://www.frontiersin.org/articles/10.3389/fneur.2022.833952/fullcerebral microbleedsprediction modelcerebral small vessel diseaseintravenous thrombolysishemorrhagic transformation |
| spellingShingle | Yifan Li Haifeng Gao Dongsen Zhang Xuan Gao Lin Lu Chunqin Liu Qian Li Chunzhi Miao Hongying Ma Yongqiu Li Clinical Prediction Model for Screening Acute Ischemic Stroke Patients With More Than 10 Cerebral Microbleeds Frontiers in Neurology cerebral microbleeds prediction model cerebral small vessel disease intravenous thrombolysis hemorrhagic transformation |
| title | Clinical Prediction Model for Screening Acute Ischemic Stroke Patients With More Than 10 Cerebral Microbleeds |
| title_full | Clinical Prediction Model for Screening Acute Ischemic Stroke Patients With More Than 10 Cerebral Microbleeds |
| title_fullStr | Clinical Prediction Model for Screening Acute Ischemic Stroke Patients With More Than 10 Cerebral Microbleeds |
| title_full_unstemmed | Clinical Prediction Model for Screening Acute Ischemic Stroke Patients With More Than 10 Cerebral Microbleeds |
| title_short | Clinical Prediction Model for Screening Acute Ischemic Stroke Patients With More Than 10 Cerebral Microbleeds |
| title_sort | clinical prediction model for screening acute ischemic stroke patients with more than 10 cerebral microbleeds |
| topic | cerebral microbleeds prediction model cerebral small vessel disease intravenous thrombolysis hemorrhagic transformation |
| url | https://www.frontiersin.org/articles/10.3389/fneur.2022.833952/full |
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