Risk factors and a prediction model for the prognosis of intracerebral hemorrhage using cerebral microhemorrhage and clinical factors
BackgroundThis study aimed to identify the risk factors and construct a prediction model for the prognosis of intracerebral hemorrhage (ICH) at discharge, 3 months, and 12 months.MethodsA total of 269 patients with ICH were retrospectively enrolled at our hospital between January 2014 and August 201...
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Frontiers Media S.A.
2023-11-01
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| Series: | Frontiers in Neurology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fneur.2023.1268627/full |
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| author | Hao Feng Xin Wang Wenjuan Wang Xingquan Zhao Xingquan Zhao Xingquan Zhao Xingquan Zhao |
| author_facet | Hao Feng Xin Wang Wenjuan Wang Xingquan Zhao Xingquan Zhao Xingquan Zhao Xingquan Zhao |
| author_sort | Hao Feng |
| collection | DOAJ |
| description | BackgroundThis study aimed to identify the risk factors and construct a prediction model for the prognosis of intracerebral hemorrhage (ICH) at discharge, 3 months, and 12 months.MethodsA total of 269 patients with ICH were retrospectively enrolled at our hospital between January 2014 and August 2016. The prognosis of ICH was assessed using the modified Rankin Scale (mRS); an mRS score > 2 was considered a poor outcome. The primary endpoint was the 3-month mRS, whereas the secondary endpoints included the mRS scores at discharge and 12 months, and mortality.ResultsThe Glasgow Coma Scale (GCS), National Institutes of Health (NIH) stroke scale, International Normalized Ratio (INR), blood urea nitrogen (BUN), epencephalon hemorrhage, and primary hematoma volume were significantly associated with a poor mRS score at 3 months. The predictive value of the prediction model based on these factors for a poor mRS score was 87.8%. Furthermore, a poor mRS score at discharge was affected by the GCS, NIH stroke scale, and primary hematoma volume; the constructed model based on these factors had a predictive value of 87.6%. In addition, the GCS, NIH stroke scale, and surgery were significantly related to a poor mRS score at 12 months; the predictive value of the constructed model based on the aforementioned factors for a poor mRS score was 86.5%. Finally, primary hematoma volume is significantly associated with the risk of 12 months mortality.ConclusionsThe study identified risk factors and constructed a prediction model for poor mRS scores and mortality at discharge, 3 and 12 months in patients with ICH. The prediction models for mRS scores showed a relatively high predictive performance. |
| first_indexed | 2024-03-10T03:16:41Z |
| format | Article |
| id | doaj.art-9754ec50fef048f58f53cfc7079439ba |
| institution | Directory Open Access Journal |
| issn | 1664-2295 |
| language | English |
| last_indexed | 2024-03-10T03:16:41Z |
| publishDate | 2023-11-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Neurology |
| spelling | doaj.art-9754ec50fef048f58f53cfc7079439ba2023-11-23T10:11:38ZengFrontiers Media S.A.Frontiers in Neurology1664-22952023-11-011410.3389/fneur.2023.12686271268627Risk factors and a prediction model for the prognosis of intracerebral hemorrhage using cerebral microhemorrhage and clinical factorsHao Feng0Xin Wang1Wenjuan Wang2Xingquan Zhao3Xingquan Zhao4Xingquan Zhao5Xingquan Zhao6Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaDepartment of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaDepartment of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaDepartment of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaChina National Clinical Research Center for Neurological Diseases, Beijing, ChinaCenter of Stroke, Beijing Institute for Brain Disorders, Beijing, ChinaResearch Unit of Artificial Intelligence in Cerebrovascular Disease, Chinese Academy of Medical Sciences, Beijing, ChinaBackgroundThis study aimed to identify the risk factors and construct a prediction model for the prognosis of intracerebral hemorrhage (ICH) at discharge, 3 months, and 12 months.MethodsA total of 269 patients with ICH were retrospectively enrolled at our hospital between January 2014 and August 2016. The prognosis of ICH was assessed using the modified Rankin Scale (mRS); an mRS score > 2 was considered a poor outcome. The primary endpoint was the 3-month mRS, whereas the secondary endpoints included the mRS scores at discharge and 12 months, and mortality.ResultsThe Glasgow Coma Scale (GCS), National Institutes of Health (NIH) stroke scale, International Normalized Ratio (INR), blood urea nitrogen (BUN), epencephalon hemorrhage, and primary hematoma volume were significantly associated with a poor mRS score at 3 months. The predictive value of the prediction model based on these factors for a poor mRS score was 87.8%. Furthermore, a poor mRS score at discharge was affected by the GCS, NIH stroke scale, and primary hematoma volume; the constructed model based on these factors had a predictive value of 87.6%. In addition, the GCS, NIH stroke scale, and surgery were significantly related to a poor mRS score at 12 months; the predictive value of the constructed model based on the aforementioned factors for a poor mRS score was 86.5%. Finally, primary hematoma volume is significantly associated with the risk of 12 months mortality.ConclusionsThe study identified risk factors and constructed a prediction model for poor mRS scores and mortality at discharge, 3 and 12 months in patients with ICH. The prediction models for mRS scores showed a relatively high predictive performance.https://www.frontiersin.org/articles/10.3389/fneur.2023.1268627/fullrisk factorsprediction modelprognosisintracerebral hemorrhagecerebral microhemorrhage |
| spellingShingle | Hao Feng Xin Wang Wenjuan Wang Xingquan Zhao Xingquan Zhao Xingquan Zhao Xingquan Zhao Risk factors and a prediction model for the prognosis of intracerebral hemorrhage using cerebral microhemorrhage and clinical factors Frontiers in Neurology risk factors prediction model prognosis intracerebral hemorrhage cerebral microhemorrhage |
| title | Risk factors and a prediction model for the prognosis of intracerebral hemorrhage using cerebral microhemorrhage and clinical factors |
| title_full | Risk factors and a prediction model for the prognosis of intracerebral hemorrhage using cerebral microhemorrhage and clinical factors |
| title_fullStr | Risk factors and a prediction model for the prognosis of intracerebral hemorrhage using cerebral microhemorrhage and clinical factors |
| title_full_unstemmed | Risk factors and a prediction model for the prognosis of intracerebral hemorrhage using cerebral microhemorrhage and clinical factors |
| title_short | Risk factors and a prediction model for the prognosis of intracerebral hemorrhage using cerebral microhemorrhage and clinical factors |
| title_sort | risk factors and a prediction model for the prognosis of intracerebral hemorrhage using cerebral microhemorrhage and clinical factors |
| topic | risk factors prediction model prognosis intracerebral hemorrhage cerebral microhemorrhage |
| url | https://www.frontiersin.org/articles/10.3389/fneur.2023.1268627/full |
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