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目的探讨采用高频超声检查腕管结构对诊断职业性手臂振动病(HAVD)的意义。方法采用方便抽样方法,以18例(36只手腕)男性职业性轻度HAVD患者为病例组,20名(40只手腕)男性健康志愿者为对照组。以彩色多普勒超声诊断仪检测2组人群豌豆骨水平正中神经横截面积(CSA)以及钩骨钩水平腕横韧带厚度、正中神经的内径和CSA。采用Fisher判别分析和受试者工作(ROC)曲线评价豌豆骨水平正中神经CSA诊断HAVD的效果。结果病例组人群双手豌豆骨水平正中神经CSA小于对照组(P<0.01)。病例组人群双手钩骨钩水平的腕横韧带厚度、正中神经内径及CSA分别与对照组比较,差异均无统计学意义(P>0.05)。以双手豌豆骨平面正中神经CSA为HAVD诊断指标进行Fisher判别分析建立判别方程,对HAVD的预测准确率为78.9%。以判别得分进行ROC曲线分析以判别HAVD,曲线下面积为0.842,灵敏度为75.00%,特异度为88.90%。结论高频超声检查可观察并量化HAVD患者腕管内容物的影像学变化,为诊断HAVD提供客观、科学的影像学诊断依据。
Objective To investigate the significance of using high-frequency ultrasound to detect carpal tunnel structure in the diagnosis of occupational arm vibration disease (HAVD). Methods 18 cases (36 wrists) of male occupational mild HAVD patients were selected as case group and 20 (40 wrists) male healthy volunteers as control group. The median nerve cross-sectional area (CSA) of pea bones and the thickness of the transverse carpal ligaments of the hooks, median diameter of the median nerve and CSA were measured by color Doppler sonography. Fisher discriminant analysis and receiver operating characteristic (ROC) curves were used to evaluate the effect of pea-level median nerve CSA in the diagnosis of HAVD. Results CSA of median peas in peas of both hands were lower in case group than in control group (P <0.01). The thickness of the transverse carpal ligament, median diameter of medial nerve and CSA of patients in the case group were significantly higher than those in the control group (P> 0.05). Discriminant equation was established by Fisher discriminant analysis based on the diagnostic value of CSA for HAVD in both hands with pea bone plane median nerve. The accuracy of HAVD prediction was 78.9%. The discriminant score was analyzed by ROC curve to discriminate HAVD. The area under the curve was 0.842, the sensitivity was 75.00% and the specificity was 88.90%. Conclusion High-frequency ultrasound can observe and quantify the radiographic changes of the contents of carpal tunnel in patients with HAVD, and provide an objective and scientific diagnostic basis for the diagnosis of HAVD.