Background/Aims: This study aimed to investigate co-occurrence and clinical characteristics of sexually transmitted infections (STIs) and pelvic inflammatory disease (PID) in women hospitalized for acute pyelonephritis (APN). Methods: This single-center retrospective study reviewed medical records of inpatients with APN from January 2019 to February 2023 and identified records of 142 patients who were referred to a gynecologist to evaluate gynecological diseases including STIs. Results: Of the 142 patients, 47 were tested positive for sexually transmitted pathogens in nucleic acid amplification testing, confirming the presence of STIs. In patients with APN, those with STIs were more likely to have lower abdominal pain or cervical motion tenderness (CMT) on pelvic examination and leukocytosis (> 14.5 × 109/L) than those without STIs. Of the 93 patients who underwent pelvic examination, 34 had CMT with one or more of additional criteria for the clinical diagnosis of PID, such as abnormal vaginal discharge and leukorrhea confirmed by microscopic examination, which could be clinically diagnosed as PID. Conclusions In sexually active women with APN, it is important to evaluate the possibility of STIs and PID, considering several risk factors such as lower abdominal pain, abnormal vaginal discharge, CMT, and leukocytosis.

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/Aims: This study aimed to investigate co-occurrence and clinical characteristics of sexually transmitted infections (STIs) and pelvic inflammatory disease (PID) in women hospitalized for acute pyelonephritis (APN). Methods: This single-center retrospective study reviewed medical records of inpatients with APN from January 2019 to February 2023 and identified records of 142 patients who were referred to a gynecologist to evaluate gynecological diseases including STIs. Results: Of the 142 patients, 47 were tested positive for sexually transmitted pathogens in nucleic acid amplification testing, confirming the presence of STIs. In patients with APN, those with STIs were more likely to have lower abdominal pain or cervical motion tenderness (CMT) on pelvic examination and leukocytosis (> 14.5 × 109/L) than those without STIs. Of the 93 patients who underwent pelvic examination, 34 had CMT with one or more of additional criteria for the clinical diagnosis of PID, such as abnormal vaginal discharge and leukorrhea confirmed by microscopic examination, which could be clinically diagnosed as PID. Conclusions In sexually active women with APN, it is important to evaluate the possibility of STIs and PID, considering several risk factors such as lower abdominal pain, abnormal vaginal discharge, CMT, and leukocytosis.

Background/Aims: This study aimed to investigate co-occurrence and clinical characteristics of sexually transmitted infections (STIs) and pelvic inflammatory disease (PID) in women hospitalized for acute pyelonephritis (APN). Methods: This single-center retrospective study reviewed medical records of inpatients with APN from January 2019 to February 2023 and identified records of 142 patients who were referred to a gynecologist to evaluate gynecological diseases including STIs. Results: Of the 142 patients, 47 were tested positive for sexually transmitted pathogens in nucleic acid amplification testing, confirming the presence of STIs. In patients with APN, those with STIs were more likely to have lower abdominal pain or cervical motion tenderness (CMT) on pelvic examination and leukocytosis (> 14.5 × 109/L) than those without STIs. Of the 93 patients who underwent pelvic examination, 34 had CMT with one or more of additional criteria for the clinical diagnosis of PID, such as abnormal vaginal discharge and leukorrhea confirmed by microscopic examination, which could be clinically diagnosed as PID. Conclusions In sexually active women with APN, it is important to evaluate the possibility of STIs and PID, considering several risk factors such as lower abdominal pain, abnormal vaginal discharge, CMT, and leukocytosis.

This pilot study evaluates an artificial intelligence (AI)-assisted electrocardiography (ECG) analysis system, QCG, to enhance urgent coronary angiography (CAG) decision-making for acute chest pain in the emergency department (ED). We retrospectively analyzed 300 ED cases, categorized as non-coronary chest pain (Group 1), acute coronary syndrome (ACS) without occlusive coronary artery disease (CAD) (Group 2), and ACS with occlusive CAD (Group 3). Six clinicians made urgent CAG decision using a conventional approach (clinical data and ECG) and a QCG-assisted approach (including QCG scores). The QCG-assisted approach improved correct CAG decisions in Group 2 (36.0% vs. 45.3%, P = 0.003) and Group 3 (85.3% vs. 90.0%, P = 0.017), with minimal impact in Group 1 (92.7% vs. 95.0%, P = 0.125). Diagnostic accuracy for ACS improved from 77% to 81% with QCG assistance and reached 82% with QCG alone, supporting AI's potential to enhance urgent CAG decisionmaking for ED chest pain cases.

This pilot study evaluates an artificial intelligence (AI)-assisted electrocardiography (ECG) analysis system, QCG, to enhance urgent coronary angiography (CAG) decision-making for acute chest pain in the emergency department (ED). We retrospectively analyzed 300 ED cases, categorized as non-coronary chest pain (Group 1), acute coronary syndrome (ACS) without occlusive coronary artery disease (CAD) (Group 2), and ACS with occlusive CAD (Group 3). Six clinicians made urgent CAG decision using a conventional approach (clinical data and ECG) and a QCG-assisted approach (including QCG scores). The QCG-assisted approach improved correct CAG decisions in Group 2 (36.0% vs. 45.3%, P = 0.003) and Group 3 (85.3% vs. 90.0%, P = 0.017), with minimal impact in Group 1 (92.7% vs. 95.0%, P = 0.125). Diagnostic accuracy for ACS improved from 77% to 81% with QCG assistance and reached 82% with QCG alone, supporting AI's potential to enhance urgent CAG decisionmaking for ED chest pain cases.

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.

This pilot study evaluates an artificial intelligence (AI)-assisted electrocardiography (ECG) analysis system, QCG, to enhance urgent coronary angiography (CAG) decision-making for acute chest pain in the emergency department (ED). We retrospectively analyzed 300 ED cases, categorized as non-coronary chest pain (Group 1), acute coronary syndrome (ACS) without occlusive coronary artery disease (CAD) (Group 2), and ACS with occlusive CAD (Group 3). Six clinicians made urgent CAG decision using a conventional approach (clinical data and ECG) and a QCG-assisted approach (including QCG scores). The QCG-assisted approach improved correct CAG decisions in Group 2 (36.0% vs. 45.3%, P = 0.003) and Group 3 (85.3% vs. 90.0%, P = 0.017), with minimal impact in Group 1 (92.7% vs. 95.0%, P = 0.125). Diagnostic accuracy for ACS improved from 77% to 81% with QCG assistance and reached 82% with QCG alone, supporting AI's potential to enhance urgent CAG decisionmaking for ED chest pain cases.

Background/Aims: This study aimed to investigate co-occurrence and clinical characteristics of sexually transmitted infections (STIs) and pelvic inflammatory disease (PID) in women hospitalized for acute pyelonephritis (APN). Methods: This single-center retrospective study reviewed medical records of inpatients with APN from January 2019 to February 2023 and identified records of 142 patients who were referred to a gynecologist to evaluate gynecological diseases including STIs. Results: Of the 142 patients, 47 were tested positive for sexually transmitted pathogens in nucleic acid amplification testing, confirming the presence of STIs. In patients with APN, those with STIs were more likely to have lower abdominal pain or cervical motion tenderness (CMT) on pelvic examination and leukocytosis (> 14.5 × 109/L) than those without STIs. Of the 93 patients who underwent pelvic examination, 34 had CMT with one or more of additional criteria for the clinical diagnosis of PID, such as abnormal vaginal discharge and leukorrhea confirmed by microscopic examination, which could be clinically diagnosed as PID. Conclusions In sexually active women with APN, it is important to evaluate the possibility of STIs and PID, considering several risk factors such as lower abdominal pain, abnormal vaginal discharge, CMT, and leukocytosis.