Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.

Background/Aims: Chronic hepatitis C (CHC) patients who failed antiviral therapy are at increased risk for hepatocellular carcinoma (HCC). This study assessed the potential role of metformin and statins, medications for diabetes mellitus (DM) and hyperlipidemia (HLP), in reducing HCC risk among these patients. Methods: We included CHC patients from the T-COACH study who failed antiviral therapy. We tracked the onset of HCC 1.5 years post-therapy by linking to Taiwan’s cancer registry data from 2003 to 2019. We accounted for death and liver transplantation as competing risks and employed Gray’s cumulative incidence and Cox subdistribution hazards models to analyze HCC development. Results: Out of 2,779 patients, 480 (17.3%) developed HCC post-therapy. DM patients not using metformin had a 51% increased risk of HCC compared to non-DM patients, while HLP patients on statins had a 50% reduced risk compared to those without HLP. The 5-year HCC incidence was significantly higher for metformin non-users (16.5%) versus non-DM patients (11.3%; adjusted sub-distribution hazard ratio [aSHR]=1.51; P=0.007) and metformin users (3.1%; aSHR=1.59; P=0.022). Statin use in HLP patients correlated with a lower HCC risk (3.8%) compared to non-HLP patients (12.5%; aSHR=0.50; P<0.001). Notably, the increased HCC risk associated with non-use of metformin was primarily seen in non-cirrhotic patients, whereas statins decreased HCC risk in both cirrhotic and non-cirrhotic patients. Conclusions Metformin and statins may have a chemopreventive effect against HCC in CHC patients who failed antiviral therapy. These results support the need for personalized preventive strategies in managing HCC risk.

Background: This report presents annual data from the surgical site infection (SSI) module of the Korean National Healthcare-associated Infections Surveillance System (KONIS) from July 2021 to June 2022. Methods: Surveillance of 20 surgeries (e.g., stomach, colon, rectal, gallbladder surgery, knee replacement, hip replacement, craniotomy, ventricular shunts, spinal fusion, laminectomy, cardiac artery bypass grafting - incision in the chest site only and incisions both the chest and donor site, cardiac, prostatectomy, abdominal hysterectomy, vaginal hysterectomy, appendectomy, thoracic, cesarean section, and head and neck surgeries) associated with SSI was performed between July 1, 2021, and June 30, 2022, according to the KONIS Manual 2020. Results: A total of 133,281 surgical cases were collected and 1,100 SSIs were identified, resulting in a SSI rate of 0.83%. The SSI rates for 30-day surveillance surgeries were 1.9% for stomach, 2.82% for colon, 1.88% for rectal, 0.29% for gallbladder, 0.25% for lumbar laminectomy, 0.33% for cesarean section, 0.67% for abdominal hysterectomy, 0.74% for vaginal hysterectomy, 0.23% for prostatectomy, 1.39% for appendectomy, and 0.06% for thoracic surgeries. Neck surgery could not be analyzed due to no reported cases. The SSI rates for the 90-day surveillance surgeries were 0.16% for knee replacement, 0.54% for hip replacement, 0.89% for spinal fusion, 0.70% for craniotomy, 0.92% for ventricular shunt, 1.13% for cardiac, 1.80% for cardiac artery bypass grafting (chest only incision), and 1.64% for cardiac artery bypass grafting (chest and leg incision) surgeries. In total, 608 strains were isolated and cultured from 1,286 infections. Conclusion Compared with the incidence of SSI (1.06%) in 2018, the overall incidence decreased, and most site-specific infection rates decreased or remained the same.

Objective: We aimed to identify the expectations and preferences for medication and medical decision-making in patients with major psychiatric disorders. Methods: A survey was conducted among patients with major psychiatric disorders who visited psychiatric outpatient clinics at 15 hospitals between 2016 and 2018 in Korea. The survey consisted of 12 questions about demographic variables and opinions on their expectations for medication, important medical decision-makers, and preferred drug type. The most preferred value in each category in the total population was identified, and differences in the preference ratio of each item among the disease groups were compared. Results: A total of 707 participants were surveyed. In the total population, patients reported high efficacy (44.01%±21.44%) as the main wish for medication, themselves (37.39%±22.57%) and a doctor (35.27%±22.88%) as the main decision makers, and tablet/capsule (36.16%±30.69%) as the preferred type of drug. In the depressive disorders group, the preference ratio of high efficacy was significantly lower, and the preference ratio of a small amount was significantly higher than that of the psychotic disorder and bipolar disorder groups. The preference ratio of a doctor as an important decision maker in the bipolar disorder group was higher compared to the other groups. Conclusion This study revealed the preference for medications and showed differences among patients with psychiatric disorders. Providing personalized medicine that considers a patient’s preference for the drug may contribute to the improvement of drug compliance and outcomes.

Objectives: Electrocardiography (ECG)-based diagnosis by experts cannot maintain uniform quality because individual differences may occur. Previous public databases can be used for clinical studies, but there is no common standard that would allow databases to be combined. For this reason, it is difficult to conduct research that derives results by combining databases. Recent commercial ECG machines offer diagnoses similar to those of a physician. Therefore, the purpose of this study was to construct a standardized ECG database using computerized diagnoses. Methods: The constructed database was standardized using Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) and Observational Medical Outcomes Partnership–common data model (OMOP-CDM), and data were then categorized into 10 groups based on the Minnesota classification. In addition, to extract high-quality waveforms, poor-quality ECGs were removed, and database bias was minimized by extracting at least 2,000 cases for each group. To check database quality, the difference in baseline displacement according to whether poor ECGs were removed was analyzed, and the usefulness of the database was verified with seven classification models using waveforms. Results: The standardized KURIAS-ECG database consists of high-quality ECGs from 13,862 patients, with about 20,000 data points, making it possible to obtain more than 2,000 for each Minnesota classification. An artificial intelligence classification model using the data extracted through SNOMED-CT showed an average accuracy of 88.03%. Conclusions The KURIAS-ECG database contains standardized ECG data extracted from various machines. The proposed protocol should promote cardiovascular disease research using big data and artificial intelligence.

Human Q fever, a zoonosis caused by Coxiella burnetii, presents with diverse clinical manifestations ranging from mild self-limited febrile illnesses to life-threatening complications such as endocarditis or vascular infection. Although acute Q fever is a benign illness with a low mortality rate, a large-scale outbreak of Q fever in the Netherlands led to concerns about the possibility of blood transfusion-related transmission or obstetric complications in pregnant women. Furthermore, a small minority (< 5%) of patients with asymptomatic or symptomatic infection progress to chronic Q fever. Chronic Q fever is fatal in 5–50% of patients if left untreated. In South Korea, Q fever in humans was designated as a notifiable infectious disease in 2006, and the number of Q fever cases has increased sharply since 2015. Nonetheless, it is still considered a neglected and under-recognized infectious disease. In this review, recent trends of human and animal Q fever in South Korea, and public health concerns regarding Q fever outbreaks are reviewed, and we consider how a One Health approach could be applied as a preventive measure to prepare for zoonotic Q fever outbreaks.

Organ crosstalk between the kidney and the heart has been suggested. Acute kidney injury (AKI) and acute heart failure (AHF) are well-known independent risk factors for mortality in hospitalized patients. This study aimed to investigate if these conditions have an additive effect on mortality in hospitalized patients, as this has not been explored in previous studies. Methods: We retrospectively reviewed the records of 101,804 hospitalized patients who visited two tertiary hospitals in the Republic of Korea over a period of 5 years. AKI was diagnosed using serum creatinine-based criteria, and AHF was classified using International Classification of Diseases codes within 2 weeks after admission. Patients were divided into four groups according to the two conditions. The primary outcome was all-cause mortality. Results: AKI occurred in 6.8% of all patients (n = 6,920) and AHF in 1.2% (n = 1,244). Three hundred thirty-one patients (0.3%) developed both conditions while AKI alone was present in 6,589 patients (6.5%) and AHF alone in 913 patients (0.9%). Among the 5,181 patients (5.1%) who died, 20.8% died within 1 month. The hazard ratio for 1-month mortality was 29.23 in patients with both conditions, 15.00 for AKI only, and 3.39 for AHF only. The relative excess risk of interaction was 11.85 (95% confidence interval, 2.43–21.27), and was more prominent in patients aged <75 years and those without chronic heart failure. Conclusion: AKI and AHF have a detrimental additive effect on short-term mortality in hospitalized patients.

Background: Thiazolidinediones (TZDs) have been associated with various safety concerns including weight gain, bladder cancer, and congestive heart failure (CHF). This study evaluated the efficacy and safety of lobeglitazone, a novel TZD in patients with type 2 diabetes mellitus (T2DM) in real practice. Methods: In this non-interventional, multi-center, retrospective, and observational study conducted at 15 tertiary or secondary referral hospitals in Korea, a total of 2,228 patients with T2DM who received lobeglitazone 0.5 mg for more than 1 year were enrolled. Results: Overall adverse events (AEs) occurred in 381 patients (17.10%) including edema in 1.97% (n=44). Cerebrovascular and cardiovascular diseases were identified in 0.81% (n=18) and 0.81% (n=18), respectively. One case of CHF was reported as an AE. Edema occurred in 1.97% (n=44) of patients. Hypoglycemia occurred in 2.47% (n=55) of patients. Fracture occurred in 1.17% (n=26) of all patients. Lobeglitazone significantly decreased HbA1c level, resulting in a mean treatment difference of -1.05%± 1.35% (P<0.001), and decreased total cholesterol, triglyceride, and low-density lipoprotein cholesterol. However, it increased high-density lipoprotein cholesterol, regardless of statin administration. The patients who received lobeglitazone 0.5 mg showed an apparent reduction in glycosylated hemoglobin (HbA1c) from baseline during the first 6 months of treatment. The HbA1c levels remained stable between months 6 and 42. Conclusion Lobeglitazone has long-term safety profile, good glycemic-lowering effect and long-term durability of glycemic control in real-world clinical settings.

Background: To evaluate prescription trends and clinical factors of the sodium-glucose cotransporter 2 inhibitors (SGLT2i) use according to the presence of atherosclerotic cardiovascular disease (ASCVD) or heart failure (HF) in Korean patients with type 2 diabetes mellitus (T2DM). Methods: Prescription patterns of SGLT2i use between 2015 and 2019 were determined using the Korean National Health Insurance Service database of claims. Results: Of all patients with T2DM (n=4,736,493), the annual prescription rate of SGLT2i increased every year in patients with ASCVD (from 2.2% to 10.7%) or HF (from 2.0% to 11.1%). After the first hospitalization for ASCVD (n=518,572), 13.7% (n=71,259) of patients initiated SGLT2i with a median of 10.6 months. After hospitalization for HF (n=372,853), 11.2% (n=41,717) of patients initiated SGLT2i after a median of 8.8 months. In multivariate regression for hospitalization, older age (per 10 years, odds ratio [OR], 0.57; 95% confidence interval [CI], 0.56 to 0.57), lower household income (OR, 0.93; 95% CI, 0.92 to 0.95), rural residents (OR, 0.95; 95% CI, 0.93 to 0.97), and dipeptidyl peptidase-4 inhibitor (DPP-4i) users (OR, 0.82; 95% CI, 0.81 to 0.84) were associated with lesser initiation of SGLT2i in ASCVD. Additionally, female gender (OR, 0.97; 95% CI, 0.95 to 0.99) was associated with lesser initiation of SGLT2i in HF. Conclusion The prescription rate of SGLT2i increased gradually up to 2019 but was suboptimal in patients with ASCVD or HF. After the first hospitalization for ASCVD or HF, older age, female gender, low household income, rural residents, and DPP-4i users were less likely to initiate SGLT2i.