Aims: Metabolic syndrome (MetS) increases the risk of diabetes mellitus (DM), cardiovascular disease (CVD), cancer, and mortality. Sarcopenia has been reported as a risk factor for MetS, non-alcoholic fatty liver disease, and CVD. To date, the association between sarcopenia and MetS has been investigated. However, there have been few studies on the dose-response relationship between sarcopenia and MetS. We investigated the association between sarcopenia and the prevalence of MetS. We also aimed to analyze the dose-response relationship between skeletal muscle mass and the prevalence of MetS. Methods: We enrolled 13,620 participants from October 2014 to December 2019. Skeletal muscle mass was measured using bioelectrical impedance analysis (BIA). Appendicular skeletal muscle mass (ASM) was divided by body weight (kg) and was expressed as a percentage (ASM x 100/Weight, ASM%). The quartiles of ASM% were calculated for each gender, with Q1 and Q4 being the lowest and highest quartiles of ASM%, respectively. The quartiles of ASM% were calculated for each gender, with Q1 and Q4 being the lowest and highest quartiles of ASM%, respectively. Linear regression and logistic regression analyses were used to compare the clinical parameters according to ASM%, adjusted for age, sex, obesity, hypertension (HT), DM, dyslipidemia (DL), smoking, alcohol intake, and C-reactive protein (CRP). Multiple logistic regression analysis was performed to determine the risk of MetS in each group. Results: A dose-response relationship was identified between ASM% and MetS. Sarcopenia was associated with an increased prevalence of MetS. After adjustment for age, sex, obesity, HT, DM, DL, smoking, alcohol intake, and CRP, sarcopenia remained significantly associated with MetS. For each 1 quartile increment in ASM%, the risk of MetS decreased by 56% (P< 0.001). After adjusting for age, sex, obesity, HT, DM, DL, smoking, alcohol intake, and CRP, the risk of MetS decreased by 25% per 1Q increment in ASM% (P < 0.001). Conclusions: Sarcopenia by BIA is independently associated with the risk of MetS and has a dose-response relationship.

Park SW, et al. J Korean Med Sci. 2024 Jan;39:e53. https://doi.org/10.3346/jkms.2024.39.e53

Background and objective: The incidence of facial fractures is on the rise globally, yet limited studies are addressing the diverse forms of facial fractures present in 3D images. In particular, due to the nature of the facial fracture, the direction in which the bone fractures vary, and there is no clear outline, it is difficult to determine the exact location of the fracture in 2D images. Thus, 3D image analysis is required to find the exact fracture area, but it needs heavy computational complexity and expensive pixel-wise labeling for supervised learning. In this study, we tackle the problem of reducing the computational burden and increasing the accuracy of fracture localization by using a weakly-supervised object localization without pixel-wise labeling in a 3D image space. Methods: We propose a Very Fast, High-Resolution Aggregation 3D Detection CAM (VFHA-CAM) model, which can detect various facial fractures. To better detect tiny fractures, our model uses high-resolution feature maps and employs Ablation CAM to find an exact fracture location without pixel-wise labeling, where we use a rough fracture image detected with 3D box-wise labeling. To this end, we extract important features and use only essential features to reduce the computational complexity in 3D image space. Results: Experimental findings demonstrate that VFHA-CAM surpasses state-of-the-art 2D detection methods by up to 20% in sensitivity/person and specificity/person, achieving sensitivity/person and specificity/person scores of 87% and 85%, respectively. In addition, Our VFHA-CAM reduces location analysis time to 76 s without performance degradation compared to a simple Ablation CAM method that takes more than 20 min. Conclusion: This study introduces a novel weakly-supervised object localization approach for bone fracture detection in 3D facial images. The proposed method employs a 3D detection model, which helps detect various forms of facial bone fractures accurately. The CAM algorithm adopted for fracture area segmentation within a 3D fracture detection box is key in quickly informing medical staff of the exact location of a facial bone fracture in a weakly-supervised object localization. In addition, we provide 3D visualization so that even non-experts unfamiliar with 3D CT images can identify the fracture status and location.

Hypothyroidism is a recognized sequela of conventional thyroid lobectomy. However, there have been no studies on the incidence of hypothyroidism following the preservation of the isthmus and pyramid during lobectomy. Therefore, in the present study, we compared the incidence of hypothyroidism following conventional lobectomy and lobectomy during which the isthmus and pyramidal lobe were preserved. Data for a total of 65 patients collected between September 2018 and April 2019 were reviewed retrospectively. Circulating thyroid-stimulating hormone (TSH) concentration was measured before and after surgery in a group who underwent conventional thyroid lobectomy (n=29) and in a group in which the isthmus and pyramid were preserved (n=36). We found no significant difference in TSH concentration between the two groups before surgery, or 3 months or 1 year after surgery. Thus, there might be no difference in the incidence of postoperative hypothyroidism between patients who undergo conventional thyroid lobectomy and those in which the isthmus and pyramid are preserved.

Purpose: Prescription drug requests and physician denial are important aspects of medical decision making, but little research has been done to identify factors linked to prescription drug request and physician denial. This paper aims to explore factors in relation to patient prescription drug request and provider denial.Design/methodology/approach: The paper is based on a cross‐sectional study in a nationally representative database of 2,988 individuals. Descriptive and multivariate stepwise conditional logistic regression analyses were conducted.Findings: Results of multivariate regression models reveal, after adjusting for personal factors, that heart disease, allergy, anxiety, minor chronic conditions, medical seeking behaviors and direct‐to‐consumer advertising (DTCA) were found to be related to prescription drug request. The denied were individuals with arthritis, less prevalent chronic conditions, the uninsured, and African Americans. It was also found that 27.4 percent of the sample requested a prescription drug and about 24 percent of those who segmented for prescriptions were physicians.Research limitations/implications: DTCA is positively associated with prescription drug requests but the analysis did not support any effect of DTCA on the refusal status. Patients' requests and physician decision making to refuse are somewhat complicated and vary with different medical conditions.Originality/value: The paper, using nationally representative data, investigates the factors associated with prescription drug request and denial.