Song Zhi, Zheng Wen, Zhu Haixia, Chen Yiwei, Fan Xuejun, Hou Deren, Deng Hao
Department of Neurology, the Third Xiangya Hospital, Central South University, Changsha 410013, PR China.
Clin Neurol Neurosurg. 2012 Jul;114(6):634-8. doi: 10.1016/j.clineuro.2011.12.029. Epub 2012 Jan 17.
Coma and anisocoria are the two common signs of a crucial state of neurological dysfunction. The ability to forecast the occurrence of these conditions would help clinicians make clinical risk assessments and decisions.
From October 2006 to September 2008, 118 patients with supratentorial intracerebral hemorrhage (SICH) were enrolled in this retrospective investigation. Patients were distributed into 3 groups according to occurrence of the signs of coma and/or anisocoria in the observation unit during a 30-day period. Group 1 included 52 patients who had normal or impaired consciousness, group 2 included 27 patients who had coma with no anisocoria and group 3 consisted of 39 patients who had coma with anisocoria. The clinical characteristics and parameters on computerized tomography (CT) findings were compared using univariate analysis to determine the factors that were related to the level of consciousness. Logistic regression models established the predictive equations for coma and anisocoria.
Univariate analysis revealed that hematoma volume, the score of intraventricular hemorrhage (IVH score) and the amplitude of midline shift were the factors related to coma and anisocoria. Mean hematoma volume was 24.0 ± 13.0 ml, 53.6 ± 12.6 ml and 80.5 ± 24.6 ml, the mean amplitudes of midline shift were 1.3 ± 2.0 mm, 5.9 ± 4.9 mm and 10.1 ± 5.5 mm, and the mean IVH score was 0.8 ± 1.3, 3.3 ± 3.3 and 5.9 ± 3.4 in groups 1, 2 and 3, respectively. Multivariate analysis showed that hematoma volume and IVH score were independent prognostic factors for coma and anisocoria. The predictive equations for coma and anisocoria were LogitP = 0.279X(HV) + 0.521X(IVH)-18.164 and LogitP = 0.125X(HV)+0.326X(IVH)-6.864, respectively.
Hematoma volume and IVH score were the independent prognostic factors for coma and anisocoria. Logistic regression models established the fitted predictive equations, which could help clinicians make clinical risk assessments and decisions.
昏迷和瞳孔不等大是神经功能障碍危急状态的两个常见体征。预测这些情况的发生能力将有助于临床医生进行临床风险评估和决策。
2006年10月至2008年9月，118例幕上脑出血（SICH）患者纳入本回顾性研究。根据观察单元30天内昏迷和/或瞳孔不等大体征的发生情况将患者分为3组。第1组包括52例意识正常或受损的患者，第2组包括27例昏迷但无瞳孔不等大的患者，第3组由39例昏迷且有瞳孔不等大的患者组成。采用单因素分析比较计算机断层扫描（CT）结果的临床特征和参数，以确定与意识水平相关的因素。逻辑回归模型建立了昏迷和瞳孔不等大的预测方程。
单因素分析显示，血肿体积、脑室内出血评分（IVH评分）和中线移位幅度是与昏迷和瞳孔不等大相关的因素。第1、2、3组的平均血肿体积分别为24.0±13.0 ml、53.6±12.6 ml和80.5±24.6 ml，中线移位平均幅度分别为1.3±2.0 mm、5.9±4.9 mm和10.1±5.5 mm，平均IVH评分分别为0.8±1.3、3.3±3.3和5.9±3.4。多因素分析表明，血肿体积和IVH评分是昏迷和瞳孔不等大的独立预后因素。昏迷和瞳孔不等大的预测方程分别为LogitP = 0.279X（HV）+ 0.521X（IVH）-18.164和LogitP = 0.125X（HV）+ 0.326X（IVH）-6.864。
血肿体积和IVH评分是昏迷和瞳孔不等大的独立预后因素。逻辑回归模型建立了拟合预测方程，有助于临床医生进行临床风险评估和决策。
