Background/Aims: This study aims to investigate the effect of a fermented rice drink with Lactiplantibacillus plantarum JSA22 on symptoms, blood tests, microbiomes, and fecal metabolites in patients with irritable bowel syndrome (IBS) who were overweight. Methods: Sixty overweight (body mass index ≥ 23 kg/m2 ) patients aged between 20 and 65 with IBS were enrolled. Patients were divided into 2 groups and administered either a fermented rice drink or an nonfermented rice drink for a month. The symptom questionnaire, blood samples, and stool samples for microbiome and metabolite were collected before and after the month of rice drink administration.The primary efficacy variable was the subject’s global assessment of IBS symptoms. Results: In both groups, global IBS symptoms, including abdominal pain, bowel habit, urgency, and abdominal distension, improved significantly (P < 0.01). The abdominal bloating was more significantly improved in the fermented rice drink group than in the nonfermented rice drink group (P < 0.05). Significant changes were not observed in metabolic syndrome-related blood tests or fecal metabolites in either group. However, microbiome analysis showed significant differences in genus levels before and after consuming fermented rice drink, such as in Blautia in stool (P = 0.020) and Prevotella (P = 0.017) and Oribacterium (P = 0.018) in saliva. Conclusions The fermented rice drink with L. plantarum JSA22 showed a beneficial effect in reducing abdominal distension in IBS patients. Bacteria that reduce visceral fat accumulation increased in the stool and saliva of patients who consumed fermented rice drinks.

OBJECTIVES: This study investigated the associations between several obesity-related anthropometric indices and mortality in middle-aged and elderly populations to compare the indices’ predictive ability with that of the body mass index (BMI). METHODS: We analyzed data on 12 indices calculated from 19,805 community-based cohort participants (average age, 63.27 years; median follow-up, 13.49 years). Each index was calculated using directly measured values of height, weight, waist circumference (WC), and hip circumference (HC). We calculated hazard ratios (HRs) and 95% confidence intervals (CIs) for each index using Cox regression and evaluated mortality prediction with the Harrell concordance index (c-index). RESULTS: Adding anthropometric indices to the basic mortality model (c-index, 0.7723; 95% CI, 0.7647 to 0.7799) significantly increased the predictive power of BMI (c-index, 0.7735; 95% CI, 0.7659 to 0.7811), a body shape index (ABSI; c-index, 0.7735; 95% CI, 0.7659 to 0.7810), weight-adjusted waist index (WWI; c-index, 0.7731; 95% CI, 0.7656 to 0.7807), and waist to hip index (WHI; c-index, 0.7733; 95% CI, 0.7657 to 0.7809). The differences between the BMI model and the other 3 models were not statistically significant. CONCLUSIONS In predicting all-cause mortality, the ABSI, WWI, and WHI models based on WC or HC had stronger predictive power than conventional risk factors but were not significantly different from the BMI model.

Rare endocrine diseases are complex conditions that require lifelong specialized care due to their chronic nature and associated long-term complications. In Korea, a lack of nationwide data on clinical practice and outcomes has limited progress in patient care. Therefore, the Multicenter Networks for Ideal Outcomes of Pediatric Rare Endocrine and Metabolic Disease (OUTSPREAD) study was initiated. This study involves 30 centers across Korea. The study aims to improve the long-term prognosis of Korean patients with rare endocrine diseases by collecting comprehensive clinical data, biospecimens, and patient-reported outcomes to identify complications and unmet needs in patient care. Patients with childhood-onset pituitary, adrenal, or gonadal disorders, such as craniopharyngioma, congenital adrenal hyperplasia (CAH), and Turner syndrome were prioritized. The planned enrollment is 1,300 patients during the first study phase (2022–2024). Clinical, biochemical, and imaging data from diagnosis, treatment, and follow-up during 1980–2023 were retrospectively reviewed. For patients who agreed to participate in the prospective cohort, clinical data and biospecimens will be prospectively collected to discover ideal biomarkers that predict the effectiveness of disease control measures and prognosis. Patient-reported outcomes, including quality of life and depression scales, will be evaluated to assess psychosocial outcomes. Additionally, a substudy on CAH patients will develop a steroid hormone profiling method using liquid chromatography-tandem mass spectrometry to improve diagnosis and monitoring of treatment outcomes. This study will address unmet clinical needs by discovering ideal biomarkers, introducing evidence-based treatment guidelines, and ultimately improving long-term outcomes in the areas of rare endocrine and metabolic diseases.

OBJECTIVES: This study investigated the associations between several obesity-related anthropometric indices and mortality in middle-aged and elderly populations to compare the indices’ predictive ability with that of the body mass index (BMI). METHODS: We analyzed data on 12 indices calculated from 19,805 community-based cohort participants (average age, 63.27 years; median follow-up, 13.49 years). Each index was calculated using directly measured values of height, weight, waist circumference (WC), and hip circumference (HC). We calculated hazard ratios (HRs) and 95% confidence intervals (CIs) for each index using Cox regression and evaluated mortality prediction with the Harrell concordance index (c-index). RESULTS: Adding anthropometric indices to the basic mortality model (c-index, 0.7723; 95% CI, 0.7647 to 0.7799) significantly increased the predictive power of BMI (c-index, 0.7735; 95% CI, 0.7659 to 0.7811), a body shape index (ABSI; c-index, 0.7735; 95% CI, 0.7659 to 0.7810), weight-adjusted waist index (WWI; c-index, 0.7731; 95% CI, 0.7656 to 0.7807), and waist to hip index (WHI; c-index, 0.7733; 95% CI, 0.7657 to 0.7809). The differences between the BMI model and the other 3 models were not statistically significant. CONCLUSIONS In predicting all-cause mortality, the ABSI, WWI, and WHI models based on WC or HC had stronger predictive power than conventional risk factors but were not significantly different from the BMI model.

Rare endocrine diseases are complex conditions that require lifelong specialized care due to their chronic nature and associated long-term complications. In Korea, a lack of nationwide data on clinical practice and outcomes has limited progress in patient care. Therefore, the Multicenter Networks for Ideal Outcomes of Pediatric Rare Endocrine and Metabolic Disease (OUTSPREAD) study was initiated. This study involves 30 centers across Korea. The study aims to improve the long-term prognosis of Korean patients with rare endocrine diseases by collecting comprehensive clinical data, biospecimens, and patient-reported outcomes to identify complications and unmet needs in patient care. Patients with childhood-onset pituitary, adrenal, or gonadal disorders, such as craniopharyngioma, congenital adrenal hyperplasia (CAH), and Turner syndrome were prioritized. The planned enrollment is 1,300 patients during the first study phase (2022–2024). Clinical, biochemical, and imaging data from diagnosis, treatment, and follow-up during 1980–2023 were retrospectively reviewed. For patients who agreed to participate in the prospective cohort, clinical data and biospecimens will be prospectively collected to discover ideal biomarkers that predict the effectiveness of disease control measures and prognosis. Patient-reported outcomes, including quality of life and depression scales, will be evaluated to assess psychosocial outcomes. Additionally, a substudy on CAH patients will develop a steroid hormone profiling method using liquid chromatography-tandem mass spectrometry to improve diagnosis and monitoring of treatment outcomes. This study will address unmet clinical needs by discovering ideal biomarkers, introducing evidence-based treatment guidelines, and ultimately improving long-term outcomes in the areas of rare endocrine and metabolic diseases.

OBJECTIVES: This study investigated the associations between several obesity-related anthropometric indices and mortality in middle-aged and elderly populations to compare the indices’ predictive ability with that of the body mass index (BMI). METHODS: We analyzed data on 12 indices calculated from 19,805 community-based cohort participants (average age, 63.27 years; median follow-up, 13.49 years). Each index was calculated using directly measured values of height, weight, waist circumference (WC), and hip circumference (HC). We calculated hazard ratios (HRs) and 95% confidence intervals (CIs) for each index using Cox regression and evaluated mortality prediction with the Harrell concordance index (c-index). RESULTS: Adding anthropometric indices to the basic mortality model (c-index, 0.7723; 95% CI, 0.7647 to 0.7799) significantly increased the predictive power of BMI (c-index, 0.7735; 95% CI, 0.7659 to 0.7811), a body shape index (ABSI; c-index, 0.7735; 95% CI, 0.7659 to 0.7810), weight-adjusted waist index (WWI; c-index, 0.7731; 95% CI, 0.7656 to 0.7807), and waist to hip index (WHI; c-index, 0.7733; 95% CI, 0.7657 to 0.7809). The differences between the BMI model and the other 3 models were not statistically significant. CONCLUSIONS In predicting all-cause mortality, the ABSI, WWI, and WHI models based on WC or HC had stronger predictive power than conventional risk factors but were not significantly different from the BMI model.

Rare endocrine diseases are complex conditions that require lifelong specialized care due to their chronic nature and associated long-term complications. In Korea, a lack of nationwide data on clinical practice and outcomes has limited progress in patient care. Therefore, the Multicenter Networks for Ideal Outcomes of Pediatric Rare Endocrine and Metabolic Disease (OUTSPREAD) study was initiated. This study involves 30 centers across Korea. The study aims to improve the long-term prognosis of Korean patients with rare endocrine diseases by collecting comprehensive clinical data, biospecimens, and patient-reported outcomes to identify complications and unmet needs in patient care. Patients with childhood-onset pituitary, adrenal, or gonadal disorders, such as craniopharyngioma, congenital adrenal hyperplasia (CAH), and Turner syndrome were prioritized. The planned enrollment is 1,300 patients during the first study phase (2022–2024). Clinical, biochemical, and imaging data from diagnosis, treatment, and follow-up during 1980–2023 were retrospectively reviewed. For patients who agreed to participate in the prospective cohort, clinical data and biospecimens will be prospectively collected to discover ideal biomarkers that predict the effectiveness of disease control measures and prognosis. Patient-reported outcomes, including quality of life and depression scales, will be evaluated to assess psychosocial outcomes. Additionally, a substudy on CAH patients will develop a steroid hormone profiling method using liquid chromatography-tandem mass spectrometry to improve diagnosis and monitoring of treatment outcomes. This study will address unmet clinical needs by discovering ideal biomarkers, introducing evidence-based treatment guidelines, and ultimately improving long-term outcomes in the areas of rare endocrine and metabolic diseases.

OBJECTIVES: This study investigated the associations between several obesity-related anthropometric indices and mortality in middle-aged and elderly populations to compare the indices’ predictive ability with that of the body mass index (BMI). METHODS: We analyzed data on 12 indices calculated from 19,805 community-based cohort participants (average age, 63.27 years; median follow-up, 13.49 years). Each index was calculated using directly measured values of height, weight, waist circumference (WC), and hip circumference (HC). We calculated hazard ratios (HRs) and 95% confidence intervals (CIs) for each index using Cox regression and evaluated mortality prediction with the Harrell concordance index (c-index). RESULTS: Adding anthropometric indices to the basic mortality model (c-index, 0.7723; 95% CI, 0.7647 to 0.7799) significantly increased the predictive power of BMI (c-index, 0.7735; 95% CI, 0.7659 to 0.7811), a body shape index (ABSI; c-index, 0.7735; 95% CI, 0.7659 to 0.7810), weight-adjusted waist index (WWI; c-index, 0.7731; 95% CI, 0.7656 to 0.7807), and waist to hip index (WHI; c-index, 0.7733; 95% CI, 0.7657 to 0.7809). The differences between the BMI model and the other 3 models were not statistically significant. CONCLUSIONS In predicting all-cause mortality, the ABSI, WWI, and WHI models based on WC or HC had stronger predictive power than conventional risk factors but were not significantly different from the BMI model.

Objective: To measure inter-reader agreement and identify associated factors in interpreting complete response (CR) on magnetic resonance imaging (MRI) following chemoradiotherapy (CRT) for rectal cancer. Materials and Methods: This retrospective study involved 10 readers from seven hospitals with experience of 80–10210 cases, and 149 patients who underwent surgery after CRT for rectal cancer. Using MRI-based tumor regression grading (mrTRG) and methods employed in daily practice, the readers independently assessed mrTRG, CR on T2-weighted images (T2WI) denoted as mrCR T2W, and CR on all images including diffusion-weighted images (DWI) denoted as mrCRoverall. The readers described their interpretation patterns and how they utilized DWI. Inter-reader agreement was measured using multi-rater kappa, and associated factors were analyzed using multivariable regression. Correlation between sensitivity and specificity of each reader was analyzed using Spearman coefficient. Results: The mrCR T2W and mrCRoverall rates varied widely among the readers, ranging 18.8%–40.3% and 18.1%–34.9%, respectively. Nine readers used DWI as a supplement sequence, which modified interpretations on T2WI in 2.7% of cases (36/1341 [149 patients x 9 readers]) and mostly (33/36) changed mrCR T2W to non-mrCRoverall. The kappa values for mrTRG, mrCR T2W, and mrCRoverall were 0.56 (95% confidence interval: 0.49, 0.62), 0.55 (0.52, 0.57), and 0.54 (0.51, 0.57), respectively.No use of rectal gel, larger initial tumor size, and higher initial cT stage exhibited significant association with a higher interreader agreement for assessing mrCRoverall (P ≤ 0.042). Strong negative correlations were observed between the sensitivity and specificity of individual readers (coefficient, -0.718 to -0.963; P ≤ 0.019). Conclusion Inter-reader agreement was moderate for assessing CR on post-CRT MRI. Readers’ varying standards on MRI interpretation (i.e., threshold effect), along with the use of rectal gel, initial tumor size, and initial cT stage, were significant factors associated with inter-reader agreement.

Background and Objectives: The association between bilirubin and atrial fibrillation (AF) has been evaluated previously in observational studies but with contradictory results. This study evaluated the causal association between serum bilirubin level and AF using Mendelian randomization (MR) analysis. Methods: This cross-sectional study includes 8,977 participants from the Dong-gu Study.In the observational analysis, multivariate logistic regression was performed to evaluate the association between bilirubin and prevalent AF. To evaluate the causal association between bilirubin and AF, MR analysis was conducted by using the UGT1A1 rs11891311 and rs4148323 polymorphisms as instrumental variables. Results: Elevated serum bilirubin levels were associated with an increased risk for AF in observational analysis (total bilirubin: odds ratio [OR], 1.31; 95% confidence interval [95% CI], 1.15–1.48 per 1 standard deviation [SD]; direct bilirubin: OR, 1.31; 95% CI, 1.18–1.46 per 1 SD), whereas the genetically predicted serum bilirubin levels in MR analysis did not show this association (total bilirubin: OR, 1.02; 95% CI, 0.67–1.53 per 1 SD; direct bilirubin: OR, 1.03; 95% CI, 0.61–1.73 per 1 SD). Conclusions Genetically predicted bilirubin levels were not associated with prevalent AF.Thus, the observational association between serum bilirubin levels and AF may be noncausal and affected by reverse causality or unmeasured confounding.