Background: Malaria elimination strategies in the Republic of Korea (ROK) have decreased malaria incidence but face challenges due to delayed case detection and response. To improve this, machine learning models for predicting malaria, focusing on high-risk areas, have been developed. Methods: The study targeted the northern region of ROK, near the demilitarized zone, using a 1-km grid to identify areas for prediction. Grid cells without residential buildings were excluded, leaving 8,425 cells. The prediction was based on whether at least one malaria case was reported in each grid cell per month, using spatial data of patient locations. Four algorithms were used: gradient boosted (GBM), generalized linear (GLM), extreme gradient boosted (XGB), and ensemble models, incorporating environmental, sociodemographic, and meteorological data as predictors. The models were trained with data from May to October (2019–2021) and tested with data from May to October 2022. Model performance was evaluated using the area under the receiver operating characteristic curve (AUROC). Results: The AUROC of the prediction models performed excellently (GBM = 0.9243, GLM = 0.9060, XGB = 0.9180, and ensemble model = 0.9301). Previous malaria risk, population size, and meteorological factors influenced the model most in GBM and XGB. Conclusion Machine-learning models with properly preprocessed malaria case data can provide reliable predictions. Additional predictors, such as mosquito density, should be included in future studies to improve the performance of models.

Myxomatous mitral valve disease (MMVD) in dogs is a heart disease that is characterized by histopathologic changes in cardiomyocytes, which ultimately result in valve degeneration and blood regurgitation due to structural changes in the heart valves. A number of studies have been conducted with the objective of identifying prognostic factors that may influence the prognosis of dogs with MMVD. Nevertheless, there is a paucity of research examining the factors that predict MMVD stage progression as defined by the American College of Veteri-nary Internal Medicine. The objective of this study was to examine whether there are factors associated with stage progression within one year of diagnosis in dogs diagnosed with subclinical MMVD (stage B1 or B2) using physical examination findings, clinicopathologic bio-markers, and echocardiographic markers. This is a retrospective study of veterinary practiceperformed at Chungbuk National University Animal Hospital. The electronic medical recordof the hospital was searched to obtain clinical records of canine patients diagnosed with subclinical MMVD over an 11-year period. For each patient cohort, a logistic regression analysis was conducted. The variables were initially selected using the backward elimination method, and the optimal logistic regression model was determined by removing the independent vari-ables with the largest variance inflation factor. Among the independent variables examined in this study, heart murmur intensity was identified as a statistically significant predictor of stage progression within one year for subclinical MMVD, a finding that aligns with those of previous studies. No other independent variables were found to be significantly associated with sub-clinical MMVD stage progression. This is the inaugural exploratory study to concentrate onblood test results, a relatively straightforward and quantifiable test result that can be readilyobtained in primary care veterinary clinics, among the factors that may be associated with the progression of subclinical MMVD stages.

Myxomatous mitral valve disease (MMVD) in dogs is a heart disease that is characterized by histopathologic changes in cardiomyocytes, which ultimately result in valve degeneration and blood regurgitation due to structural changes in the heart valves. A number of studies have been conducted with the objective of identifying prognostic factors that may influence the prognosis of dogs with MMVD. Nevertheless, there is a paucity of research examining the factors that predict MMVD stage progression as defined by the American College of Veteri-nary Internal Medicine. The objective of this study was to examine whether there are factors associated with stage progression within one year of diagnosis in dogs diagnosed with subclinical MMVD (stage B1 or B2) using physical examination findings, clinicopathologic bio-markers, and echocardiographic markers. This is a retrospective study of veterinary practiceperformed at Chungbuk National University Animal Hospital. The electronic medical recordof the hospital was searched to obtain clinical records of canine patients diagnosed with subclinical MMVD over an 11-year period. For each patient cohort, a logistic regression analysis was conducted. The variables were initially selected using the backward elimination method, and the optimal logistic regression model was determined by removing the independent vari-ables with the largest variance inflation factor. Among the independent variables examined in this study, heart murmur intensity was identified as a statistically significant predictor of stage progression within one year for subclinical MMVD, a finding that aligns with those of previous studies. No other independent variables were found to be significantly associated with sub-clinical MMVD stage progression. This is the inaugural exploratory study to concentrate onblood test results, a relatively straightforward and quantifiable test result that can be readilyobtained in primary care veterinary clinics, among the factors that may be associated with the progression of subclinical MMVD stages.

Myxomatous mitral valve disease (MMVD) in dogs is a heart disease that is characterized by histopathologic changes in cardiomyocytes, which ultimately result in valve degeneration and blood regurgitation due to structural changes in the heart valves. A number of studies have been conducted with the objective of identifying prognostic factors that may influence the prognosis of dogs with MMVD. Nevertheless, there is a paucity of research examining the factors that predict MMVD stage progression as defined by the American College of Veteri-nary Internal Medicine. The objective of this study was to examine whether there are factors associated with stage progression within one year of diagnosis in dogs diagnosed with subclinical MMVD (stage B1 or B2) using physical examination findings, clinicopathologic bio-markers, and echocardiographic markers. This is a retrospective study of veterinary practiceperformed at Chungbuk National University Animal Hospital. The electronic medical recordof the hospital was searched to obtain clinical records of canine patients diagnosed with subclinical MMVD over an 11-year period. For each patient cohort, a logistic regression analysis was conducted. The variables were initially selected using the backward elimination method, and the optimal logistic regression model was determined by removing the independent vari-ables with the largest variance inflation factor. Among the independent variables examined in this study, heart murmur intensity was identified as a statistically significant predictor of stage progression within one year for subclinical MMVD, a finding that aligns with those of previous studies. No other independent variables were found to be significantly associated with sub-clinical MMVD stage progression. This is the inaugural exploratory study to concentrate onblood test results, a relatively straightforward and quantifiable test result that can be readilyobtained in primary care veterinary clinics, among the factors that may be associated with the progression of subclinical MMVD stages.

Background: It is well known that a large number of patients with diabetes also have dyslipidemia, which significantly increases the risk of cardiovascular disease (CVD). This study aimed to evaluate the efficacy and safety of combination drugs consisting of metformin and atorvastatin, widely used as therapeutic agents for diabetes and dyslipidemia. Methods: This randomized, double-blind, placebo-controlled, parallel-group and phase III multicenter study included adults with glycosylated hemoglobin (HbA1c) levels >7.0% and <10.0%, low-density lipoprotein cholesterol (LDL-C) >100 and <250 mg/dL. One hundred eighty-five eligible subjects were randomized to the combination group (metformin+atorvastatin), metformin group (metformin+atorvastatin placebo), and atorvastatin group (atorvastatin+metformin placebo). The primary efficacy endpoints were the percent changes in HbA1c and LDL-C levels from baseline at the end of the treatment. Results: After 16 weeks of treatment compared to baseline, HbA1c showed a significant difference of 0.94% compared to the atorvastatin group in the combination group (0.35% vs. −0.58%, respectively; P<0.0001), whereas the proportion of patients with increased HbA1c was also 62% and 15%, respectively, showing a significant difference (P<0.001). The combination group also showed a significant decrease in LDL-C levels compared to the metformin group (−55.20% vs. −7.69%, P<0.001) without previously unknown adverse drug events. Conclusion The addition of atorvastatin to metformin improved HbA1c and LDL-C levels to a significant extent compared to metformin or atorvastatin alone in diabetes and dyslipidemia patients. This study also suggested metformin’s preventive effect on the glucose-elevating potential of atorvastatin in patients with type 2 diabetes mellitus and dyslipidemia, insufficiently controlled with exercise and diet. Metformin and atorvastatin combination might be an effective treatment in reducing the CVD risk in patients with both diabetes and dyslipidemia because of its lowering effect on LDL-C and glucose.

Antimicrobial resistance significantly threatens human and animal health globally, with con-siderable mortality and economic impact. This study investigated antimicrobial usage in small animal clinics in South Korea, focusing on understanding the trends in prescriptions for therapeutic and preventive purposes. Data were collected from 12 small animal clinics that were analyzed for antimicrobial prescriptions from 2018–2020. A comprehensive dataset was used, including patient signalment, clinical notes, and prescription details, and statistically analyzed using SPSS software. The results indicated that most antimicrobials (93.1%) were prescribed for the treatment of infectious diseases, with a smaller portion (6.9%) used for pre-ventive measures, such as surgery. High prescription rates were observed for the treatment of cutaneous and otological diseases, which may reflect common diseases in companion an-imals. The study highlighted a higher prescription rate for adult age groups, possibly because of the higher prevalence in those groups. Overall, this study provides valuable insights into common prescription patterns in veterinary practice and underscores the need for more strin-gent antimicrobial stewardship to curb the rise of antimicrobial resistance. This suggests that ongoing surveillance and education on appropriate antimicrobial use are crucial for optimizing treatment outcomes and minimizing the development of resistance.

Background: Foot-and-mouth disease (FMD) is a highly contagious viral disease in livestock that has tremendous economic impact nationally. After multiple FMD outbreaks, the South Korean government implemented a vaccination policy for efficient disease control. However, during active surveillance by quarantine authorities, pig farms have reported an insufficient antibody positivity rate to FMD. Objective: In this study, the spatial and temporal trends of insufficiency among pig farms were analyzed, and the effect of the number of government veterinary officers was explored as a potential preventive factor. Methods: Various data were acquired, including national-level surveillance data for antibody insufficiency from the Korea Animal Health Integrated System, the number of veterinary officers, and the number of local pig farms. Temporal and geographical descriptive analyses were conducted to overview spatial and temporal trends. Additionally, logistic regression models were employed to investigate the association between the number of officers per pig farm with antibody insufficiency. Spatial cluster analysis was conducted to detect spatial clusters. Results: The results showed that the incidence of insufficiency tended to decrease in recent years (odds ratio [OR], 0.803; 95% confidence interval [95% CIs], 0.721–0.893), and regions with a higher density of governmental veterinary officers (OR, 0.942; 95% CIs, 0.918–0.965) were associated with a lower incidence. Conclusions This study implies that previously conducted national interventions would be effective, and the quality of government-provided veterinary care could play an important role in addressing the insufficient positivity rate of antibodies.

Background and Objectives: The recent developments in chronic thromboembolic pulmonary hypertension (CTEPH) are emphasizing the multidisciplinary team. We report on the changes in clinical practice following the development of a multidisciplinary team, based on our 7 years of experience. Methods: Multidisciplinary team was established in 2015 offering both balloon pulmonary angioplasty (BPA) and pulmonary endarterectomy (PEA) with technical upgrades by internal and external expertise. For operable cases, PEA was recommended as the primary treatment modality, followed by pulmonary angiography and right heart catheterization after 6 months to evaluate treatment effect and identify patients requiring further BPA. For patients with inoperable anatomy or high surgical risk, BPA was recommended as the initial treatment modality. Patient data and clinical outcomes were closely monitored. Results: The number of CTEPH treatments rapidly increased and postoperative survival improved after team development. Before the team, 38 patients were treated by PEA for 18 years; however, 125 patients were treated by PEA or BPA after the team for 7 years. The number of PEA performed was 64 and that of BPA 342 sessions. World Health Organization functional class I or II was achieved in 93% of patients. The patients treated with PEA was younger, male dominant, higher pulmonary artery pressure, and smaller cardiac index, than BPA-only patients. In-hospital death after PEA was only 1 case and none after BPA. Conclusions The balanced development of BPA and PEA through a multidisciplinary team approach proved synergistic in increasing the number of actively treated CTEPH patients and improving clinical outcomes.

The surveillance and epidemiological investigation systems for companion animals in South Korea are significantly underdeveloped compared to those for humans and livestock. Recent outbreaks, such as idiopathic neuromuscular syndrome and highly pathogenic avian influenza among cats, have highlighted the need for reliable systems. This short review conducts situation analysis regarding disease surveillance and epidemiological investigation for companion animals in South Korea. The current challenges include an absence of administrative leadership, a lack of legal support, and unreliable medical data. The recommendations for future directions include clear leadership by the Animal and Plant Quarantine Agency, amending the Act on the Prevention of Contagious Animal Diseases to include companion animals, and enhancing the quality of medical data through standardized coding systems, such as Systematized Nomenclature of Medicine Clinical Terms. In addition, sentinel surveillance rather than universal systems should be established to provide adequate incentives for local practitioners to provide data and develop sustainable public–private networks. These recommendations could be important for developing a comprehensive and sustainable system for disease surveillance and epidemiological investigation in the companion animal field.

Artificial intelligence (AI) in radiology is a rapidly developing field with several prospective clinical studies demonstrating its benefits in clinical practice. In 2022, the Korean Society of Radiology held a forum to discuss the challenges and drawbacks in AI development and implementation. Various barriers hinder the successful application and widespread adoption of AI in radiology, such as limited annotated data, data privacy and security, data heterogeneity, imbalanced data, model interpretability, overfitting, and integration with clinical workflows. In this review, some of the various possible solutions to these challenges are presented and discussed; these include training with longitudinal and multimodal datasets, dense training with multitask learning and multimodal learning, self-supervised contrastive learning, various image modifications and syntheses using generative models, explainable AI, causal learning, federated learning with large data models, and digital twins.