【摘要】 目的建立预测眼肌型起病的重症肌无力患者(ocular myasthenia gravis,OMG)预后的临床评分方法。方法回顾性分析113例眼肌型起病的重症肌无力(myasthenia gravis,MG)患者临床资料,根据起病2年时病情进展情况将患者分为单纯眼肌型组(ocular myasthenia gravis,OMG)和进展为全身型组(general myasthenia gravis,GMG),应用Logistic回归分析筛选影响OMG预后的影响因素,并根据影响因素的回归系数建立量化的预测OMG预后的临床评分方法。受试者工作曲线(receiver operator characteristic curve,ROC)验证评分方法的有效性并确定诊断界点。结果 Logistic回归分析显示胸腺瘤(OR=4.005,95%CI 1.493~10.742)、甲状腺功能(OR=6.640,95%CI 2.553~17.25)是影响OMG预后的危险因素,评分方法总分数值为3分。ROC曲线下面积为76.6%,界点为1分,患者大于该分数值有进展为GMG的风险。界点为1分时该评分方法预测OMG预后的灵敏度为1,特异度为0.455,阳性预测值为73.9%,阴性预测值为59.1%。结论该评分方法在预测眼肌型MG预后方面切实有效,量化评分1分以上OMG患者2年内有进展为GMG的可能。更多还原

【Abstract】 ObjectiveTo establish a simple scale system to predict early risk of general myasthenia gravis(GMG)in patients with ocular myasthenia gravis(OMG).MethodsWe retrospectively analyzed clinical data of the patients with general myasthenia gravis with a definite ocular myasthenia gravis origin(n=113). The patients with OMG were divided into two groups(OMG and GMG) according to the disease progression within two years after onset of OMG. Logistic regression analysis was used to screen the influencing factors.The score was developed according to regression coefficients.The receiver operating characteristic(ROC) curve was first plotted. The ROC was then used to determine sensitivities and specificities of prediction.ResultsLogistic regression analysis revealed that thymoma(OR 4.005, 95 %CI 1.493~10.742)and thyroid dysfunction(OR 6.640, 95 % CI 2.553~17.25) were the risk factors for the poor prognosis of OMG, and a three-point scale system was used to rate the risk of GMG in OMG patients. ROC was plotted and area under the curve(AUC) was 76.6%. One-point was set as the cutoff point with sensitivity of 1, specificity of 0.455,positive predictive value 73.9% and negative predictive value 59.1%. OMG patients with score higher than 1 were at high risk for GMG.ConclusionsThe present study has established a simple three-point scale system for the risk of GMG in patients with OMG.The scale system can be used in routine clinical practice to identify high-risk individuals with score higher than 1 although further validations are needed.更多还原