Objective: To classify life stages for companion dogs and cats by identifying clusters in age-specific disease proportions derived from medical records, providing a data-driven foundation for health examination programs. Methods: We collected 505,667 medical records from 82 veterinary facilities in South Korea between 2020 and 2023. Diagnoses were standardized using GPT-4o and S-BioBERT. Following preprocessing, data from 27 facilities yielded 222,706 canine and 39,910 feline records for the final analysis. Principal component analysis and K-means clustering (K = 4) were applied to age-specific disease proportions to identify life stages.The 10 most highest-proportion diagnoses diseases were determined for each cluster. Results: Canine life stages were classified as ≤ 1 year, 2–5 years, 6–10 years, and 11–15+ years.Feline life stages were 1–2 years, 3–8 years, 9–12 years, and 13–15+ years. In dogs, developmental diseases were common in the youngest age group, while chronic diseases were more prevalent in older groups. In cats, oral and urinary diseases were high-ranking, conjunctivitis was most common in the early stage, and chronic diseases increased with age. Conclusions and Relevance: Age-specific diagnosis patterns support four practical life stages for dogs and cats in South Korea. These boundaries can inform evidence-based preventive examination schedules, animal health policy, and pet insurance product design.

Background/Aims: Portal vein thrombosis (PVT) frequently occurs in patients with inflammatory bowel disease (IBD), particularly when influenced by factors such as abdominal infections, IBD flare-ups, or surgical procedures. The implications of PVT range from immediate issues such as intestinal ischemia to long-term concerns including portal hypertension and its complications. However, there is a notable gap in comprehensive studies on PVT in IBD, especially with the increasing incidence of IBD in Asia. This research aimed to evaluate the clinical features and outcomes of PVT in patients with IBD at a leading hospital in South Korea. Methods: This retrospective analysis reviewed adult patients diagnosed with both IBD and PVT from 1989 to 2021 at a renowned South Korean medical center. The study focused on patient characteristics, specifics of PVT, administered treatments, and outcomes, all confirmed through enhanced CT scans. Results: A total of 78 patients met the study’s criteria. Notably, only 20.5% (16/78) were treated with oral anticoagulants; however, a vast majority (96.2%; 75/78) achieved complete radiographic resolution (CRR). When comparing patients receiving anticoagulants to those who did not, a significant preference for anticoagulant use was observed in cases where the main portal vein was affected, as opposed to just the left or right veins (p = 0.006). However, multivariable analysis indicated that neither anticoagulant use nor previous surgeries significantly impacted CRR. Conclusions Patients with IBD and PVT generally had favorable outcomes, regardless of anticoagulant use.

Background/Aims: The incidence of steatotic liver disease (SLD) is increasing across all age groups as the incidence of obesity increases worldwide. The existing noninvasive prediction models for SLD require laboratory tests or imaging and perform poorly in the early diagnosis of infrequently screened populations such as young adults and individuals with healthcare disparities. We developed a machine learning-based point-of-care prediction model for SLD that is readily available to the broader population with the aim of facilitating early detection and timely intervention and ultimately reducing the burden of SLD. Methods: We retrospectively analyzed the clinical data of 28,506 adults who had routine health check-ups in South Korea from January to December 2022. A total of 229,162 individuals were included in the external validation study. Data were analyzed and predictions were made using a logistic regression model with machine learning algorithms. Results: A total of 20,094 individuals were categorized into SLD and non-SLD groups on the basis of the presence of fatty liver disease. We developed three prediction models: SLD model 1, which included age and body mass index (BMI); SLD model 2, which included BMI and body fat per muscle mass; and SLD model 3, which included BMI and visceral fat per muscle mass. In the derivation cohort, the area under the receiver operating characteristic curve (AUROC) was 0.817 for model 1, 0.821 for model 2, and 0.820 for model 3. In the internal validation cohort, 86.9% of individuals were correctly classified by the SLD models. The external validation study revealed an AUROC above 0.84 for all the models. Conclusions As our three novel SLD prediction models are cost-effective, noninvasive, and accessible, they could serve as validated clinical tools for mass screening of SLD.

Background/Aims: The study investigated the incidence, risk factors, and clinical outcomes of chronic antibiotic-refractory pouchitis (CARP) in Korean patients with ulcerative colitis (UC). Methods: This single-center retrospective study included patients with UC who underwent total proctocolectomy with ileal pouch-anal anastomosis at the Asan Medical Center in Korea between January 1987 and December 2022. The primary outcomes were endoscopic remission and pouch failure. The Cox’s proportional hazard model was used to identify the risk factors for CARP. Results: The clinical data of 232 patients were analyzed. The most common cause of surgery was steroid refractoriness (50.9%), followed by dysplasia/colorectal cancer (26.7%). Among 74 patients (31.9%) with chronic pouchitis (CP), 31 (13.4%) had CARP, and 43 (18.5%) had chronic antibiotic-dependent pouchitis (CADP). The most frequent endoscopic phenotype was focal inflammation of the pouch (CP, 47.3%; CARP, 35.5%; CADP, 55.8%). Patients with CARP were less likely to use concomitant probiotics than patients with CADP (29.0% vs 72.1%, p<0.01). The endoscopic remission rate of CP, CARP, and CADP was 14.9%, 9.7%, and 18.6%, respectively.The pouch failure rate associated with CP, CARP, and CADP was 13.5%, 16.1%, and 11.6%, respectively. Current smoking status (adjusted hazard ratio [aHR], 2.96; 95% confidence interval [CI], 1.27 to 6.90; p=0.01) and previous use of biologics/small molecules (aHR, 2.40; 95% CI, 1.05 to 5.53; p=0.04) were significantly associated with CARP development. Conclusions UC patients who were current smokers and previously used biologics/small molecules had a higher risk of developing CARP. Concomitant use of probiotics was less likely to be associated with CARP development.

Background/Aims: The incidence of steatotic liver disease (SLD) is increasing across all age groups as the incidence of obesity increases worldwide. The existing noninvasive prediction models for SLD require laboratory tests or imaging and perform poorly in the early diagnosis of infrequently screened populations such as young adults and individuals with healthcare disparities. We developed a machine learning-based point-of-care prediction model for SLD that is readily available to the broader population with the aim of facilitating early detection and timely intervention and ultimately reducing the burden of SLD. Methods: We retrospectively analyzed the clinical data of 28,506 adults who had routine health check-ups in South Korea from January to December 2022. A total of 229,162 individuals were included in the external validation study. Data were analyzed and predictions were made using a logistic regression model with machine learning algorithms. Results: A total of 20,094 individuals were categorized into SLD and non-SLD groups on the basis of the presence of fatty liver disease. We developed three prediction models: SLD model 1, which included age and body mass index (BMI); SLD model 2, which included BMI and body fat per muscle mass; and SLD model 3, which included BMI and visceral fat per muscle mass. In the derivation cohort, the area under the receiver operating characteristic curve (AUROC) was 0.817 for model 1, 0.821 for model 2, and 0.820 for model 3. In the internal validation cohort, 86.9% of individuals were correctly classified by the SLD models. The external validation study revealed an AUROC above 0.84 for all the models. Conclusions As our three novel SLD prediction models are cost-effective, noninvasive, and accessible, they could serve as validated clinical tools for mass screening of SLD.

Background/Aims: The study investigated the incidence, risk factors, and clinical outcomes of chronic antibiotic-refractory pouchitis (CARP) in Korean patients with ulcerative colitis (UC). Methods: This single-center retrospective study included patients with UC who underwent total proctocolectomy with ileal pouch-anal anastomosis at the Asan Medical Center in Korea between January 1987 and December 2022. The primary outcomes were endoscopic remission and pouch failure. The Cox’s proportional hazard model was used to identify the risk factors for CARP. Results: The clinical data of 232 patients were analyzed. The most common cause of surgery was steroid refractoriness (50.9%), followed by dysplasia/colorectal cancer (26.7%). Among 74 patients (31.9%) with chronic pouchitis (CP), 31 (13.4%) had CARP, and 43 (18.5%) had chronic antibiotic-dependent pouchitis (CADP). The most frequent endoscopic phenotype was focal inflammation of the pouch (CP, 47.3%; CARP, 35.5%; CADP, 55.8%). Patients with CARP were less likely to use concomitant probiotics than patients with CADP (29.0% vs 72.1%, p<0.01). The endoscopic remission rate of CP, CARP, and CADP was 14.9%, 9.7%, and 18.6%, respectively.The pouch failure rate associated with CP, CARP, and CADP was 13.5%, 16.1%, and 11.6%, respectively. Current smoking status (adjusted hazard ratio [aHR], 2.96; 95% confidence interval [CI], 1.27 to 6.90; p=0.01) and previous use of biologics/small molecules (aHR, 2.40; 95% CI, 1.05 to 5.53; p=0.04) were significantly associated with CARP development. Conclusions UC patients who were current smokers and previously used biologics/small molecules had a higher risk of developing CARP. Concomitant use of probiotics was less likely to be associated with CARP development.

Background/Aims: Portal vein thrombosis (PVT) frequently occurs in patients with inflammatory bowel disease (IBD), particularly when influenced by factors such as abdominal infections, IBD flare-ups, or surgical procedures. The implications of PVT range from immediate issues such as intestinal ischemia to long-term concerns including portal hypertension and its complications. However, there is a notable gap in comprehensive studies on PVT in IBD, especially with the increasing incidence of IBD in Asia. This research aimed to evaluate the clinical features and outcomes of PVT in patients with IBD at a leading hospital in South Korea. Methods: This retrospective analysis reviewed adult patients diagnosed with both IBD and PVT from 1989 to 2021 at a renowned South Korean medical center. The study focused on patient characteristics, specifics of PVT, administered treatments, and outcomes, all confirmed through enhanced CT scans. Results: A total of 78 patients met the study’s criteria. Notably, only 20.5% (16/78) were treated with oral anticoagulants; however, a vast majority (96.2%; 75/78) achieved complete radiographic resolution (CRR). When comparing patients receiving anticoagulants to those who did not, a significant preference for anticoagulant use was observed in cases where the main portal vein was affected, as opposed to just the left or right veins (p = 0.006). However, multivariable analysis indicated that neither anticoagulant use nor previous surgeries significantly impacted CRR. Conclusions Patients with IBD and PVT generally had favorable outcomes, regardless of anticoagulant use.

Background/Aims: The incidence of steatotic liver disease (SLD) is increasing across all age groups as the incidence of obesity increases worldwide. The existing noninvasive prediction models for SLD require laboratory tests or imaging and perform poorly in the early diagnosis of infrequently screened populations such as young adults and individuals with healthcare disparities. We developed a machine learning-based point-of-care prediction model for SLD that is readily available to the broader population with the aim of facilitating early detection and timely intervention and ultimately reducing the burden of SLD. Methods: We retrospectively analyzed the clinical data of 28,506 adults who had routine health check-ups in South Korea from January to December 2022. A total of 229,162 individuals were included in the external validation study. Data were analyzed and predictions were made using a logistic regression model with machine learning algorithms. Results: A total of 20,094 individuals were categorized into SLD and non-SLD groups on the basis of the presence of fatty liver disease. We developed three prediction models: SLD model 1, which included age and body mass index (BMI); SLD model 2, which included BMI and body fat per muscle mass; and SLD model 3, which included BMI and visceral fat per muscle mass. In the derivation cohort, the area under the receiver operating characteristic curve (AUROC) was 0.817 for model 1, 0.821 for model 2, and 0.820 for model 3. In the internal validation cohort, 86.9% of individuals were correctly classified by the SLD models. The external validation study revealed an AUROC above 0.84 for all the models. Conclusions As our three novel SLD prediction models are cost-effective, noninvasive, and accessible, they could serve as validated clinical tools for mass screening of SLD.

Background/Aims: The study investigated the incidence, risk factors, and clinical outcomes of chronic antibiotic-refractory pouchitis (CARP) in Korean patients with ulcerative colitis (UC). Methods: This single-center retrospective study included patients with UC who underwent total proctocolectomy with ileal pouch-anal anastomosis at the Asan Medical Center in Korea between January 1987 and December 2022. The primary outcomes were endoscopic remission and pouch failure. The Cox’s proportional hazard model was used to identify the risk factors for CARP. Results: The clinical data of 232 patients were analyzed. The most common cause of surgery was steroid refractoriness (50.9%), followed by dysplasia/colorectal cancer (26.7%). Among 74 patients (31.9%) with chronic pouchitis (CP), 31 (13.4%) had CARP, and 43 (18.5%) had chronic antibiotic-dependent pouchitis (CADP). The most frequent endoscopic phenotype was focal inflammation of the pouch (CP, 47.3%; CARP, 35.5%; CADP, 55.8%). Patients with CARP were less likely to use concomitant probiotics than patients with CADP (29.0% vs 72.1%, p<0.01). The endoscopic remission rate of CP, CARP, and CADP was 14.9%, 9.7%, and 18.6%, respectively.The pouch failure rate associated with CP, CARP, and CADP was 13.5%, 16.1%, and 11.6%, respectively. Current smoking status (adjusted hazard ratio [aHR], 2.96; 95% confidence interval [CI], 1.27 to 6.90; p=0.01) and previous use of biologics/small molecules (aHR, 2.40; 95% CI, 1.05 to 5.53; p=0.04) were significantly associated with CARP development. Conclusions UC patients who were current smokers and previously used biologics/small molecules had a higher risk of developing CARP. Concomitant use of probiotics was less likely to be associated with CARP development.

Background/Aims: The incidence of steatotic liver disease (SLD) is increasing across all age groups as the incidence of obesity increases worldwide. The existing noninvasive prediction models for SLD require laboratory tests or imaging and perform poorly in the early diagnosis of infrequently screened populations such as young adults and individuals with healthcare disparities. We developed a machine learning-based point-of-care prediction model for SLD that is readily available to the broader population with the aim of facilitating early detection and timely intervention and ultimately reducing the burden of SLD. Methods: We retrospectively analyzed the clinical data of 28,506 adults who had routine health check-ups in South Korea from January to December 2022. A total of 229,162 individuals were included in the external validation study. Data were analyzed and predictions were made using a logistic regression model with machine learning algorithms. Results: A total of 20,094 individuals were categorized into SLD and non-SLD groups on the basis of the presence of fatty liver disease. We developed three prediction models: SLD model 1, which included age and body mass index (BMI); SLD model 2, which included BMI and body fat per muscle mass; and SLD model 3, which included BMI and visceral fat per muscle mass. In the derivation cohort, the area under the receiver operating characteristic curve (AUROC) was 0.817 for model 1, 0.821 for model 2, and 0.820 for model 3. In the internal validation cohort, 86.9% of individuals were correctly classified by the SLD models. The external validation study revealed an AUROC above 0.84 for all the models. Conclusions As our three novel SLD prediction models are cost-effective, noninvasive, and accessible, they could serve as validated clinical tools for mass screening of SLD.