首页|University of Medicine and Pharmacy Reports Findings in Cerebral Hemorrhage (Fac tors associated with 90-day mortality in Vietnamese stroke patients: Prospective findings compared with explainable machine learning, multicenter study)
University of Medicine and Pharmacy Reports Findings in Cerebral Hemorrhage (Fac tors associated with 90-day mortality in Vietnamese stroke patients: Prospective findings compared with explainable machine learning, multicenter study)
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New research on Central Nervous System Diseases and Conditions -Cerebral Hemorrhage is the subject of a report. Accor ding to news originating from Ho Chi Minh City, Vietnam, by NewsRx correspondent s, research stated, "The prevalence and predictors of mortality following an isc hemic stroke or intracerebral hemorrhage have not been well established among pa tients in Vietnam. 2885 consecutive diagnosed patients with ischemic stroke and intracerebral hemorrhage at ten stroke centres across Vietnam were involved in t his prospective study. Posthoc analyses were performed in 2209 subjects (age was 65.4 ? 13.7 years, with 61.4% being male) to explore the clinical characteristics and prognostic factors associated with 90-day mortality followi ng treatment." Our news journalists obtained a quote from the research from the University of M edicine and Pharmacy, "An explainable machine learning model using extreme gradi ent boosting and SHapley Additive exPlanations revealed the correlation between original clinical research and advanced machine learning methods in stroke care. In the 90 days following treatment, the mortality rate for ischemic stroke was 8.2 %, while for intracerebral hemorrhage, it was higher at 20.5% . Atrial fibrillation was an elevated risk of 90-day mortality in the ischemic s troke patient (OR 3.09; 95% CI 1.90-5.02, p<0 .001). Among patients with intracerebral hemorrhage, there was no statistical si gnificance in those with hypertension compared to their counterparts without hyp ertension (OR 0.65, 95% CI 0.41-1.03, p> 0 .05). The baseline NIHSS score was a significant predictor of 90-day mortality i n both patient groups. The machine learning model can predict a 0.91 accuracy pr ediction of death rate after 90 days. Age and NIHSS score were in the top high r isks with other features, such as consciousness, heart rate, and white blood cel ls."
Ho Chi Minh CityVietnamAsiaCentral Nervous System Diseases and ConditionsCerebral HemorrhageCerebrovascular Di seases and ConditionsCyborgsEmerging TechnologiesHealth and MedicineMach ine LearningStroke
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