The purpose of this study was to assess several indices of diet quality based on nutrient, food and food group intake of Korean adolescents based on several indices on diet quality according to residence area and body size. Using the data from the 1998 National Health and Nutrition Survey, twenty-four-hour-dietary recalls of a total of 1,110 Korean adolescents aged 13-19 years (male 543, female 567) were analyzed for nutrient adequacy ratio (NAR), index of nutritional quality (INQ), the number of foods (Dietary Variety Score, DVS) and food group consumed (Dietary Diversity Score, DDS). In doing that, it was attempted to apply only the minimum amount of solid foods of Kant's without inclusion of liquid foods because of the very limited variety in Korean foods. Based on weight length index, 13.1% of the subjects were categorized as obese, 14.2%, overweight, 44.4%, normal and 28.3%, underweight. Only vitamin B2 intake was higher in the obese group than in the underweight group. There was no meaningful difference in energy, protein and fat intakes according to the grade of the body size. In terms of residence area, intake of fat, niacin, vitamin B6 and folic acid were lower in the rural areas than in the metropolitan city. Only vitamin E intake was higher in the rural areas. Mean value of NARs (MAR) and INQs (mINQ) was also higher in the metropolitan city than in the rural areas, but there was no significant difference of these two values according to body size of the subjects. Mean DVS was 21.02 for total subjects, and has no difference between male and female and between metropolitan city and other medium-small city. But, the rural areas showed the lowest DVS of 19.05. Mean DDS in which five is a maximum score was 3.3 with no significant difference by sex and by residence area in male subjects. However, in female subjects, DDS in the rural areas was the lowest. According to body size of the subjects, there was no meaningful difference in both scores of DVS and DDS. In conclusion, most indices of nutrient intake and food and food group intake were not significantly different by body size of the subjects, while most indices were significantly different by residence areas: higher in the metropolitan city than in the rural area.
Adolescent* ; Body Size* ; Diet* ; Female ; Folic Acid ; Humans ; Male ; Niacin ; Nutrition Surveys ; Nutritive Value ; Overweight ; Riboflavin ; Thinness ; Vitamin B 6 ; Vitamin E ; Vitamins

BACKGROUND: Severe forefoot deformities, particularly those involving the dorsum of the foot, cause inconvenience in daily activities of living including moderate pain on the dorsal aspect of the contracted foot while walking and difficulty in wearing nonsupportive shoes due to toe contractures. This paper presents clinical results of reconstruction of severe forefoot deformity using the anterolateral thigh (ALT) free flap. METHODS: Severe forefoot deformities were reconstructed using ALT flaps in 7 patients (8 cases) between March 2012 and December 2015. The mean contracture duration was 28.6 years. RESULTS: All the flaps survived completely. The size of the flaps ranged from 8 cm × 5 cm to 19 cm × 8 cm. The mean follow-up period was 10 months (range, 7 to 15 months). There was no specific complication at both the recipient and donor sites. There was one case where the toe contracture could not be completely treated after surgery. All of the patients were able to wear shoes and walk without pain. Also, the patients were highly satisfied with cosmetic results. CONCLUSIONS: The ALT flap may be considered ideal for the treatment of severe forefoot deformity.
Congenital Abnormalities ; Contracture* ; Follow-Up Studies ; Foot ; Foot Deformities ; Free Tissue Flaps ; Humans ; Shoes ; Thigh* ; Tissue Donors ; Toes ; Walking

Chronic pancreatitis is a rare problem in childhood and sometimes shows pancreatic calcification. The most common symptom is recurrent upper abdominal pain with or without associated nausea or vomiting. Pancreatic calcifications are virtually pathognomonic of chronic pancreatitis. In our case, however, chronic pancreatitis caused by multiple pancreatic stones in dilated pancreatic duct, which was very rare in childhood. Endoscopic retrograde cholangiopancreaticography (ERCP) is valuable in confirming the diagnosis and decision making process for further medical or surgical management of pancreatic disease. We experienced a case of chronic relapsing pancreatitis with pancreatic stones in 13-year-old girl who presented with recurrent upper abdominal pain. She was investigated with ERCP and treated by endoscopic sphincterotomy of sphincter of Oddi and by some stone removal with endoscopic basket. We report this case and review related literatures briefly.
Abdominal Pain ; Adolescent ; Cholangiopancreatography, Endoscopic Retrograde ; Decision Making ; Diagnosis ; Female ; Humans ; Nausea ; Pancreatic Diseases ; Pancreatic Ducts ; Pancreatitis* ; Pancreatitis, Chronic ; Sphincter of Oddi ; Sphincterotomy, Endoscopic ; Vomiting

Objective: We aimed to determine whether individuals at immediate risk of suicide could be identified using data from a commercially available wearable device. Methods: Thirty-nine participants experiencing acute depressive episodes and 20 age- and sex-matched healthy controls wore a commercially available wearable device (Galaxy Watch Active2) for two months. We collected data on activities, sleep, and physiological metrics like heart rate and heart rate variability using the wearable device. Participants rated their mood spontaneously twice daily on a Likert scale displayed on the device. Mood ratings by clinicians were performed at weeks 0, 2, 4, and 8. The suicide risk was assessed using the Hamilton Depression Rating Scale’s suicide item score (HAMD-3). We developed two predictive models using machine learning: a single-level model that processed all data simultaneously to identify those at immediate suicide risk (HAMD-3 scores ≥1) and a multilevel model. We compared the predictions of imminent suicide risk from both models. Results: Both the single-step and multi-step models effectively predicted imminent suicide risk. The multi-step model outperformed the single-step model in predicting imminent suicide risk with area under the curve scores of 0.89 compared to 0.88. In the multi-step model, the HAMD total score and heart rate variability were most significant, whereas in the single-step model, the HAMD total score and diagnosis were key predictors. Conclusion Wearable devices are a promising tool for identifying individuals at immediate risk of suicide. Future research with more refined temporal resolution is recommended.

Objective: We aimed to determine whether individuals at immediate risk of suicide could be identified using data from a commercially available wearable device. Methods: Thirty-nine participants experiencing acute depressive episodes and 20 age- and sex-matched healthy controls wore a commercially available wearable device (Galaxy Watch Active2) for two months. We collected data on activities, sleep, and physiological metrics like heart rate and heart rate variability using the wearable device. Participants rated their mood spontaneously twice daily on a Likert scale displayed on the device. Mood ratings by clinicians were performed at weeks 0, 2, 4, and 8. The suicide risk was assessed using the Hamilton Depression Rating Scale’s suicide item score (HAMD-3). We developed two predictive models using machine learning: a single-level model that processed all data simultaneously to identify those at immediate suicide risk (HAMD-3 scores ≥1) and a multilevel model. We compared the predictions of imminent suicide risk from both models. Results: Both the single-step and multi-step models effectively predicted imminent suicide risk. The multi-step model outperformed the single-step model in predicting imminent suicide risk with area under the curve scores of 0.89 compared to 0.88. In the multi-step model, the HAMD total score and heart rate variability were most significant, whereas in the single-step model, the HAMD total score and diagnosis were key predictors. Conclusion Wearable devices are a promising tool for identifying individuals at immediate risk of suicide. Future research with more refined temporal resolution is recommended.

Objective: We aimed to determine whether individuals at immediate risk of suicide could be identified using data from a commercially available wearable device. Methods: Thirty-nine participants experiencing acute depressive episodes and 20 age- and sex-matched healthy controls wore a commercially available wearable device (Galaxy Watch Active2) for two months. We collected data on activities, sleep, and physiological metrics like heart rate and heart rate variability using the wearable device. Participants rated their mood spontaneously twice daily on a Likert scale displayed on the device. Mood ratings by clinicians were performed at weeks 0, 2, 4, and 8. The suicide risk was assessed using the Hamilton Depression Rating Scale’s suicide item score (HAMD-3). We developed two predictive models using machine learning: a single-level model that processed all data simultaneously to identify those at immediate suicide risk (HAMD-3 scores ≥1) and a multilevel model. We compared the predictions of imminent suicide risk from both models. Results: Both the single-step and multi-step models effectively predicted imminent suicide risk. The multi-step model outperformed the single-step model in predicting imminent suicide risk with area under the curve scores of 0.89 compared to 0.88. In the multi-step model, the HAMD total score and heart rate variability were most significant, whereas in the single-step model, the HAMD total score and diagnosis were key predictors. Conclusion Wearable devices are a promising tool for identifying individuals at immediate risk of suicide. Future research with more refined temporal resolution is recommended.

Objective: We aimed to determine whether individuals at immediate risk of suicide could be identified using data from a commercially available wearable device. Methods: Thirty-nine participants experiencing acute depressive episodes and 20 age- and sex-matched healthy controls wore a commercially available wearable device (Galaxy Watch Active2) for two months. We collected data on activities, sleep, and physiological metrics like heart rate and heart rate variability using the wearable device. Participants rated their mood spontaneously twice daily on a Likert scale displayed on the device. Mood ratings by clinicians were performed at weeks 0, 2, 4, and 8. The suicide risk was assessed using the Hamilton Depression Rating Scale’s suicide item score (HAMD-3). We developed two predictive models using machine learning: a single-level model that processed all data simultaneously to identify those at immediate suicide risk (HAMD-3 scores ≥1) and a multilevel model. We compared the predictions of imminent suicide risk from both models. Results: Both the single-step and multi-step models effectively predicted imminent suicide risk. The multi-step model outperformed the single-step model in predicting imminent suicide risk with area under the curve scores of 0.89 compared to 0.88. In the multi-step model, the HAMD total score and heart rate variability were most significant, whereas in the single-step model, the HAMD total score and diagnosis were key predictors. Conclusion Wearable devices are a promising tool for identifying individuals at immediate risk of suicide. Future research with more refined temporal resolution is recommended.

Objective: We aimed to determine whether individuals at immediate risk of suicide could be identified using data from a commercially available wearable device. Methods: Thirty-nine participants experiencing acute depressive episodes and 20 age- and sex-matched healthy controls wore a commercially available wearable device (Galaxy Watch Active2) for two months. We collected data on activities, sleep, and physiological metrics like heart rate and heart rate variability using the wearable device. Participants rated their mood spontaneously twice daily on a Likert scale displayed on the device. Mood ratings by clinicians were performed at weeks 0, 2, 4, and 8. The suicide risk was assessed using the Hamilton Depression Rating Scale’s suicide item score (HAMD-3). We developed two predictive models using machine learning: a single-level model that processed all data simultaneously to identify those at immediate suicide risk (HAMD-3 scores ≥1) and a multilevel model. We compared the predictions of imminent suicide risk from both models. Results: Both the single-step and multi-step models effectively predicted imminent suicide risk. The multi-step model outperformed the single-step model in predicting imminent suicide risk with area under the curve scores of 0.89 compared to 0.88. In the multi-step model, the HAMD total score and heart rate variability were most significant, whereas in the single-step model, the HAMD total score and diagnosis were key predictors. Conclusion Wearable devices are a promising tool for identifying individuals at immediate risk of suicide. Future research with more refined temporal resolution is recommended.

OBJECTIVES: In the unique metal iris method, the developing interfacial gap at the cavity floor resulting from the cavity wall property during polymerizing composite resin might affect the nominal shear bond strength values. The aim of this study is to evaluate that the iris method reduces the cohesive failure in the substrates and the cavity wall property effects on the shear bond strength tests using iris method. MATERIALS AND METHODS: The occlusal dentin of 64 extracted human molars were randomly divided into 4 groups to simulate two different levels of cavity wall property (metal and dentin iris) and two different materials (ONE-STEP(R) and ALL-BOND(R) 2) for each wall property. After positioning the iris on the dentin surface, composite resin was packed and light-cured. After 24 hours the shear bond strength was measured at a crosshead speed of 0.5 mm/min. Fracture analysis was performed using a microscope and SEM. The data was analyzed statistically by a two-way ANOVA and t-test. RESULTS: The shear bond strength with metal iris was significant higher than those with dentin iris (p = 0.034). Using ONE-STEP(R), the shear bond strength with metal iris was significant higher than those with dentin iris (p = 0.005), but not in ALL-BOND(R) 2 (p = 0.774). The incidence of cohesive failure was very lower than other shear bond strength tests that did not use iris method. CONCLUSIONS: The iris method may significantly reduce the cohesive failures in the substrates. According to the bonding agent systems, the shear bond strength was affected by the cavity wall property.
Dentin ; Humans ; Incidence ; Iris* ; Molar ; Polymers

Background: The purpose of this study was to measure several mental health variables according to HbA1c level and examine their relationship among diabetic patients. Methods: Total 89 outpatients who attended diabetes education program at St. Vincent’s Hospital, The Catholic University of Korea College of Medicine, were enrolled this study. The Beck Depression Inventory (BDI), State-Trait Anxiety Inventory, Stress Response Inventory (SRI), abbreviated version of World Health Organization Quality of Life assessment instrument (WHOQOL-BREF), Insomnia Severity Index, and Epworth Sleepiness Scale (ESS) were administered to all patients. Significant differences between groups were assessed by t-test and chi-squared test. Pearson correlation and multiple linear regression analyses were used to identify the variables that affect HbA1c levels. Results: The well-controlled group had a significantly lower BDI score than the poorly controlled group. The wellcontrolled group also showed significantly lower SRI and ESS. HbA1c, BDI, SRI, and ESS were positively correlated. Duration and BDI were the only variables affecting HbA1c levels. Conclusion Emphasis should be given to the identification and management of mental health problems, including especially depressive symptoms in patients with diabetes.