摘要
目的建立神经外科术后细菌性脑膜炎诊断的多指标线性判别模型。方法回顾性分析2012—2016年某院细菌性脑膜炎(226例)和无菌性脑膜炎患者(255例)的14项实验室检查,将有意义的指标绘制受试者工作曲线(ROC曲线),曲线下面积(AUC)> 0. 7的项目进行线性回归拟合,建立多指标联合诊断线性判别模型。选取26例脑膜炎患者的数据,验证判别模型的判别能力。结果两组脑膜炎患者11项指标比较,差异有统计学意义(均P <0. 05),其中脑脊液白细胞计数(C-WBC)、脑脊液葡萄糖浓度(C-Glu)、血葡萄糖浓度(B-Glu)、脑脊液血糖比例(C/B-Glu)及脑脊液乳酸(C-Lac) 5项指标的AUC均>0. 7。通过线性拟合获得判别模型:Y=-0. 268×C-Glu+0. 127×B-Glu+0. 24×C-Lac-0. 722×C/B-Glu+0. 00000638×C-WBC-0. 866,拟合5项指标诊断细菌性脑膜炎的ROC曲线AUC为0. 907,灵敏度、特异度、阳性预测值与阴性预测值均> 80. 0%。26例脑膜炎患者的数据验证判别模型效果,结果显示,模型判别的准确率与特异度均较高(90. 0%、81. 2%),一致率达84. 6%。结论利用多指标联合诊断可以有效地区分细菌性脑膜炎与无菌性脑膜炎,更好地解决细菌性脑膜炎的诊断问题。
Objective To establish a multi-index linear discriminant model for the diagnosis of bacterial meningitis after neurosurgery operation. Methods A retrospective analysis was performed on 14 laboratory examinations of bacterial meningitis( n = 226) and aseptic meningitis( n = 255) in patients in a hospital from 2012 to 2016. Receiver operating characteristic( ROC) curve for significant variables was drawn,items with area under the curve( AUC) >0. 7 were conducted linear regression fitting,and a linear discriminant model for combined multi-index diagnosis was established,data of 26 patients with meningitis were selected to verify the discriminant capacity of the discriminant model. Results There were significant differences in 11 indexes between two groups of patients with meningitis( all P< 0. 05). AUC of cerebrospinal fluid( CSF) white blood cell count( C-WBC),CSF glucose concentration( C-Glu),blood glucose concentration( B-Glu),CSF blood glucose ratio( C/B-Glu) and CSF lactic acid( C-Lac) were all> 0. 7. The discriminant model was obtained by linear fitting: Y =-0. 268 × C-Glu + 0. 127 × B-Glu + 0. 24 × CLac-0. 722 × C/B-Glu + 0. 00000638 × C-WBC-0. 866,AUC of ROC curve of five indexes for diagnosis of bacterial meningitis was 0. 907,sensitivity,specificity,positive predictive value,and negative predictive value were all >80. 0 %. Data of 26 patients with meningitis validated the discriminant capacity of discriminant model,the accuracy and specificity discriminated by the model were high( 90. 0 %,81. 2 %),consistency rate was 84. 6 %. Conclusion The combined diagnosis of multiple indexes can effectively distinguish bacterial meningitis from aseptic meningitis,and promote the diagnosis of bacterial meningitis.
引文
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