ObjectiveTo determine the prevalence and related characteristics of carpal tunnel syndrome (CTS) in orchardists and to investigate the association between electrodiagnostic severity and physical examinations.MethodsBetween July 2013 and September 2014, 377 subjects (174 men and 203 women) visited the Gyeongsang National University Hospital's Center for Farmer's Safety and Health. All the subjects underwent electrodiagnostic tests and physical examination, including Phalen's test, Tinel's sign, and Durkan's carpal compression test (CCT). The subjects were classified into 2 groups, the normal group and the CTS group, according to electrodiagnostic test results. To determine the related characteristics of CTS, potential variables, including age, sex, drinking, smoking, body mass index, waist circumference, and total work time, were compared between the 2 groups. The association between electrodiagnostic severity and physical examinations was analyzed.ResultsCTS was diagnosed in 194 subjects based only on electrodiagnostic test results, corresponding to a prevalence of 51.5%. Among the variables, mean age (p=0.001) and total work time (p=0.007) were significantly correlated with CTS. With respect to the physical examinations, low specificities were observed for Tinel's sign, Phalen's test, and Durkan's CCT (38.4%, 36.1%, and 40.9%, respectively) in the subjects aged ≥65 years. In addition, Phalen's test (p=0.003) and Tinel's sign (p=0.032) in men and Durkan's CCT (p=0.047) in women showed statistically significant differences with increasing CTS severity. The odds ratio was 2.066 for Durkan's CCT in women according to the multivariate logistic regression analysis.ConclusionCTS prevalence among orchardists was high, and Durkan's CCT result was significantly quantitatively correlated with the electrodiagnostic test results. Therefore, Durkan's CCT is another reliable examination method for CTS.

-Galloping is one of the most serious vibration problems in transmission lines. Power lines can be extensively damaged owing to aerodynamic instabilities caused by ice accretion. In this study, the accident probability induced by galloping phenomenon was analyzed using logistic regression analysis. As former studies have generally concluded, main factors considered were local weather factors and physical factors of power delivery systems. Since the number of transmission towers outnumbers the number of weather observatories, interpolation of weather factors, Kriging to be more specific, has been conducted in prior to forming galloping accident estimation model. Physical factors have been provided by Korea Electric Power Corporation, however because of the large number of explanatory variables, variable selection has been conducted, leaving total 11 variables. Before forming estimation model, with 84 provided galloping cases, 840 non-galloped cases were chosen out of 13 billion cases. Prediction model for accidents by galloping has been formed with logistic regression model and validated with 4-fold validation method, corresponding AUC value of ROC curve has been used to assess the discrimination level of estimation models. As the result, logistic regression analysis effectively discriminated the power lines that experienced galloping accidents from those that did not.