Background/Objectives: Hyperglycemia in hospitalized patients is associated with an increased risk of complications, morbidity, mortality, and healthcare costs, regardless of a prior diagnosis of diabetes. The hospitalist system can improve various outcomes, including length of stay, medical costs, patient satisfaction, and mortality rates. However, the effects of hospitalist care on blood glucose control in hospitalized patients remain unclear. This study aimed to assess the specific effects of hospitalist services on blood glucose control in hospitalized patients, with a focus on hyperglycemia management and patient outcomes. Methods: This retrospective study reviewed the electronic medical records of patients diagnosed with diabetes at Yonsei Severance Hospital in Yongin, between March 2020 and February 2022. It included adults aged ≥20 years who were hospitalized and had undergone blood glucose measurements during hospitalization. Glycemic control was assessed using hemoglobin A1c, and the blood glucose levels were measured four times daily during hospitalization. Variability was quantified using the coefficient of variation and compared between hospitalist-led and traditional specialty care groups, over a 14-day hospitalization period. Results: Despite a higher baseline risk profile, patients receiving hospitalist-led care experienced significantly more stable glycemic variability over time (p = 0.002), suggesting better inpatient glucose management than those receiving traditional specialty care. Conclusions: Hospitalist-led care was associated with more stable glycemic variability over time in hospitalized patients with diabetes, despite a higher baseline burden of comorbidities and poorer glycemic control at admission.

ABSTRACT Background Hospital falls are the most prevalent and fatal event in healthcare, posing significant risks to patient health outcomes and institutional care quality. Real‐time location system (RTLS) enables continuous tracking of patient location, providing a unique opportunity to monitor changes in physical activity, a key factor related to the risk of falls in hospitals. This study is aimed at utilizing RTLS data to capture dynamic patient movements, integrating it with clinical information through a machine learning approach to enhance in‐hospital fall predictions. Methods This retrospective study developed and compared three models: clinical data only, RTLS data only and a combined data model. It included 22 201 patients from Yongin Severance Hospital, South Korea, from March 2020 to June 2022, with 118 fall patients and 443 nonfall patients selected through random sampling and relevant criteria for detailed analysis, totaling 561 patients. The average age of the participants was 70.1 years, with a median of 71.0 years (IQR: 60.0–80.0). Among participants, 52.6% (n = 295) were male. This study evaluated the occurrence of the first fall during hospitalization. The performance was assessed using the area under the receiver operating characteristic (AUROC), the area under the precision‐recall curve (AUPRC) and the Brier score. The Shapley additive explanations (SHAP) method and decision curve analysis (DCA) were employed to enhance model explainability and assess the clinical utility of the models. Results The RTLS model showed significant predictive accuracy for hospital falls, with an AUROC of 0.813 (95% CI: 0.703–0.903). The clinical + RTLS model outperformed those using only one type of data, achieving an AUROC of 0.847 (95% CI: 0.764–0.917), AUPRC of 0.667 (95% CI: 0.472–0.816) and Brier score of 0.120 (95% CI: 0.083–0.162), with significant differences in performance metrics (p < 0.0001). DCA confirmed its greater clinical benefit. SHAP analysis indicated that patients who experienced falls tended to have less active time and slower movement speed just before the fall compared to the early hospitalization period, despite attempting to move more. Additionally, higher fall incidence was significantly associated with sedative use and higher red cell distribution width (RDW) levels. Conclusion This study underscores the capability of utilizing RTLS to predict in‐hospital falls by tracking the changes of patients' physical activity through a machine learning approach. This may improve early fall risk detection during hospitalization, thereby preventing falls and enhancing patient safety.

Despite the increasing number of anti-osteoporotic medications for improving bone mineral density (BMD) and reducing fracture risk, some patients show unsatisfactory responses. We retrospectively analyzed 2134 patients who received anti-osteoporotic medications between March 2020 and October 2024. BMD percentage changes at the lumbar spine, femoral neck, and total hip were assessed after 1 year. Patients were categorized as “non-BMD gainers” (<3

AimsWe investigated the feasibility and effects of using large language models (LLMs), particularly GPTs, to support the selection of anti-diabetic medications for T2DM management based on individual-level clinical information.Materials and MethodsThis retrospective study included adults diagnosed with T2DM who visited the Endocrine Department at Yongin Severance Hospital. ChatGPT 4.0 was used with zero-shot and few-shot learning approaches to recommend treatments based on clinical data. Concordance between ChatGPT's recommendations and clinician prescriptions for monotherapy, dual therapy, and triple therapy was categorised as agree, partially agree, and disagree.ResultsAmong the 85 individuals included, the overall concordance rate was highest for monotherapy and decreased as the treatment regimen became more complex. In treatment-naive individuals, agreement rates were 69.2% (1st), 69.2% (2nd), and 84.6% (3rd) for monotherapy; 12.5% (1st), 20.8% (2nd), and 0% (3rd) for dual therapy; and 0% at all three assessment points for triple therapy. The concordance rate was lower for individuals with prior treatment history. Few-shot prompting improved agreement compared with zero-shot, particularly for monotherapy and dual therapy.ConclusionChatGPT shows potential as a decision-support tool for selecting anti-diabetic medications, particularly for treatment-naive individuals. Few-shot learning demonstrated improvements in recommendation accuracy, especially for simpler regimens. However, accuracy was notably limited in complex regimens such as triple therapy, highlighting the need for further refinement before clinical use.

BACKGROUND:This study aimed to investigate the association between handgrip strength (HGS) and cardiovascular disease (CVD) in individuals with metabolic dysfunction-associated steatotic liver disease (MASLD) using data from the UK Biobank cohort. METHODS:A total of 201 563 participants were enrolled in this study. The HGS was measured using a Jamar J00105 hydraulic hand dynamometer. MASLD was defined as the presence of hepatic steatosis accompanied by one or more cardiometabolic criteria. Hepatic steatosis was identified using a fatty liver index ≥ 60. Advanced liver fibrosis was defined by a fibrosis-4 (FIB-4) score > 2.67. To examine the differences in the incidence of CVD, male and female participants were divided into non-MASLD, MASLD with high HGS, MASLD with middle HGS, and MASLD with low-HGS groups. RESULTS:Of the study participants, 75 498 (37.5%) were diagnosed with MASLD, with a mean age of 56.5 years, and 40.6% were male. The median follow-up duration was 13.1 years. The frequency of incident CVD events increased significantly across groups: 10.9% in non-MASLD, 13.3% in MASLD with high HGS, 14.8% in MASLD with middle HGS, and 18.4% in MASLD with low HGS for males (p < 0.001). In females, the frequency of incident CVD events was 6.1% in non-MASLD, 9.2% in MASLD with high HGS, 10.7% in MASLD with middle HGS, and 13.3% in MASLD with low HGS (p < 0.001). Using the non-MASLD group as a reference, multivariate-adjusted hazard ratios (HRs) (95% confidence intervals [CI]) for CVD varied according to HGS in individuals with MASLD. In males with MASLD, HRs (95% CI) were 1.03 (0.96-1.10) for high HGS, 1.14 (1.07-1.21) for middle HGS, and 1.38 (1.30-1.46) for low HGS; in females with MASLD, they were 1.07 (0.97-1.18) for high HGS, 1.25 (1.14-1.37) for middle HGS, and 1.56 (1.43-1.72) for low HGS. The incidence of CVD events increased as HGS decreased in participants with MASLD, regardless of the presence or absence of advanced liver fibrosis (all p < 0.001). CONCLUSIONS:This large prospective cohort study using the UK Biobank showed that in MASLD, a decrease in HGS was associated with increased CVD risk.

Introduction and Objective: Glycemic variability (GV) is associated with poor glycemic control and complications in patients with T2DM. The coefficient of variation (CV) derived from CGM has been widely used as a reliable measure of GV. Methods: A total of 773 patients with T2DM were included. A multivariate linear regression model was used to assess independent associations between CV and clinical factors, including age, sex, BMI, diabetes duration, HbA1c, use of antidiabetic medications, and estimated glomerular filtration rate (eGFR). A subgroup analysis of 396 patients with HbA1c <7.5% was also performed. Results: The mean age was 53.37±11.74 years, and 60.4% were male. Higher age was significantly associated with increased CV (β=0.08, p<0.001). Lower BMI (<18.5kg/m²) was significantly associated with higher CV compared to normal BMI (18.5-25 kg/m²) (β=4.40, p=0.006), while BMI 25-30 kg/m² was associated with lower CV (β=-0.94, p=0.046). Longer diabetes duration (≥10 years vs. <5 years) (β=3.24, p<0.001) and higher HbA1c (≥9.0% vs. <7.5%) (β = 1.44, p=0.010) were associated with increased CV. Use of oral combination therapy with three agents (β=2.31, p=0.010), GLP-1 RAs (β=2.14, p=0.005), and insulin (β=4.63, p<0.001) were also associated with higher CV. Additionally, in the subgroup analysis of patients with HbA1c <7.5%, similar patterns of association were observed; higher age, lower BMI (<18.5 kg/m²), use of triple oral agents, GLP-1 RAs, and insulin were significantly associated with higher CV. Conclusion: Higher age, lower BMI, longer diabetes duration, higher HbA1c, and use of triple oral therapy, GLP-1 RAs, and insulin were associated with greater GV in patients with T2DM. Our study suggests that GV management strategies should consider these clinical factors to improve glycemic stability. S. Jang: None. S. Kwon: None. W. Hong: None. C. Kim: None. S. Park: None. K. Kim: None.

Background: Inhibitory effects of denosumab on bone remodeling are reversible and disappear once treatment is discontinued. Herein, we examined whether and to what extent delayed denosumab administration is also associated with fracture risk using nation-wide data.Methods: The study cohort included women aged 45 to 89 years who were started on denosumab for osteoporosis between October 2017 and December 2019 using data from the Korean Health Insurance Review and Assessment service. Participants were stratified according to the time of their subsequent denosumab administration from the last denosumab administration, including those with within 30 days early dosing (ED30), within the planned time of 180–210 days (referent), within 30–90 days of delayed dosing (DD90), within 90–180 days of delayed dosing (DD180), and longer than 181 days of delayed dosing (DD181+). The primary outcome was the incidence of all clinical fractures.Results: A total of 149,199 participants included and 2,323 all clinical fractures (including 1,223 vertebral fractures) occurred. The incidence of all fractures was significantly higher in the DD90 compared to reference group (hazard ratio [HR], 1.2; 95% confidence interval [CI], 1.1 to 1.4). The risk of all fracture was even higher in the longer delayed DD180 group (HR, 1.9; 95% CI, 1.6 to 2.3) and DD181+ group (HR, 1.8; 95% CI, 1.5 to 2.2). Increased risks of fractures with delayed dosing were consistently observed for vertebral fractures.Conclusion: Delayed denosumab dosing, even by 1 to 3 months, was significantly associated with increased fracture risk. Maintaining the correct dosing schedule should be emphasized when starting denosumab.

Several studies have shown that hyperglycemia and a history of diabetes mellitus (DM) are liked to poor outcomes in hospitalized patients. However, about one third of patients with diabetes are left undiagnosed until they admitted to the hospital. The impacts of undiagnosed or newly diagnosed diabetes on hospitalization-related outcomes are not well studied. In this study, we aimed to evaluate hospitalization-related outcomes in hospitalized patents according to their diabetic status at admission. This is a retrospective cohort study, and all subjects aged 20 years or older admitted to Yongin Severance hospital between March 2020 and February 2022 were included. Subjects were divided into no DM group, known DM group by a history of diabetes or taking any antidiabetic medications, and newly diagnosed DM group by results of laboratory test including HbA1c. We compared hospitalization-related outcomes such as in-hospital mortality rate and the length of hospital stay. A total of 33,166 subjects was enrolled. At hospitalization, 6,572 (19.8%) subjects were classified as known DM and another 2,634 (7.9%) subjects were classified as newly diagnosed DM. In-hospital mortality was highest in newly diagnosed DM group (hazard ratio [HR] 5.81, 95% confidence interval [CI] 4.90-6.89, p<0.001) followed by known DM group (HR 2.08, 95% CI 1.74-2.47, p<0.001) compared to no DM group. The length of hospital stay was significantly increased in newly diagnosed DM (15.5±19.3 days) compared with no DM (6.5±7.9 days) and known DM group (8.6±11.1 days) (p<0.001). After adjusting for multiple covariates, newly diagnosed diabetes was independently associated with increased in-hospital mortality (p<0.001). In conclusion, diabetic status at admission was associated with poor outcomes in hospitalized patients. Those with a newly diagnosed diabetes showed particularly high risk of in-hospital mortality and even longer length of hospital stay. Disclosure S.A. Jang: None. K. Kim: None. C. Kim: None. S. Park: None.

This study investigated the relationships of thigh and waist circumference with the glycemic variability and carotid atherosclerosis in patients with type 2 diabetes mellitus (T2DM) and prediabetes. This observational study included 3,453 Korean patients with T2DM and prediabetes, in whom anthropometric measurements and carotid ultrasonography were conducted. Carotid plaque was defined as focal structures encroaching the arterial lumen by ≥ 0.5 mm or 50% of the surrounding IMT value or a thickness ≥1.5 mm. In men with T2DM, it was found that the larger the thigh circumference, the lower the risk of carotid plaque after adjustment for potential confounding variables. In women with T2DM, a similar tendency was observed before adjustment, but no statistically significant relationship was seen after adjustment. In women with T2DM, the presence of carotid plaque was higher in the thickest waist group compared to the reference group, but there is no statistical significance after adjustment. However, no difference in carotid arteriosclerosis according to waist and thigh circumference was found in both men and women in prediabetic patients. It suggests that the risk of cardiovascular disease according to the difference in body type such as waist circumference and thigh thickness may appear differently depending on the glucose status. However, further longitudinal studies are warranted. Disclosure C.Kim: None. S.A.Jang: None. K.Kim: None. S.Park: None.

AIMS:This study evaluated the efficacy and safety of enavogliflozin, a novel sodium-glucose cotransporter 2 inhibitor, versus dapagliflozin in Korean patients with type 2 diabetes mellitus (T2DM) inadequately controlled with metformin and gemigliptin. METHODS:In this multicenter, double-blind, randomized study, patients with inadequate response to metformin (≥ 1000 mg/day) plus gemigliptin (50 mg/day) were randomized to receive enavogliflozin 0.3 mg/day (n = 134) or dapagliflozin 10 mg/day (n = 136) in addition to the metformin plus gemigliptin therapy. The primary endpoint was change in HbA1c from baseline to week 24. RESULTS:Both treatments significantly reduced HbA1c at week 24 (-0.92% in enavogliflozin group, -0.86% in dapagliflozin group). The enavogliflozin and dapagliflozin groups did not differ in terms of changes in HbA1c (between-group difference: -0.06%, 95% confidence interval [CI]: -0.19, 0.06) and fasting plasma glucose (between-group difference: -3.49 mg/dl [-8.08;1.10]). An increase in urine glucose-creatinine ratio was significantly greater in the enavogliflozin group than in the dapagliflozin group (60.2 g/g versus 43.5 g/g, P < 0.0001). The incidence of treatment-emergent adverse events was similar between the groups (21.64% versus 23.53%). CONCLUSIONS:Enavogliflozin, added to metformin plus gemigliptin, was well tolerated and as effective as dapagliflozin in the treatment of patients with T2DM.

Several studies have shown that hyperglycemia and a history of diabetes mellitus (DM) are liked to poor outcomes in hospitalized patients. However, about one third of patients with diabetes are left undiagnosed until they admitted to the hospital. The impacts of undiagnosed or newly diagnosed diabetes on hospitalization-related outcomes are not well studied. In this study, we aimed to evaluate hospitalization-related outcomes in hospitalized patents according to their diabetic status at admission. This is a retrospective cohort study, and all subjects aged 20 years or older admitted to Yongin Severance hospital between March 2020 and February 2022 were included. Subjects were divided into no DM group, known DM group by a history of diabetes or taking any antidiabetic medications, and newly diagnosed DM group by results of laboratory test including HbA1c. We compared hospitalization-related outcomes such as in-hospital mortality rate and the length of hospital stay. A total of 33,166 subjects was enrolled. At hospitalization, 6,572 (19.8%) subjects were classified as known DM and another 2,634 (7.9%) subjects were classified as newly diagnosed DM. In-hospital mortality was highest in newly diagnosed DM group (hazard ratio [HR] 5.81, 95% confidence interval [CI] 4.90-6.89, p<0.001) followed by known DM group (HR 2.08, 95% CI 1.74-2.47, p<0.001) compared to no DM group. The length of hospital stay was significantly increased in newly diagnosed DM (15.5±19.3 days) compared with no DM (6.5±7.9 days) and known DM group (8.6±11.1 days) (p<0.001). After adjusting for multiple covariates, newly diagnosed diabetes was independently associated with increased in-hospital mortality (p<0.001). In conclusion, diabetic status at admission was associated with poor outcomes in hospitalized patients. Those with a newly diagnosed diabetes showed particularly high risk of in-hospital mortality and even longer length of hospital stay. S.A. Jang: None. K. Kim: None. C. Kim: None. S. Park: None.

BACKGROUND:We compared the efficacy and safety of low-intensity atorvastatin and ezetimibe combination therapy with moderate-intensity atorvastatin monotherapy in patients requiring cholesterol-lowering therapy.METHODS:At 19 centers in Korea, 290 patients were randomized to 4 groups: atorvastatin 5 mg and ezetimibe 10 mg (A5E), ezetimibe 10 mg (E), atorvastatin 5 mg (A5), and atorvastatin 10 mg (A10). Clinical and laboratory examinations were performed at baseline, and at 4-week and 8-week follow-ups. The primary endpoint was percentage change from baseline in low-density lipoprotein (LDL) cholesterol levels at the 8-week follow-up. Secondary endpoints included percentage changes from baseline in additional lipid parameters.RESULTS:Baseline characteristics were similar among the study groups. At the 8-week follow-up, percentage changes in LDL cholesterol levels were significantly greater in the A5E group (49.2%) than in the E (18.7%), A5 (27.9%), and A10 (36.4%) groups. Similar findings were observed regarding the percentage changes in total cholesterol, non-high-density lipoprotein cholesterol, and apolipoprotein B levels. Triglyceride levels were also significantly decreased in the A5E group than in the E group, whereas high-density lipoprotein levels substantially increased in the A5E group than in the E group. In patients with low- and intermediate-cardiovascular risk, 93.3% achieved the target LDL cholesterol levels in the A5E group, 40.0% in the E group, 66.7% in the A5 group, and 92.9% in the A10 group. In addition, 31.4% of patients in the A5E group, 8.1% in E, 9.7% in A5, and 7.3% in the A10 group reached the target levels of both LDL cholesterol < 70 mg/dL and reduction of LDL ≥ 50% from baseline.CONCLUSIONS:The addition of ezetimibe to low-intensity atorvastatin had a greater effect on lowering LDL cholesterol than moderate-intensity atorvastatin alone, offering an effective treatment option for cholesterol management, especially in patients with low and intermediate risks.

Abstract Disclosure: S. Jang: None. K. Kim: None. C. Kim: None. S. Park: None. Introduction: The changes in body composition with aging are known to be associated with the risk of various chronic diseases. But the body composition changes with age among different races, is not well studied. This study aimed to investigate the racial differences in the changes of body composition according to age and the association with prevalent diabetes mellitus. Methods: A total of 37,153 participants was include in the study. 27,864 Korean from the Korea National Health and Nutrition Examination Surveys (KNHANES) 2008-2011 and 9,289 from the National Health and Nutrition Examination Survey (NHANES) 2003-2006 whose age ranged from 20 to 85 years were analyzed. Body composition was measured by dual-energy X-ray absorptiometry (Hologic Horizon) in both cohorts. Relative body composition measures based on young adult (20-29 years) were compared. The association of body composition measures and diabetes were analyzed. Results: Compare to other three races from NHANES, Korean men and women had a lower BMI. Total percentage fat tended to increase with age in all races, but degree of increase with age was not higher in Korean men than in other races and a similar trend was observed in Korean women. Regarding the changes in lean mass, men and women showed different patterns. In men, non-Hispanic white showed peak levels in their 40s and then tended to decrease. All other races showed peaks in their 20s and 30s, and subsequently decreased. Compared to other races, the decline according to age was the largest in Korean men. For women, in all races, the pattern was maintained even after their 20s until their 40s or 50s, and then decreased. The degree of decline was similar in all races. In men, higher fat percentage and lower lean mass were associated with prevalent diabetes in all races. In women, however, higher fat percentage and lower lean mass were associated with prevalent diabetes in only Korean and non-Hispanic white. Conclusion: The changes in body composition according to age vary by race and its association with prevalent diabetes also differs. The clinical significance of changes in body composition according to age and race in chronic diseases needs to be further clarified. Presentation: Friday, June 16, 2023