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.

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.

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.

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.

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.