Vazquez Sima, Jain Aarti K, Nolan Bridget, Spirollari Eris, Clare Kevin, Thomas Anish, Soldozy Sauson, Ali Syed, Sukul Vishad, Rosenberg Jon, Mayer Stephan, Khatri Rakesh, Jankowitz Brian T, Singer Justin, Gandhi Chirag, Al-Mufti Fawaz
School of Medicine, New York Medical College, Valhalla, NY 10595, USA.
Department of Neurosurgery, Westchester Medical Center, Valhalla, NY 10595, USA.
Life (Basel). 2024 Aug 22;14(8):1049. doi: 10.3390/life14081049.
As the incidence of subdural hematoma is increasing, it is important to understand symptomatology and clinical variables associated with treatment outcomes and mortality in this population; patients with subdural hematoma were selected from the National Inpatient Sample (NIS) Database between 2016 and 2020 using International Classification of Disease 10th Edition (ICD10) codes. Moderate-to-severe subdural hematoma patients were identified using the Glasgow Coma Scale (GCS). Multivariate regression was first used to identify predictors of in-hospital mortality and then beta coefficients were used to create a weighted mortality score. Of 29,915 patients admitted with moderate-to-severe subdural hematomas, 12,135 (40.6%) died within the same hospital admission. In a multivariate model of relevant demographic and clinical covariates, age greater than 70, diabetes mellitus, mechanical ventilation, hydrocephalus, and herniation were independent predictors of mortality ( < 0.001 for all). Age greater than 70, diabetes mellitus, mechanical ventilation, hydrocephalus, and herniation were assigned a "1" in a weighted mortality score. The ROC curve for our model showed an area under the curve of 0.64. Age greater than 70, diabetes mellitus, mechanical ventilation, hydrocephalus, and herniation were predictive of mortality. We created the first clinically relevant weighted mortality score that can be used to stratify risk, guide prognosis, and inform family discussions.
随着硬膜下血肿的发病率不断上升,了解该人群中与治疗结果和死亡率相关的症状学及临床变量至关重要;2016年至2020年间,使用国际疾病分类第10版(ICD10)编码从国家住院样本(NIS)数据库中选取硬膜下血肿患者。使用格拉斯哥昏迷量表(GCS)识别中重度硬膜下血肿患者。首先采用多因素回归确定院内死亡率的预测因素,然后使用β系数创建加权死亡率评分。在29915例中重度硬膜下血肿入院患者中,12135例(40.6%)在同一住院期间死亡。在相关人口统计学和临床协变量的多因素模型中,年龄大于70岁、糖尿病、机械通气、脑积水和脑疝是死亡率的独立预测因素(所有P均<0.001)。在加权死亡率评分中,年龄大于70岁、糖尿病、机械通气、脑积水和脑疝赋值为“1”。我们模型的ROC曲线显示曲线下面积为0.64。年龄大于70岁、糖尿病、机械通气、脑积水和脑疝可预测死亡率。我们创建了首个具有临床相关性的加权死亡率评分,可用于风险分层、指导预后并为家属讨论提供信息。