A simple screening tool for non-alcoholic fatty liver disease based on healthy physical examination population / 公共卫生与预防医学

Objective To design a simple screening tool for non-alcoholic fatty liver disease based on Chinese healthy physical examination population. Methods Subjects were selected from the health management center of China Medical University since January 2017 to December 2017. A total of 32,578 subjects were included. 80% subjects were randomly selected as the training set for modeling and internal assessment, and the remaining 20% subjects were used as the verification set for external assessment. Stepwise logistic regression analysis was used to construct the NAFLD screening index. Results Multivariate regression analysis showed that body mass index (BMI), fasting glucose (FPG), serum triglyceride (TG), and aspartate aminotransferase/alanine aminotransferase (AST/ALT) were included in the NAFLD screening model. The constructed NAFLD screening index was 2×BMI+FPG+3×TG-7×(AST/ALT). The AUC of the index was 0.883 [95%CI (0.879, 0.887)] in the training set and was 0.888 [95%CI (0.880, 0.896)] in the verification set. Conclusion The NAFLD screening index, as a simple and effective screening tool, can be used to screen large-scale population at high risk, which has certain epidemiological and health economic significance.

Evaluation of the Predictive Index for Osteoporosis as a Clinical Tool to Identify the Risk of Osteoporosis in Korean Men by Using the Korea National Health and Nutrition Examination Survey Data / 가정의학회지

BACKGROUND: We previously proposed the Predictive Index for Osteoporosis as a new index to identify men who require bone mineral density measurement. However, the previous study had limitations such as a single-center design and small sample size. Here, we evaluated the usefulness of the Predictive Index for Osteoporosis using the nationally representative data of the Korea National Health and Nutrition Examination Survey. METHODS: Participants underwent bone mineral density measurements via dual energy X-ray absorptiometry, and the Predictive Index for Osteoporosis and Osteoporosis Self-Assessment Tool for Asians were assessed. Receiver operating characteristic analysis was used to obtain optimal cut-off points for the Predictive Index for Osteoporosis and Osteoporosis Self-Assessment Tool for Asians, and the predictability of osteoporosis for the 2 indices was compared. RESULTS: Both indices were useful clinical tools for identifying osteoporosis risk in Korean men. The optimal cut-off value for the Predictive Index for Osteoporosis was 1.07 (sensitivity, 67.6%; specificity, 72.7%; area under the curve, 0.743). When using a cut-off point of 0.5 for the Osteoporosis Self-Assessment Tool for Asians, the sensitivity and specificity were 71.9% and 64.0%, respectively, and the area under the curve was 0.737. CONCLUSION: The Predictive Index for Osteoporosis was as useful as the Osteoporosis Self-Assessment Tool for Asians as a screening index to identify candidates for dual energy X-ray absorptiometry among men aged 50–69 years.

Evaluation of the Predictive Index for Osteoporosis as a Clinical Tool to Identify the Risk of Osteoporosis in Korean Men by Using the Korea National Health and Nutrition Examination Survey Data / 가정의학회지

BACKGROUND: We previously proposed the Predictive Index for Osteoporosis as a new index to identify men who require bone mineral density measurement. However, the previous study had limitations such as a single-center design and small sample size. Here, we evaluated the usefulness of the Predictive Index for Osteoporosis using the nationally representative data of the Korea National Health and Nutrition Examination Survey. METHODS: Participants underwent bone mineral density measurements via dual energy X-ray absorptiometry, and the Predictive Index for Osteoporosis and Osteoporosis Self-Assessment Tool for Asians were assessed. Receiver operating characteristic analysis was used to obtain optimal cut-off points for the Predictive Index for Osteoporosis and Osteoporosis Self-Assessment Tool for Asians, and the predictability of osteoporosis for the 2 indices was compared. RESULTS: Both indices were useful clinical tools for identifying osteoporosis risk in Korean men. The optimal cut-off value for the Predictive Index for Osteoporosis was 1.07 (sensitivity, 67.6%; specificity, 72.7%; area under the curve, 0.743). When using a cut-off point of 0.5 for the Osteoporosis Self-Assessment Tool for Asians, the sensitivity and specificity were 71.9% and 64.0%, respectively, and the area under the curve was 0.737. CONCLUSION: The Predictive Index for Osteoporosis was as useful as the Osteoporosis Self-Assessment Tool for Asians as a screening index to identify candidates for dual energy X-ray absorptiometry among men aged 50–69 years.

Development of Nutrition Screening Index for Hospitalized Patients / 대한지역사회영양학회지

Several studies about hospital malnutrition have been reported that about more than 40% of hospitalized patients are having nutritional risk factors and hospital malnutrition presents a high prevalence. People in a more severe nutritional status ended up with a longer length of hospital stay and higher hospital cost. Nutrition screening tools identify individuals who are malnourished or at risk of becoming malnourished and who may benefit from nutritional support. For the early detection and treatment of malnourished hospital patients, few valid screening instruments for Koreans exist. Therefore, the aim of this study was to develop a simple, reliable and valid malnutrition screening tool that could be used at hospital admission to identify adult patients at risk of malnutrition using medical electrical record data. Two hundred and one patients of the university affiliated medical center were assessed on nutritional status and classified as well nourished, moderately or severely malnourished by a Patient-Generated subjective global assessment (PG-SGA) being chosen as the 'gold standard' for defining malnutrition. The combination of nutrition screening questions with the highest sensitivity and specificity at prediction PG-SGA was termed the nutrition screening index (NSI). Odd ratio, and binary logistic regression were used to predict the best nutritional status predictors. Based on regression coefficient score, albumin less than 3.5 g/dl, body mass index (BMI) less than 18.5 kg/m2, total lymphocyte count less than 900 and age over 65 were determined as the best set of NSI. By using best nutritional predictors receiver operating characteristic curve with the area under the curve, sensitivity and 1-specificity were analyzed to determine the best optimal cut-off point to decide normal or abnormal in nutritional status. Therefore simple and beneficial NSI was developed for identifying patients with severe malnutrition. Using NSI, nutritional information of the severe malnutrition patient should be shared with physicians and they should be cared for by clinical dietitians to improve their nutritional status.