Dietary therapy is a basic and emphasized treatment for diabetes. Several clinical studies have shown that diet can play a major role in preventing and managing diabetes. The purposes of this study were to evaluate the dietary behavior and to find solutions to barriers of diabetes mellitus patients. From February to July in 2007, questionnaires were distributed to one hundred and ten patients who were diagnosed DM by physicians and excluded first coming out-patients. One hundred and three data were used for statistical analysis using SPSS/Win 12.0. The main results of this study included the following: To measure dietary behaviors and barriers, a five point scale was used with the following labels: 'strongly yes', 'yes', 'fair', 'no', 'strongly no'. Thirteen dietary behaviors related to diabetes were grouped into the following 4 factors using factor analysis; 'taste control factor', 'blood glucose influence factor', 'practice volition factor', and 'exercise factor'. The mean scores of 4 factors were 3.88, 3.48, 3.55, 3.21, respectively. The 'taste control behaviors' score of subjects who had practiced diet therapy (4.00) was higher than those who had not practiced diet therapy (P < 0.05). The 'blood glucose influence behaviors' score of subjects who had nutrition education (3.59) was higher than those who had no nutrition education (P < 0.05) and subjects who had practiced diet therapy showed higher score (3.59) than those who had not practiced diet therapy (P < 0.05). 'Exercise behaviors score' of subjects who were over 60 (3.59) was the lowest (P < 0.05). Subjects who had nutrition education showed higher 'exercise behaviors' scores (3.38) than those who had no nutrition education (P < 0.05). Subjects who had practiced diet therapy showed higher 'practice volition behaviors' scores (3.72) than those who had not practiced diet therapy (P < 0.001). Subjects who were over weight showed the highest 'practice volition behaviors' scores (3.78) concerning BMI (P < 0.05). In conclusion, this study expected that Nutrition educators (Dietitian) applied to patient effective nutrition education and counseling through evaluation of Dietary behaviors and barriers considered management types and ecological factors of diabetes patients. Also diabetic patients were easy to change dietary habits because they formed behaviors through education and counsel and there were positive effects in their blood glucose control through removing barriers related to dietary therapy.
Blood Glucose ; Counseling ; Diabetes Mellitus ; Diet ; Food Habits ; Glucose ; Humans ; Life Style ; Outpatients ; Volition

Purpose: This study was performed to assess the clinical validity and accuracy of a deep learning-based automatic landmarking algorithm for cone-beam computed tomography (CBCT). Three-dimensional (3D) CBCT head measurements obtained through manual and automatic landmarking were compared. Materials and Methods: A total of 80 CBCT scans were divided into 3 groups: non-surgical (39 cases); surgical without hardware, namely surgical plates and mini-screws (9 cases); and surgical with hardware (32 cases). Each CBCT scan was analyzed to obtain 53 measurements, comprising 27 lengths, 21 angles, and 5 ratios, which weredetermined based on 65 landmarks identified using either a manual or a 3D automatic landmark detection method. Results: In comparing measurement values derived from manual and artificial intelligence landmarking, 6 items displayed significant differences: R U6CP-L U6CP, R L3CP-L L3CP, S-N, Or_R-R U3CP, L1L to Me-GoL, and GoR-Gn/S-N (P<0.05). Of the 3 groups, the surgical scans without hardware exhibited the lowest error, reflecting the smallest difference in measurements between human- and artificial intelligence-based landmarking. The timerequired to identify 65 landmarks was approximately 40-60 minutes per CBCT volume when done manually,compared to 10.9 seconds for the artificial intelligence method (PC specifications: GeForce 2080Ti, 64GB RAM, and an Intel i7 CPU at 3.6 GHz). Conclusion Measurements obtained with a deep learning-based CBCT automatic landmarking algorithm were similar in accuracy to values derived from manually determined points. By decreasing the time required to calculatethese measurements, the efficiency of diagnosis and treatment may be improved.

Purpose: This study was performed to assess the clinical validity and accuracy of a deep learning-based automatic landmarking algorithm for cone-beam computed tomography (CBCT). Three-dimensional (3D) CBCT head measurements obtained through manual and automatic landmarking were compared. Materials and Methods: A total of 80 CBCT scans were divided into 3 groups: non-surgical (39 cases); surgical without hardware, namely surgical plates and mini-screws (9 cases); and surgical with hardware (32 cases). Each CBCT scan was analyzed to obtain 53 measurements, comprising 27 lengths, 21 angles, and 5 ratios, which weredetermined based on 65 landmarks identified using either a manual or a 3D automatic landmark detection method. Results: In comparing measurement values derived from manual and artificial intelligence landmarking, 6 items displayed significant differences: R U6CP-L U6CP, R L3CP-L L3CP, S-N, Or_R-R U3CP, L1L to Me-GoL, and GoR-Gn/S-N (P<0.05). Of the 3 groups, the surgical scans without hardware exhibited the lowest error, reflecting the smallest difference in measurements between human- and artificial intelligence-based landmarking. The timerequired to identify 65 landmarks was approximately 40-60 minutes per CBCT volume when done manually,compared to 10.9 seconds for the artificial intelligence method (PC specifications: GeForce 2080Ti, 64GB RAM, and an Intel i7 CPU at 3.6 GHz). Conclusion Measurements obtained with a deep learning-based CBCT automatic landmarking algorithm were similar in accuracy to values derived from manually determined points. By decreasing the time required to calculatethese measurements, the efficiency of diagnosis and treatment may be improved.

Purpose: This study was performed to assess the clinical validity and accuracy of a deep learning-based automatic landmarking algorithm for cone-beam computed tomography (CBCT). Three-dimensional (3D) CBCT head measurements obtained through manual and automatic landmarking were compared. Materials and Methods: A total of 80 CBCT scans were divided into 3 groups: non-surgical (39 cases); surgical without hardware, namely surgical plates and mini-screws (9 cases); and surgical with hardware (32 cases). Each CBCT scan was analyzed to obtain 53 measurements, comprising 27 lengths, 21 angles, and 5 ratios, which weredetermined based on 65 landmarks identified using either a manual or a 3D automatic landmark detection method. Results: In comparing measurement values derived from manual and artificial intelligence landmarking, 6 items displayed significant differences: R U6CP-L U6CP, R L3CP-L L3CP, S-N, Or_R-R U3CP, L1L to Me-GoL, and GoR-Gn/S-N (P<0.05). Of the 3 groups, the surgical scans without hardware exhibited the lowest error, reflecting the smallest difference in measurements between human- and artificial intelligence-based landmarking. The timerequired to identify 65 landmarks was approximately 40-60 minutes per CBCT volume when done manually,compared to 10.9 seconds for the artificial intelligence method (PC specifications: GeForce 2080Ti, 64GB RAM, and an Intel i7 CPU at 3.6 GHz). Conclusion Measurements obtained with a deep learning-based CBCT automatic landmarking algorithm were similar in accuracy to values derived from manually determined points. By decreasing the time required to calculatethese measurements, the efficiency of diagnosis and treatment may be improved.

Purpose: This study was performed to assess the clinical validity and accuracy of a deep learning-based automatic landmarking algorithm for cone-beam computed tomography (CBCT). Three-dimensional (3D) CBCT head measurements obtained through manual and automatic landmarking were compared. Materials and Methods: A total of 80 CBCT scans were divided into 3 groups: non-surgical (39 cases); surgical without hardware, namely surgical plates and mini-screws (9 cases); and surgical with hardware (32 cases). Each CBCT scan was analyzed to obtain 53 measurements, comprising 27 lengths, 21 angles, and 5 ratios, which weredetermined based on 65 landmarks identified using either a manual or a 3D automatic landmark detection method. Results: In comparing measurement values derived from manual and artificial intelligence landmarking, 6 items displayed significant differences: R U6CP-L U6CP, R L3CP-L L3CP, S-N, Or_R-R U3CP, L1L to Me-GoL, and GoR-Gn/S-N (P<0.05). Of the 3 groups, the surgical scans without hardware exhibited the lowest error, reflecting the smallest difference in measurements between human- and artificial intelligence-based landmarking. The timerequired to identify 65 landmarks was approximately 40-60 minutes per CBCT volume when done manually,compared to 10.9 seconds for the artificial intelligence method (PC specifications: GeForce 2080Ti, 64GB RAM, and an Intel i7 CPU at 3.6 GHz). Conclusion Measurements obtained with a deep learning-based CBCT automatic landmarking algorithm were similar in accuracy to values derived from manually determined points. By decreasing the time required to calculatethese measurements, the efficiency of diagnosis and treatment may be improved.

OBJECTIVE: We investigated how mental health awareness among North Korean refugees transformed depending on temporal-spatial context changes. METHODS: In 2013, we conducted interviews with 10 refugees (eight women) who had been in South Korea for over a year and performed a qualitative analysis of the change in mental health awareness in the differences between living in North Korea, escape (a related period of forced sojourn in a third country), and settlement in South Korea. RESULTS: We classified 39 concepts into five main categories. The first two categories (while living in North Korea) were “a mindset for the system, but not for individual mental health” and “being confined in a social environment that was indifferent to mental health.” A third category appeared during escape: “focusing on survival amid continuity of intense suffering.” The final two categories appeared when settling in South Korea: “recognition of mental health amid cultural shock” and “introspection and sorting oneself out.” CONCLUSION: This qualitative study enabled a better multi-dimensional understanding of the social and cultural aspects involved in improving mental health awareness among North Korean refugees in South Korea. It is desirable to integrate mental health as a part of daily life and to expand training for North Korean settlers.
Democratic People's Republic of Korea ; Humans ; Korea ; Mental Health* ; Qualitative Research* ; Refugees* ; Social Environment ; United Nations

Objective: We aimed to identify the association between low serum total cholesterol levels and the risk of out-of-hospital cardiac arrest (OHCA). Methods: This case-control study was performed using datasets from the Cardiac Arrest Pursuit Trial with Unique Registration and Epidemiologic Surveillance (CAPTURES) project and the Korea National Health and Nutrition Examination Survey (KNHANES). Cases were defined as emergency medical service-treated adult patients who experienced OHCA with a presumed cardiac etiology from the CAPTURES project dataset. Four controls from the KNHANES dataset were matched to each case based on age, sex, and county. Multivariable conditional logistic regression analysis was conducted to evaluate the effect of total cholesterol levels on OHCA. Results: A total of 607 matched case-control pairs were analyzed. We classified total cholesterol levels into six categories (<148, 148-166.9, 167-189.9, 190-215.9, 216.237.9, and ≥238 mg/dL) according to the distribution of total cholesterol levels in the KNHANES dataset. Subjects with a total cholesterol level of 167-189.9 mg/dL (25th.49th percentile of the KNHANES dataset) were used as the reference group. In both the adjusted models and sensitivity analysis, a total cholesterol level of <148 mg/dL was significantly associated with OHCA (adjusted odds ratio [95% confidence interval], 6.53 [4.47.9.56]). Conclusion We identified an association between very-low total cholesterol levels and an increased risk of OHCA in a large, community-based population. Future prospective studies are needed to better understand how a low lipid profile is associated with OHCA.

Osteoclasts (OCs) are clinically important cells that resorb bone matrix. Accelerated bone destruction by OCs is closely linked to the development of metabolic bone diseases. In this study, we screened novel chemical inhibitors targeting OC differentiation to identify drug candidates for metabolic bone diseases. We identified that 1,3-dibenzyl-5-fluorouracil, also named OCI-101, is a novel inhibitor of osteoclastogenesis. The formation of multinucleated OCs is reduced by treatment with OCI-101 in a dose-dependent manner. OCI-101 inhibited the expression of OC markers via downregulation of receptor activator of NF-κB ligand and M-CSF signaling pathways. Finally, we showed that OCI-101 prevents ovariectomy-induced bone loss by suppressing OC differentiation in mice. Hence, these results demonstrated that OCI-101 is a good drug candidate for treating metabolic bone diseases.

BACKGROUND: Injury is a major public health problem and accounts for 10% of the global burden of disease. This study intends to present the temporal trend in the injury burden in Korea and to compare the burden size by injury mechanism and age group. METHODS: This study was a nationwide population-based observational study. We used two data sets, the death certificates statistics and the Korean National Hospital Discharge Survey data (2004–2012). We calculated age-standardized disability-adjusted life year (DALY) from years of life lost (YLL) and years lived with disability (YLD) and trend analysis. RESULTS: The DALYs of road injury decreased (P = 0.002), falls did not exhibit a trend (P = 0.108), and self-harm increased overall (P = 0.045). In the road injury, the YLLs decreased across all 4 age groups (0–14, 15–49, 50–79, ≥ 80) and the YLDs decreased in the 0–14-year-old group. In total, the DALYs of road injuries decreased in the 0–14-year-old group. In the fall injury, although the YLLs decreased in the over 80-year-old group, the YLDs increased in the 50–79-year-old group and the over 80-year-old group. The burden of self-harm injury was high in the age group 15 years and over, especially in the 15–49-year-old group. CONCLUSION: The leading causes of the injury burden were road injuries, falls, and self-harm. The burden of road injury and self-harm have recently shown a gradual decreasing tendency. On the other hands, that of fall injuries are continually high in the age group over 50 years of age.
Accidental Falls ; Accidents, Traffic ; Aged, 80 and over ; Dataset ; Death Certificates ; Hand ; Health Care Surveys ; Humans ; Korea* ; Observational Study ; Public Health ; Suicide

Background: Human papillomavirus (HPV) infection is a major global disease burden and the main cause of cervical cancer. Certain HPV genotypes, with are the most common etiologic pathogens and cause a significant disease burden, are being targeted for vaccine development. However, few studies have focused on the comparative effectiveness of the bivalent HPV (2v-HPV), quadrivalent HPV (4v-HPV), and nonavalent HPV (9v-HPV) vaccines against HPV strain-specific infection. This study investigated the comparative effects of these vaccines against genotype-specific infection. Materials and Methods: We conducted a pairwise and network meta-analysis of published randomized clinical trials of HPV vaccines according to sex and HPV infection status for nine HPV genotypes (HPV 6/11/16/18/31/33/45/52/58). Results: Overall, 10 randomized controlled trials (12 articles) were included in this study. In the network metaanalysis, no statistically significant differences were observed in the prevention of carcinogenic HPV strains (16/18/31/33/45/52/58) between the 2v-HPV and 4v-HPV vaccines in female HPV infection–naïve populations. However, the 9v-HPV vaccine showed a significantly superior effect compared with 2v-HPV and 4v-HPV vaccines in preventing HPV 31/33/45/52/58 infections. Although 2v-HPV and 4v-HPV vaccines provided some cross-protection against HPV 31/33/45/52/58 infections, the effect was significant only on HPV 31 infection. For HPV 16 and 18, neither statistically significant nor small differences were found in the prevention of HPV infection among the 2v-HPV, 4v-HPV, and 9v-HPV vaccines. Conclusion Our study complements previous understanding of how the effect of HPV vaccines differs according to the HPV genotype. This is important because HPV genotype prevalence varies among countries. We advocate for continued efforts in vaccinating against HPV, while public health agencies should consider the difference in the vaccine effect and HPV genotype prevalence when implementing HPV vaccination in public vaccination programs.