To evaluate the relationship among smoking, alcohol consumption, and obesity and benign or malignant parotid tumors in a Korean population. The Korean National Health Insurance Service-Health Screening Cohort (for ≥40-year-olds) was assessed from 2002 to 2013. In total, 336 benign parotid tumors and 46 malignant parotid tumors were matched with controls at a ratio of 1 to 4 with respect to age, sex, income, region of residence, hypertension, diabetes, and dyslipidemia. We analyzed previous histories of smoking, alcohol consumption, and obesity. By unconditional logistic regression analyses, the crude and adjusted odds ratios (ORs) were investigated and the 95% confidence intervals (CIs) were counted. The estimated annual incidence of the benign parotid tumors was 5.66 per 100,000, and that of the malignant parotid tumor was 0.81 per 100,000. The adjusted ORs of smoking for the benign parotid tumors was 2.52 (95% CI, 1.84 to 3.46). This finding was consistent in the subgroups of <60 years old, ≥60 years old, and men. The adjusted ORs of alcohol consumption for the benign parotid tumors showed the statistical significance only in women (adjusted OR, 2.35; 95% CI, 1.10 to 5.00). Obesity did not reach a statistical significance in any analysis. Benign parotid tumor was related with smoking, and it was linked with alcohol consumption in women only.

Facial nerve palsy induces a weakness or loss of facial expression through damage of the facial nerve. A quantitative and reliable assessment system for facial nerve palsy is required for both patients and clinicians. In this study, we propose a rapid and portable smartphone-based automatic diagnosis system that discriminates facial nerve palsy from normal subjects. Facial landmarks are localized and tracked by an incremental parallel cascade of the linear regression method. An asymmetry index is computed using the displacement ratio between the left and right side of the forehead and mouth regions during three motions: resting, raising eye-brow and smiling. To classify facial nerve palsy, we used Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM), and Leave-one-out Cross Validation (LOOCV) with 36 subjects. The classification accuracy rate was 88.9%.

Yoo HW, et al. J Korean Med Sci. 2021 Oct;36(41):e291. https://doi.org/10.3346/jkms.2021.36.e291

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