Background: and Purpose: Amyloid-beta (Aβ) plaques are key in Alzheimer’s disease (AD), with Aβ positron emission tomography imaging enabling non-invasive quantification.To address regional Aβ deposition, we developed regional Centiloid scales (rdcCL) and commercialized them through the computed tomography (CT)-based BeauBrain Amylo platform, eliminating the need for three-dimensional T1 magnetic resonance imaging (MRI). Objective: We aimed to establish robust regional Aβ cutoffs using the commercialized BeauBrain Amylo platform and to explore the prevalence of subgroups defined by global, regional, and striatal Aβ cutoffs across cognitive stages. Methods: We included 2,428 individuals recruited from the Korea-Registries to Overcome Dementia and Accelerate Dementia Research project. We calculated regional Aβ cutoffs using Gaussian Mixture Modeling. Participants were classified into subgroups based on global, regional, and striatal Aβ positivity across cognitive stages (cognitively unimpaired [CU], mild cognitive impairment, and dementia of the Alzheimer’s type). Results: MRI-based and CT-based global Aβ cutoffs were highly comparable and consistent with previously reported Centiloid values. Regional cutoffs revealed both similarities and differences between MRI- and CT-based methods, reflecting modality-specific segmentation processes. Subgroups such as global(−)regional(+) were more frequent in non-dementia stages, while global(+)striatal(−) was primarily observed in CU individuals. Conclusions Our study established robust regional Aβ cutoffs using a CT-based rdcCL method and demonstrated its clinical utility in classifying amyloid subgroups across cognitive stages. These findings highlight the importance of regional Aβ quantification in understanding amyloid pathology and its implications for biomarker-guided diagnosis and treatment in AD.

Background: and Purpose: Amyloid-beta (Aβ) plaques are key in Alzheimer’s disease (AD), with Aβ positron emission tomography imaging enabling non-invasive quantification.To address regional Aβ deposition, we developed regional Centiloid scales (rdcCL) and commercialized them through the computed tomography (CT)-based BeauBrain Amylo platform, eliminating the need for three-dimensional T1 magnetic resonance imaging (MRI). Objective: We aimed to establish robust regional Aβ cutoffs using the commercialized BeauBrain Amylo platform and to explore the prevalence of subgroups defined by global, regional, and striatal Aβ cutoffs across cognitive stages. Methods: We included 2,428 individuals recruited from the Korea-Registries to Overcome Dementia and Accelerate Dementia Research project. We calculated regional Aβ cutoffs using Gaussian Mixture Modeling. Participants were classified into subgroups based on global, regional, and striatal Aβ positivity across cognitive stages (cognitively unimpaired [CU], mild cognitive impairment, and dementia of the Alzheimer’s type). Results: MRI-based and CT-based global Aβ cutoffs were highly comparable and consistent with previously reported Centiloid values. Regional cutoffs revealed both similarities and differences between MRI- and CT-based methods, reflecting modality-specific segmentation processes. Subgroups such as global(−)regional(+) were more frequent in non-dementia stages, while global(+)striatal(−) was primarily observed in CU individuals. Conclusions Our study established robust regional Aβ cutoffs using a CT-based rdcCL method and demonstrated its clinical utility in classifying amyloid subgroups across cognitive stages. These findings highlight the importance of regional Aβ quantification in understanding amyloid pathology and its implications for biomarker-guided diagnosis and treatment in AD.

Background: and Purpose: Amyloid-beta (Aβ) plaques are key in Alzheimer’s disease (AD), with Aβ positron emission tomography imaging enabling non-invasive quantification.To address regional Aβ deposition, we developed regional Centiloid scales (rdcCL) and commercialized them through the computed tomography (CT)-based BeauBrain Amylo platform, eliminating the need for three-dimensional T1 magnetic resonance imaging (MRI). Objective: We aimed to establish robust regional Aβ cutoffs using the commercialized BeauBrain Amylo platform and to explore the prevalence of subgroups defined by global, regional, and striatal Aβ cutoffs across cognitive stages. Methods: We included 2,428 individuals recruited from the Korea-Registries to Overcome Dementia and Accelerate Dementia Research project. We calculated regional Aβ cutoffs using Gaussian Mixture Modeling. Participants were classified into subgroups based on global, regional, and striatal Aβ positivity across cognitive stages (cognitively unimpaired [CU], mild cognitive impairment, and dementia of the Alzheimer’s type). Results: MRI-based and CT-based global Aβ cutoffs were highly comparable and consistent with previously reported Centiloid values. Regional cutoffs revealed both similarities and differences between MRI- and CT-based methods, reflecting modality-specific segmentation processes. Subgroups such as global(−)regional(+) were more frequent in non-dementia stages, while global(+)striatal(−) was primarily observed in CU individuals. Conclusions Our study established robust regional Aβ cutoffs using a CT-based rdcCL method and demonstrated its clinical utility in classifying amyloid subgroups across cognitive stages. These findings highlight the importance of regional Aβ quantification in understanding amyloid pathology and its implications for biomarker-guided diagnosis and treatment in AD.

Background: and Purpose: Amyloid-beta (Aβ) plaques are key in Alzheimer’s disease (AD), with Aβ positron emission tomography imaging enabling non-invasive quantification.To address regional Aβ deposition, we developed regional Centiloid scales (rdcCL) and commercialized them through the computed tomography (CT)-based BeauBrain Amylo platform, eliminating the need for three-dimensional T1 magnetic resonance imaging (MRI). Objective: We aimed to establish robust regional Aβ cutoffs using the commercialized BeauBrain Amylo platform and to explore the prevalence of subgroups defined by global, regional, and striatal Aβ cutoffs across cognitive stages. Methods: We included 2,428 individuals recruited from the Korea-Registries to Overcome Dementia and Accelerate Dementia Research project. We calculated regional Aβ cutoffs using Gaussian Mixture Modeling. Participants were classified into subgroups based on global, regional, and striatal Aβ positivity across cognitive stages (cognitively unimpaired [CU], mild cognitive impairment, and dementia of the Alzheimer’s type). Results: MRI-based and CT-based global Aβ cutoffs were highly comparable and consistent with previously reported Centiloid values. Regional cutoffs revealed both similarities and differences between MRI- and CT-based methods, reflecting modality-specific segmentation processes. Subgroups such as global(−)regional(+) were more frequent in non-dementia stages, while global(+)striatal(−) was primarily observed in CU individuals. Conclusions Our study established robust regional Aβ cutoffs using a CT-based rdcCL method and demonstrated its clinical utility in classifying amyloid subgroups across cognitive stages. These findings highlight the importance of regional Aβ quantification in understanding amyloid pathology and its implications for biomarker-guided diagnosis and treatment in AD.

Background: Dipeptidyl peptidase-4 (DPP4) inhibitors are frequently prescribed for patients with type 2 diabetes; however, their cost can pose a significant barrier for those with impaired kidney function. This study aimed to estimate the economic benefits of substituting non-renal dose-adjusted (NRDA) DPP4 inhibitors with renal dose-adjusted (RDA) DPP4 inhibitors in patients with both impaired kidney function and type 2 diabetes. Methods: This retrospective cohort study was conducted from January 1, 2012 to December 31, 2018, using data obtained from common data models of five medical centers in Korea. Model 1 applied the prescription pattern of participants with preserved kidney function to those with impaired kidney function. In contrast, model 2 replaced all NRDA DPP4 inhibitors with RDA DPP4 inhibitors, adjusting the doses of RDA DPP4 inhibitors based on individual kidney function. The primary outcome was the cost difference between the two models. Results: In total, 67,964,996 prescription records were analyzed. NRDA DPP4 inhibitors were more frequently prescribed to patients with impaired kidney function than in those with preserved kidney function (25.7%, 51.3%, 64.3%, and 71.6% in patients with estimated glomerular filtration rates [eGFRs] of ≥60, <60, <45, and <30 mL/min/1.73 m2, respectively). When model 1 was applied, the cost savings per year were 7.6% for eGFR <60 mL/min/1.73 m2 and 30.4% for eGFR <30 mL/min/1.73 m2. According to model 2, 15.4% to 51.2% per year could be saved depending on kidney impairment severity. Conclusion Adjusting the doses of RDA DPP4 inhibitors based on individual kidney function could alleviate the economic burden associated with medical expenses.

Objective: This study evaluated the efficacy and effectiveness of a new patient handover system developed for better handover in a metropolitan emergency department (ED). Methods: A retrospective observational study was designed to evaluate the appropriateness and satisfaction level of the new ED handover system. The participants were pre-hospital emergency medical service (EMS) providers with patient transport experience before and after the pilot of the new handover system. Results: A questionnaire was completed by 37 pre-hospital EMS providers who transported patients to the emergency department. Based on the results, pre-hospital EMS providers felt an increased level of kindness from the ED healthcare professionals during patient handover (P<0.001), from 3.19±1.05 points before the introduction of the system to 3.97±0.96 points after its introduction, and the activeness of ED healthcare professionals also increased, from 3.35±1.03 to 4.14±0.86 points (P<0.001). The sufficiency of contents of patient handover information to explain a patient’s condition increased from 3.59±0.76 to 4.08±0.72 points (P<0.003). The score for overall satisfaction felt by the EMS providers during patient handover increased from 3.46±0.96 to 3.76±0.86 points, which was not statistically significant (P=0.020). Conclusion Our findings suggest that the introduction of a new patient handover system between EMS providers and the ED staff is effective for both pre-hospital EMS providers and ED staff.

Background and Objectives: Accumulating evidence shows that sodium-glucose cotransporter 2 inhibitors (SGLT2is) reduce adverse cardiovascular outcomes. However, whether SGLT2i, compared with other antidiabetic drugs, reduce the new development of atrial fibrillation (AF) is unclear. In this study, we compared SGLT2i with dipeptidyl peptidase-4 inhibitors (DPP-4is) in terms of reduction in the risk of AF in individuals with type 2 diabetes. Methods: We included 42,786 propensity score-matched pairs of SGLT2i and DPP-4i users without previous AF diagnosis using the Korean National Health Insurance Service database between May 1, 2016, and December 31, 2018. Results: During a median follow-up of 1.3 years, SGLT2i users had a lower incidence of AF than DPP-4i users (1.95 vs. 2.65 per 1,000 person-years; hazard ratio [HR], 0.73; 95% confidence interval [CI], 0.55–0.97; p=0.028]). In individuals without heart failure, SGLT2i users was associated with a decreased risk of AF incidence (HR, 0.70; 95% CI, 0.52–0.94; p=0.019) compared to DPP-4i users. However, individuals with heart failure, SGLT2i users was not significantly associated with a change in risk (HR, 1.04; 95% CI, 0.44–2.44; p=0.936). Conclusions In this nationwide cohort study of individuals with type 2 diabetes, treatment with SGLT2i was associated with a lower risk of AF compared with treatment with DPP-4i.

OBJECTIVES: This study compared the current smoking prevalence among adults with human immunodeficiency virus (HIV) infection to that of the general Korean population and analyzed changes in smoking prevalence and cessation rates from 2009 to 2020. METHODS: The study included a total of 10,980 adults with HIV infection who underwent a health screening examination (National Health Insurance Service-National Health Information Database; NHIS-NHID), 1,230 individuals with HIV infection who participated in the Korea HIV/AIDS Cohort (KoCosHIV), and 76,783 participants from the Korea National Health and Nutrition Examination Survey (KNHANES). We estimated the current smoking prevalence and the quit ratio, defined as the ratio of former smokers to ever-smokers. RESULTS: In the NHIS-NHID and KoCosHIV studies, the prevalence of current and former smoking among adults with HIV was 44.2% (95% confidence interval [CI], 43.2 to 45.1) and 15.6% (95% CI, 14.9 to 16.3), and 47.7% (95% CI, 43.7 to 51.8) and 16.9% (95% CI, 11.8 to 22.0), respectively. In the KNHANES, these rates were 22.5% and 18.1%, respectively. The standardized prevalence ratio of current smoking among adults with HIV was 1.76 in the NHIS-NHID and 1.97 in the KoCosHIV. Furthermore, the likelihood of quitting smoking was lower among adults with HIV than in the general population (NHIS-NHID: 26.1%; 95% CI, 25.0 to 27.1; KoCosHIV: 26.2%; 95% CI, 20.2 to 32.1; KNHANES: 44.6%; 95% CI, 44.5 to 44.6). Among HIV-positive adults, there was a 1.53% decline in the current smoking rate and a 2.86% increase in the quit ratio. CONCLUSIONS Adults with HIV were more likely to smoke and less likely to quit smoking than the general adult population. Tobacco screening and cessation strategies should specifically target this population.

Purpose: This study aims to find ways to reduce the reality shock of newly graduated nurses by exploring the relationship between nursing practice readiness, social support from clinical nurse educators, and reality shock. Methods: From August 24 to September 13, 2023, data were collected from 134 newly graduated nurses with less than 12 months of clinical experience, who were trained by clinical nurse educators at one general hospital and two tertiary hospitals in I City and G Province. The data were analyzed using descriptive statistics, independent t-test, one-way analysis of variance, Pearson’s correlation coefficient, and hierarchical multiple regression with the SPSS/WIN 28.0 program. Results: Reality shock was negatively correlated with nursing practice readiness (r=-.50, p<.001) and social support (r=-.19, p=.03), while nursing practice readiness was positively correlated with social support (r=.37, p<.001). Nursing practice readiness was identified as a significant predictor of reality shock in newly graduated nurses (β=-.46, p<.001), accounting for 31% of the variance in reality shock (F=18.82, p<.001). Conclusion To alleviate the reality shock of newly graduated nurses, it is important to improve their practice readiness and ensure systematic, continuous education for clinical nurse educators.