Background/Aims: Adiponectin, a hormone primarily produced by adipocytes, typically shows an inverse relationship with body mass index (BMI). However, some studies have reported a positive correlation between the two. Thus, this study aimed to examine the relationship between adiponectin level and BMI in diabetic patients, focusing on the impact of past obesity on current adiponectin levels. Methods: We conducted an observational study analyzing data from 323 diabetic patients at Kyungpook National University Hospital. Based on past and current BMIs, participants were categorized into never-obese (nn, n = 106), previously obese (on, n = 43), and persistently obese (oo, n = 73) groups based on a BMI threshold of 25 kg/m2. Adiponectin level and BMI were key variables. Kaplan–Meier analysis assessed their impact on all-cause mortality up to August 2023, with survival differences based on adiponectin quartiles and follow-up starting from patient enrollment (2010–2015). Results: The analysis revealed a significant inverse correlation between adiponectin level and past maximum BMI. The on group exhibited approximately 10% lower adiponectin levels compared to the nn group. This association remained significant after adjusting for current BMI, age, and sex, highlighting the lasting influence of previous obesity on adiponectin levels. Furthermore, survival analysis indicated that patients in the lowest adiponectin quartile had reduced survival, with a statistically significant trend (p = 0.062). Conclusions Findings of this study suggest that lower adiponectin levels, potentially reflecting past obesity, are associated with decreased survival in diabetic patients, underscoring a critical role of adiponectin in long-term health outcomes.

Purpose: To evaluate the feasibility and utility of deep learning-based computer-aided diagnosis (DL-CAD) for the detection of pulmonary nodules on coronary artery calcium (CAC)-scoring computed tomography (CT). Materials and Methods: This retrospective study included 273 patients (aged 63.9±13.2 years; 129 men) who underwent CACscoring CT. A DL-CAD system based on thin-section images was used for pulmonary nodule detection, and two independent junior readers reviewed the standard CAC-scoring CT scans with and without referencing DL-CAD results. A reference standard was established through the consensus of two experienced radiologists. Sensitivity, positive predictive value, and F1-score were assessed on a per-nodule and per-patient basis. The patients’ medical records were monitored until November 2023. Results: A total of 269 nodules were identified in 129 patients. With DL-CAD assistance, the readers’ sensitivity significantly improved (65% vs. 80% for reader 1; 82% vs. 86% for reader 2; all p<0.001), without a notable increase in the number of false-positives per case (0.11 vs. 0.13, p=0.078 for reader 1; 0.11 vs. 0.11, p>0.999 for reader 2). Per-patient analysis also enhanced sensitivity with DL-CAD assistance (73% vs. 84%, p<0.001 for reader 1; 89% vs. 91%, p=0.250 for reader 2). During follow-up, lung cancer was diagnosed in four patients (1.5%). Among them, two had lesions detected on CAC-scoring CT, both of which were successfully identified by DL-CAD. Conclusion DL-CAD based on thin-section images can assist less experienced readers in detecting pulmonary nodules on CACscoring CT scans, improving detection sensitivity without significantly increasing false-positives.

Purpose: Early identification of patients at risk for acute respiratory failure (ARF) could help clinicians devise preventive strategies. Analyzing biosignals with artificial intelligence (AI) can uncover hidden information and variability within time series. We aimed to develop and validate AI models to predict ARF within 72 h after emergency department admission, primarily using highresolution biosignals collected within 4 h of arrival. Materials and Methods: Our AI model, built on convolutional recurrent neural networks, combines biosignal feature extraction and sequence modeling. The model was developed and internally validated with data from 5284 admissions [1085 (20.5%) positive for ARF], and externally validated using data from 144 admissions [7 (4.9%) positive for ARF] from another institution. We defined ARF as the application of advanced respiratory support devices. Results: Our AI model performed well in predicting ARF, achieving area under the receiver operating characteristic curve (AUROC) of 0.840 and 0.743 in internal and external validations, respectively. It outperformed the Modified Early Warning Score (MEWS) and XGBoost models built only with clinical variables. High predictive ability for mortality was observed, with AUROC up to 0.809. A 10% increase in AI prediction scores was associated with 1.44-fold and 1.42-fold increases in ARF risk and mortality risk, respectively, even after adjusting for MEWS and demographic variables. Conclusion Our AI model demonstrates high predictive accuracy and significant associations with clinical outcomes. Our AI model has the potential to promptly aid in triage decisions. Our study shows that using AI to analyze biosignals advances disease detection and prediction.

Background: s/Aims: Hepatocellular carcinoma (HCC) is the sixth most common cancer and second leading cause of cancer-related deaths in South Korea. This study evaluated the characteristics of Korean patients newly diagnosed with HCC in 2016-2018. Methods: Data from the Korean Primary Liver Cancer Registry (KPLCR), a representative database of patients newly diagnosed with HCC in South Korea, were analyzed. This study investigated 4,462 patients with HCC registered in the KPLCR in 2016-2018. Results: The median patient age was 63 years (interquartile range, 55-72). 79.7% of patients were male. Hepatitis B infection was the most common underlying liver disease (54.5%). The Barcelona Clinic Liver Cancer (BCLC) staging system classified patients as follows: stage 0 (14.9%), A (28.8%), B (7.5%), C (39.0%), and D (9.8%). The median overall survival was 3.72 years (95% confidence interval, 3.47-4.14), with 1-, 3-, and 5-year overall survival rates of 71.3%, 54.1%, and 44.3%, respectively. In 2016-2018, there was a significant shift toward BCLC stage 0-A and Child-Turcotte-Pugh liver function class A (P<0.05), although survival rates did not differ by diagnosis year. In the treatment group (n=4,389), the most common initial treatments were transarterial therapy (31.7%), surgical resection (24.9%), best supportive care (18.9%), and local ablation therapy (10.5%). Conclusions Between 2016 and 2018, HCC tended to be diagnosed at earlier stages, with better liver function in later years. However, since approximately half of the patients remained diagnosed at an advanced stage, more rigorous and optimized HCC screening strategies should be implemented.

Purpose: This study aimed to evaluate the impact of declining surgical residency program enrollment on patient care and outcomes in colorectal cancer surgeries. Methods: This retrospective observational study included 676 patients (410 males; median age: 69 years) who underwent colorectal cancer surgery at Pusan National University Hospital between January 2018 and June 2024. Patients were divided into Group A (before December 31, 2023; with residents) and Group B (after January 1, 2024; without residents). All surgeries were performed by a single attending surgeon. Results: Preoperative variables were comparable between groups. Group A had more emergency and open surgeries, and a higher proportion of advanced-stage cancers. Overall complication rates were similar, but Group B had a longer hospital stay (9.72 days vs. 11.95 days). Specific complications such as anastomotic leakage and surgical site infections differed significantly. The overall number of surgical procedures declined markedly in 2024 compared to 2018 (77.1% vs. 49.9%). Conclusion The absence of residents did not increase overall complication rates but was associated with longer hospital stays and shifts in clinical practice. Greater reliance on attending surgeons contributed to more defensive decision-making and conservative patient management. Addressing these issues requires systemic reforms, including multidisciplinary collaboration and legal protections to improve surgical care.

Background: Skipping breakfast is associated with an increased risk of chronic inflammatory diseases. This study aimed to examine the association between breakfast-eating habits and inflammation, using high-sensitivity C-reactive protein (hs-CRP) as a marker. Methods: A total of 4,000 Korean adult males with no history of myocardial infarction, angina, stroke, diabetes, rheumatoid arthritis, cancer, or current smoking were included. Data from the 2016–2018 Korea National Health and Nutrition Examination Survey were used for analysis. The frequency of breakfast consumption was assessed through a questionnaire item in the dietary survey section asking participants about their weekly breakfast consumption routines over the past year. Participants were categorized into two groups, namely “0–2 breakfasts per week” and “3–7 breakfasts per week”; hs-CRP concentrations were measured through blood tests. Results: Comparing between the “infrequent breakfast consumption (0–2 breakfasts per week)” and “frequent breakfast consumption (3–7 breakfasts per week)” groups, the mean hs-CRP was found to be significantly higher in the “infrequent breakfast consumption” group, even after adjusting for age, body mass index, physical activity, alcohol consumption, systolic blood pressure, blood pressure medication, fasting blood glucose, and triglycerides (mean hs-CRP: frequent breakfast consumption, 1.36±0.09 mg/L; infrequent breakfast consumption, 1.17±0.05 mg/L; P-value=0.036). Conclusion Less frequent breakfast consumption was associated with elevated hs-CRP levels. Further large-scale studies incorporating adjusted measures of daily eating patterns as well as food quality and quantity are required for a deeper understanding of the role of breakfast in the primary prevention of chronic inflammatory diseases.

Background: Patients with diabetes are known to be at high risk for end-stage kidney disease (ESKD), but the accurate annual risk data for new-onset ESKD is still limited. In South Korea, the prevalence and incidence of ESKD are increasing more rapidly compared to the global average. This study aimed to determine the incidence rate (IR) of ESKD by diabetes status from 2012 to 2022. Methods: Using data from the Korean National Health Insurance Service, we calculated the IR and hazard ratio (HR) for newonset ESKD in the general population. Individuals were categorized based on diabetes status into nondiabetes, impaired fasting glucose (IFG), diabetes duration <5 and ≥5 years. Results: Among the participants, 67.6% were nondiabetic, 22.3% had IFG, and 10% had diabetes. In Korea, the IRs of ESKD were 139 per million population (pmp) for nondiabetes, 188 pmp for IFG, 632 pmp for diabetes <5 years, and 3,403 pmp for diabetes ≥5 years. An advanced estimated glomerular filtration rate (eGFR) category was the strongest risk factor for ESKD development. However, even in patients with normal renal function, those with long-standing diabetes had a 14-fold higher risk of ESKD compared to nondiabetic individuals. The risk of ESKD associated with diabetes increased exponentially with declining renal function. Notably, IFG showed an increasing tendency for ESKD in younger patients (<65 years) with early-stage chronic kidney disease (CKD; eGFR ≥60 mL/min/1.73 m²). Conclusion Longer diabetes duration amplifies ESKD risk, particularly as renal function declines. Even in patients with normal renal function, long-standing diabetes significantly increases ESKD risk, while IFG is associated with elevated risk only in younger individuals with early-stage CKD.

Background: The positive relationship between triiodothyronine (T3) and steatotic liver disease (SLD) demonstrated only in crosssectional study. We aimed to evaluated whether total T3 (TT3) is associated with the development/resolution of SLD in longitudinal design. Methods: This retrospective, longitudinal, population-based cohort study included 1,665 South Korean euthyroid adults with ≥4 thyroid function test. We explored the impact of mean TT3 during follow-up on development/resolution of either SLD (diagnosed by ultrasound) or modified metabolic dysfunction-associated steatotic liver disease (MASLD) using Cox proportional hazards regression models. Results: During about median 5 years follow-up, 807/1,216 (66.3%) participants among participants without SLD at baseline developed SLD, and 253/318 (79.5%) participants among participants with SLD at baseline SLD resolved fatty liver. Mean TT3 rather than thyroid stimulating hormone or mean free thyroxine was significantly related with development (adjusted hazard ratio [HR], 1.01; 95% confidence interval [CI], 1.00 to 1.02; P=0.002) and resolution (adjusted HR, 0.97; 95% CI, 0.96 to 0.99; P=0.005) of SLD. Compared with low mean TT3 group, high mean TT3 group was positively associated with development of SLD (adjusted HR, 1.20; 95% CI, 1.05 to 1.38; P=0.008) and inversely associated with resolution of SLD (adjusted HR, 0.66; 95% CI, 0.51 to 0.85; P=0.001). The statistical significance remained for development (adjusted HR, 1.29; 95% CI, 1.10 to 1.51; P=0.001) and resolution (adjusted HR, 0.71; 95% CI, 0.54 to 0.94; P=0.018) of modified MASLD. Conclusion In Korean euthyroid adults, TT3 level was associated with development and resolution of either SLD or modified MASLD.

Background/Aims: This study aimed to evaluate the performance of the Model for End-Stage Liver Disease (MELD) 3.0 for predicting mortality and liver-related complications compared with the Child-Pugh classification, albumin-bilirubin (ALBI) grade, the MELD, and the MELD sodium (MELDNa) score. Methods: We evaluated a multicenter retrospective cohort of incorporated patients with cirrhosis between 2013 and 2019. We conducted comparisons of the area under the receiver operating characteristic curve (AUROC) of the MELD3.0 and other models for predicting 3-month mortality. Additionally, we assessed the risk of cirrhosis-related complications according to the MELD3.0 score. Results: A total of 3,314 patients were included. The mean age was 55.9±11.3 years, and 70.2% of the patients were male. Within the initial 3 months, 220 patients (6.6%) died, and the MELD3.0had the best predictive performance among the tested models, with an AUROC of 0.851, outperforming the Child-Pugh classification, ALBI grade, MELD, and MELDNa. A high MELD3.0score was associated with an increased risk of mortality. Compared with that of the group with a MELD3.0 score <10 points, the adjusted hazard ratio of the group with a score of 10–20 pointswas 2.176, and that for the group with a score of ≥20 points was 4.892. Each 1-point increase inthe MELD3.0 score increased the risk of cirrhosis-related complications by 1.033-fold. The risk of hepatorenal syndrome showed the highest increase, with an adjusted hazard ratio of 1.149, followed by hepatic encephalopathy and ascites. Conclusions The MELD3.0 demonstrated robust prognostic performance in predicting mortality in patients with cirrhosis. Moreover, the MELD3.0 score was linked to cirrhosis-related complications, particularly those involving kidney function, such as hepatorenal syndrome and ascites.

Purpose: It is well known that the majority of the extranodal marginal zone lymphomas of mucosa-associated lymphoid tissues (MALT lymphomas) are associated with microbiota, e.g., gastric MALT lymphoma with Helicobacter pylori. In general, they are very sensitive to low-dose radiotherapy and chemotherapeutic agents. The microbiota profile is not clearly elucidated in bronchus-associated lymphoid tissue (BALT) lymphoma, a rare type of MALT lymphoma in the lung. Thus, this study aimed to clarify the intratumor microbiome in BALT lymphoma using the third-generation next-generation sequencing (NGS) method. Materials and Methods: DNAs were extracted from 12 formalin-fixed paraffin-embedded (FFPE) tumor tissues obtained from BALT lymphoma patients diagnosed between 1990 and 2016. 16S rRNA gene was amplified by polymerase chain reaction. Amplicons were sequenced using a Nanopore platform. Next-generation sequencing analysis was performed to assess microbial profiles. For comparison, FFPE specimens from nine non-cancerous lung tissues were also analyzed. Results: Specific bacterial families including Burkholderiaceae, Bacillaceae, and Microbacteriaceae were associated with BALT lymphoma by a linear discriminant analysis effect size approach. Although the number of specimens was limited, BALT lymphomas exhibited significantly higher microbial abundance and diversity with distinct microbial composition patterns and correlation networks than non-cancerous lung tissues. Conclusion This study provides the first insight into intratumor microbiome in BALT lymphoma using the third-generation NGS method. A distinct microbial composition suggests the presence of a unique tumor microenvironment of BALT lymphoma.