Department of Neurosurgery, Beijing Tian Tan Hospital, Capital Medical University, Beijing, People's Republic of China; China National Clinical Research Center for Neurological Diseases, Beijing, People's Republic of China; Beijing Key Laboratory of Central Nervous System Injury, Beijing, People's Republic of China; Neurotrauma Laboratory, Beijing Neurosurgical Institute, Capital Medical University, Beijing, People's Republic of China.
Department of Neurosurgery, Beijing Tian Tan Hospital, Capital Medical University, Beijing, People's Republic of China; China National Clinical Research Center for Neurological Diseases, Beijing, People's Republic of China; Beijing Key Laboratory of Central Nervous System Injury, Beijing, People's Republic of China.
World Neurosurg. 2019 Jun;126:e101-e108. doi: 10.1016/j.wneu.2019.01.246. Epub 2019 Feb 18.
Although several prognostic factors for traumatic brain injury (TBI) have been evaluated, a useful predictive scoring model for the outcomes has not been developed for patients with severe TBI who undergo decompressive craniectomy (DC). The aim of the present study was to determine independent predictors and develop a multivariate logistic regression equation to predict the early outcome and discharge status for patients with severe TBI who have undergone DC.
A total of 13 different variables were evaluated. The data from all 278 patients with severe TBI who had undergone DC in the present study were retrospectively evaluated from July 2011 to June 2017. Using univariate, multiple logistic regression and prognostic regression scoring equations it was possible to draw receiver operating characteristic curves to predict the early outcomes and discharge status after TBI.
We found that younger age (P = 0.012), no significant medical history (P = 0.044), diameter of both pupils <4 mm (P = 0.032), higher admission Glasgow coma scale score (P = 0.004), no tracheotomy (P < 0.001), and DC for severe TBI were associated with a favorable early outcome and discharge status. Using receiver operating characteristic curves to predict the probability of a favorable outcome, the sensitivity was 80.0% and the specificity was 79.5%.
Our preliminary findings have shown that 5 variables can be used as independent predictors in assessing the early outcome and discharge status for patients with severe TBI after DC.
尽管已经评估了几种创伤性脑损伤（TBI）的预后因素，但对于接受去骨瓣减压术（DC）的重度 TBI 患者，尚未建立有用的预测评分模型来预测其结局。本研究的目的是确定独立的预测因素，并建立多元逻辑回归方程来预测接受 DC 的重度 TBI 患者的早期结局和出院状况。
共评估了 13 个不同的变量。本研究回顾性评估了 2011 年 7 月至 2017 年 6 月期间接受 DC 的 278 例重度 TBI 患者的所有数据。使用单变量、多因素逻辑回归和预后回归评分方程，可以绘制受试者工作特征曲线来预测 TBI 后的早期结局和出院状况。
我们发现，年龄较小（P=0.012）、无明显病史（P=0.044）、双侧瞳孔直径<4mm（P=0.032）、入院格拉斯哥昏迷量表评分较高（P=0.004）、未行气管切开术（P<0.001）和 DC 治疗重度 TBI 与良好的早期结局和出院状况相关。使用受试者工作特征曲线预测良好结局的概率，敏感性为 80.0%，特异性为 79.5%。
我们的初步研究结果表明，5 个变量可作为评估接受 DC 的重度 TBI 患者早期结局和出院状况的独立预测因素。
