Spanos A, Harrell F E, Durack D T
Division of Infectious Diseases, Duke University, Medical Center, Durham, NC 27710.
JAMA. 1989 Nov 17;262(19):2700-7.
We analyzed data from the records of 422 patients with acute bacterial or viral meningitis. A cerebrospinal fluid (CSF) glucose level less than 1.9 mmol/L, a CSF-blood glucose ratio less than 0.23, a CSF protein level greater than 2.2 g/L, more than 2000 x 10(6)/L CSF leukocytes, or more than 1180 x 10(6)/L CSF polymorphonuclear leukocytes were individual predictors of bacterial infection with 99% certainty or better. Although any one of these tests could rule in bacterial meningitis with high probability, none could rule it out. To better predict whether a patient has bacterial vs viral infection, we developed a logistic multiple regression model using CSF-blood glucose ratio, total polymorphonuclear leukocyte count in CSF, age, and month of onset. This proved highly reliable when validated in an independent test sample, with an area under receiver operating characteristic curve of 0.97. The model should allow physicians to differentiate between acute viral and acute bacterial meningitis with greater accuracy.
我们分析了422例急性细菌性或病毒性脑膜炎患者的病历数据。脑脊液(CSF)葡萄糖水平低于1.9 mmol/L、脑脊液与血糖比值低于0.23、脑脊液蛋白水平高于2.2 g/L、脑脊液白细胞计数超过2000×10⁶/L或脑脊液多形核白细胞计数超过1180×10⁶/L,均是细菌感染的个体预测指标,确定性达99%或更高。虽然这些检查中的任何一项都能以高概率确诊细菌性脑膜炎,但无一能排除该病。为了更好地预测患者是细菌性感染还是病毒性感染,我们使用脑脊液与血糖比值、脑脊液中多形核白细胞总数、年龄和发病月份建立了一个逻辑多元回归模型。在独立测试样本中进行验证时,该模型被证明具有高度可靠性,受试者操作特征曲线下面积为0.97。该模型应能使医生更准确地区分急性病毒性脑膜炎和急性细菌性脑膜炎。