CT测量的脑中线移位是脑出血预后的独立预测因素
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摘要
目的探讨CT显示脑中线移位程度与自发性脑出血预后的关系。方法回顾性分析2012年1月至2018年1月收治的自发性脑出血的临床资料。采用多因素Logistic回归分析鉴别脑出血预后的独立预测因素;同时采用受试者工作特征(ROC)曲线分析判断脑中线移位值对于预测不良预后的最佳分界点。结果发病3个月,预后良好(GOS评分4～5分)132例,预后不良(GOS评分1～3分)79例。多因素Logistic回归分析显示,入院GCS评分低、血肿形态不规则、脑中线移位严重为预后不良的独立危险因素(P<0.05)。ROC曲线结果显示,脑中线移位≥3.65 mm预测不良预后的敏感性为0.835、特异性为0.758。结论脑中线移位是脑出血预后的独立预测因素,移位大于3.65 mm时可能预后不良。
Objective To investigate the relationship between midline shift(MLS) and prognosis in the patient with spontaneousintracerebral hemorrhage(sICH). Methods The clinical and radiological data of 211 patients with sICH treated in Changzheng Hospitalfrom January, 2012 to January, 2018 were analyzed retrospectively. MLS value was calculated on the cerebral CT images and itsrelationship with the prognoses 3 months after sICH was evaluated by multivariate logistic regression analysis. The optimal MLS valuecut-off point for the prognoses prediction was decided by receiver operating characteristics(ROC) curve analysis. Results Themultivariate logistic regression analysis showed that MLS was an independent predictor for the prognoses in the patients with sICH. Thepredictive value was confirmed by ROC curve analysis, and the optimal MLS value cut-off point was 3.65 mm. Conclusions MLS isassociated with clinical prognosis and MLS value >3.65 mm may independently predict poor prognoses in the patients with sICH.
Objective To investigate the relationship between midline shift(MLS) and prognosis in the patient with spontaneousintracerebral hemorrhage(sICH). Methods The clinical and radiological data of 211 patients with sICH treated in Changzheng Hospitalfrom January, 2012 to January, 2018 were analyzed retrospectively. MLS value was calculated on the cerebral CT images and itsrelationship with the prognoses 3 months after sICH was evaluated by multivariate logistic regression analysis. The optimal MLS valuecut-off point for the prognoses prediction was decided by receiver operating characteristics(ROC) curve analysis. Results Themultivariate logistic regression analysis showed that MLS was an independent predictor for the prognoses in the patients with sICH. Thepredictive value was confirmed by ROC curve analysis, and the optimal MLS value cut-off point was 3.65 mm. Conclusions MLS isassociated with clinical prognosis and MLS value >3.65 mm may independently predict poor prognoses in the patients with sICH.
引文
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[2]Wiggins WS,Moody DM,Toole JF,et al.Clinical and computerized tomographic study of hypertensive intracerebral hemorrhage[J].J Comput Assist Tomo,1978,3:832-833.
[3]MasèG,Zorzon M,Biasutti E,et al.Immediate prognosis of primary intracerebral hemorrhage using an easy model for the prediction of survival[J].Acta Neurol Scand,2010,91(4):306-309.
[4]Daverat P,Castel JP,Dartigues JF,et al.Death and functional outcome after spontaneous intracerebral hemorrhage.A prospective study of 166 cases using multivariate analysis[J].Stroke,1991,22(1):1-6.
[5]Barras CD,Tress BM,Christensen S,et al.Density and shape as CT predictors of intracerebral hemorrhage growth[J].Stroke,2009,40(4):1325-1331.
[6]Hallevy C,Ifergane G,Kordysh E,et al.Spontaneous supratentorial intracerebral hemorrhage:criteria for short-term functional outcome prediction[J].J Neurol,2002,249(12):1704-1709.
[7]Kiphuth IC,Huttner HB,Breuer L,et al.Sonographic monitoring of midline shift predicts outcome after intracerebral hemorrhage[J].Cerebrovasc Dis,2012,34(4):297-304.
[8]Chen J,Zhang D,Li Z,et al.Lateral ventricular volume asymmetry predicts poor outcome after spontaneous intracerebral hemorrhage[J].World Neurosurg,2018,110:e958-e964.
[9]Yang WS,Li Q,Li R,et al.Defining the optimal midline shift threshold to predict poor outcome in patients with supratentorial spontaneous intracerebral hemorrhage[J].Neurocrit Care,2018,28(3):314-321.
[10]Suthar NN,Patel KL,Saparia C,et al.Study of clinical and radiological profile and outcome in patients of intracranial hemorrhage[J].Ann Afr Med,2016,15(2):69-77.
[11]Morotti A,Boulouis G,Romero JM,et al.Blood pressure reduction and noncontrast CT markers of intracerebral hemorrhage expansion[J].Neurology,2017,89:548-554.
[12]Delcourt C,Zhang S,Arima H,et al.Significance of hematoma shape and density in intracerebral hemorrhage:the intensive blood pressure reduction in acute intracerebral hemorrhage trial study[J].Stroke,2016,47(5):1227-1232.
[13]Boulouis G,Morotti A,Brouwers HB,et al.Noncontrast computed tomography hypodensities predict poor outcome in intracerebral hemorrhage patients[J].Stroke,2016,47(10):2511-2516.
[14]Zhang D,Chen J,Guo J,et al.Hematoma heterogeneity on noncontrast computed tomography predicts intracerebral hematoma expansion:a meta-analysis[J].World Neurosurg,2018,114:e663-e676.