Atherosclerotic cardiovascular disease (ASCVD) is the leading cause of death in Korea. According to a report of published by Statistics Korea in 2014, cerebrovascular disease and cardiovascular disease were the major/leading causes of mortality. However, it is more difficult to identify prevalence and incidence of a disease than the mortality owing to the lack of national-level statistics. Few studies have examined the prevalence and incidence of ASCVD and its risk factors since 2012. This study aimed to estimate the prevalence and incidence of ASCVD and its risk factors in Korea using national claims data. We conducted a retrospective analysis using the national claims data of the Health Insurance Review and Assessment Service. Patients aged ≥18 years with ASCVD (defined as myocardial infarction, angina, coronary revascularization, peripheral artery disease, ischemic stroke, and transient ischemic attack) were identified between January 1, 2014 and December 31, 2015. Patients at high risk for ASCVD (defined as hypertension, diabetes mellitus, and dyslipidemia without ASCVD during the baseline period) were identified between January 1, 2015 and December 31, 2015. We estimated the prevalence, cumulative incidence, and incidence density. These were further stratified by age and sex. The respective denominators for prevalence and incidence were the census population and the at-risk population (defined as the population without respective disease 1 year prior to the respective disease identification). Among the included Korean adult patients, the overall prevalence of clinical ASCVD per 1000 individuals was 98.25 in 2014 and 101.11 in 2015. The respective cumulative incidence and incidence density rates of ASCVD per 1000 individuals were 65.30 and 68.03 in 2014, and 67.05 and 69.94 in 2015, respectively. Peripheral artery disease seemed to drive the increase in the total prevalence and incidence of ASCVD. The prevalence and incidence of ASCVD continued to increase with age until 79 years. This national population-based study confirmed the high prevalence and incidence of ASCVD and its risk factors in the adult population of South Korea. We suggest that more intensive treatment and prevention are needed to prevent ASCVD.

Background: Parkinson’s disease (PD) and drug-induced parkinsonism (DIP) are the major diseases of parkinsonism. To better understand parkinsonism, we aimed to assess the prevalence and incidence of PD and DIP in Korea from 2012 to 2015. Methods: We used the Health Insurance Review and Assessment Service database, which covers the entire population in Korea. We used claims during 2011–2015 to assess epidemiology of PD and DIP during 2012–2015. Retrospective cross-sectional study design was employed to assess prevalence, whereas retrospective cohort study design was used to determine incidence. Patients with at least one claim with ICD-10 G20 and who received antiparkinsonian drugs for at least 60 days were classified as having PD. We excluded patients with antiparkinsonian drugs that can be used for indications other than PD. Patients with at least one claim with ICD-10 G211 or G251 during the prescription period of drugs that are frequently related with DIP were classified as having DIP. Incident cases had a disease-free period of 1 year before diagnosis. To evaluate the significance of changes in the prevalence or incidence over time, Poisson regression was used to determine p for trend. Results: The prevalence of PD increased from 156.9 per 100,000 persons in 2012 to 181.3 per 100,000 persons in 2015 (p for trend< 0.0001). The incidence of PD decreased steadily from 35.4 per 100,000 person-years in 2012 to 33.3 per 100,000 person-years in 2015 (p for trend< 0.0001). The prevalence of DIP increased from 7.3 per 100,000 persons in 2012 to 15.4 per 100,000 persons in 2015 (p for trend< 0.0001) and the incidence of DIP increased from 7.1 per 100,000 person-years in 2012 to 13.9 per 100,000 person-years in 2015 (p for trend< 0.0001). Conclusions: Our study suggests that the incidence of PD has gradually decreased whereas, the incidence of DIP increased from 2012 to 2015. Further studies are warranted to examine possible causes of increased DIP incidence in order to develop management strategy for parkinsonism.

It is important to achieve the low-density lipoprotein cholesterol (LDL-C) goal recommended by clinical guidelines in managing the risk of cardiovascular (CV) events, however, the current management of LDL-C in actual clinical settings is suboptimal. We examined the LDL-C level among patients with dyslipidemia against the 2015 Korean guidelines, the crude rates of CV events based on LDL-C goal achievement, and the factors associated with LDL-C goal achievement. This was a retrospective cohort study using the National Health Insurance Service–National Health Screening Cohort (NHIS-HEALS) database from 2006 to 2013. Patients who had a health examination with LDL-C measurement between January 1, 2007, and December 31, 2011 were identified. Patients were required to have at least one diagnosis of dyslipidemia during the 1 year before the index date, defined as the first date of LDL-C measurement. The 2015 Korean guidelines were used to measure LDL-C goal achievement based on the CV risk level. Crude CV event rates were calculated for total and individual CV events as the number of events divided by person-years (PYs) during the follow-up period. CV events included acute coronary syndrome, ischemic stroke, peripheral artery disease, CV death, and all-cause death. Factors associated with LDL-C goal achievement were assessed using logistic regression. In the NHIS-HEALS database, 69,942 patients met the eligibility criteria: 36.7%, 22.5%, 20.1%, and 20.6% were among the very high-, high-, moderate-, and low-risk groups for the CV events, respectively, as defined by the 2015 Korean guidelines. Approximately half of the patients with dyslipidemia (47.6%) achieved their recommended LDL-C goal, but the achievement rates were substantially different across CV risk levels (17.6%, 47.2%, 66.9%, and 82.4% for very high-, high-, moderate-, and low-risk groups, respectively; P<0.0001). The crude event rate of total CV events during the follow-up period in the LDL-C goal non-achievers was higher than that in the LDL-C goal achievers (24.35/100 PYs vs. 11.93/100 PYs; P<0.0001). LDL-C goal achievement was significantly associated with patient characteristics, including age, sex, body mass index, lipid-modifying therapy, and CV risk level. In South Korea, LDL-C goal achievement among patients with very high or high CV risk was suboptimal. Patients who did not achieve the goal showed a higher rate of CV events during the follow-up period than patients who achieved the goal. LDL-C management strategies should be highlighted in dyslipidemia patients who are less likely to achieve the goal, such as female, overweight or obese patients, patients not adherent to statin, or patients with very high or high CV risk.

In this study, we aimed to assess the utilization pattern (potentially inappropriate dosing and concomitant use of contraindicated drugs) and adherence to direct oral anticoagulants (DOACs), including apixaban, dabigatran, and rivaroxaban, in patients with atrial fibrillation (AF) unsuitable for warfarin. We used nationally representative data, namely Health Insurance Review and Assessment Service-Aged Patient Sample 2014, that included medical and pharmacy claims of approximately 1 million patients aged 65 or older. We included patients who had at least one diagnosis of AF and at least one prescription of DOAC between January 1 and December 31, 2014. In 2014, DOACs were reimbursed only to patients with AF unsuitable for warfarin. Appropriate dosing and contraindicated drugs were determined according to the Summary of Product Characteristics for each DOAC. Multivariate logistic regression was performed to examine the factors contributing to the concomitant use of contraindicated drugs. To assess adherence, we calculated the medication possession ratio (MPR). The percentage of inappropriate dosing was 11.8% among 1,234 patients with AF; it was the highest in rivaroxaban users (16.8%). Contraindicated drugs were prescribed to 236 patients (19.1%). Clinics, smaller healthcare institutions, and outpatient visits were significantly related to contraindicated drug use. The mean MPRs were 0.95, 0.93, and 0.91 for apixaban, dabigatran, and rivaroxaban, respectively (P = 0.075). Careful monitoring is warranted in patients with AF aged over 65 who were unsuitable for warfarin to reduce the incidence of inappropriate dosing and concomitant use of contraindicated drugs.

Background: Exudative age-related macular degeneration (AMD), one of the leading causes of blindness, requires expensive drugs such as anti–vascular endothelial growth factor (VEGF) agents. The long-term regular use of effective but expensive drugs causes an economic burden for patients with exudative AMD. However, there are no studies on the long-term patient-centered economic burden of exudative AMD after reimbursement of anti-VEGFs. Objective: This study aimed to evaluate the patient-centered economic burden of exudative AMD for 2 years, including nonreimbursement and out-of-pocket costs, compared with nonexudative AMD using the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM). Methods: This retrospective cohort study was conducted using the OMOP CDM, which included 2,006,478 patients who visited Seoul National University Bundang Hospital from June 2003 to July 2019. We defined the exudative AMD group as patients aged >50 years with a diagnosis of exudative AMD and a prescription for anti-VEGFs or verteporfin. The control group was defined as patients aged >50 years without a diagnosis of exudative AMD or a prescription for anti-VEGFs or verteporfin. To adjust for selection bias, controls were matched by propensity scores using regularized logistic regression with a Laplace prior. We measured any medical cost occurring in the hospital as the economic burden of exudative AMD during a 2-year follow-up period using 4 categories: total medical cost, reimbursement cost, nonreimbursement cost, and out-of-pocket cost. To estimate the average cost by adjusting the confounding variable and overcoming the positive skewness of costs, we used an exponential conditional model with a generalized linear model. Results: We identified 931 patients with exudative AMD and matched 783 (84.1%) with 2918 patients with nonexudative AMD. In the exponential conditional model, the total medical, reimbursement, nonreimbursement, and out-of-pocket incremental costs were estimated at US $3426, US $3130, US $366, and US $561, respectively, in the first year and US $1829, US $1461, US $373, and US $507, respectively, in the second year. All incremental costs in the exudative AMD group were 1.89 to 4.25 and 3.50 to 5.09 times higher in the first and second year, respectively, than those in the control group (P<.001 in all cases). Conclusions: Exudative AMD had a significantly greater economic impact (P<.001) for 2 years on reimbursement, nonreimbursement, and out-of-pocket costs than nonexudative AMD after adjusting for baseline demographic and clinical characteristics using the OMOP CDM. Although economic policies could relieve the economic burden of patients with exudative AMD over time, the out-of-pocket cost of exudative AMD was still higher than that of nonexudative AMD for 2 years. Our findings support the need for expanding reimbursement strategies for patients with exudative AMD given the significant economic burden faced by patients with incurable and fatal diseases both in South Korea and worldwide.

Background: Hospitalized patients with blood cancer face an elevated risk for cardiovascular diseases caused by cardiotoxic cancer therapies, which can lead to cardiovascular-related unplanned readmissions. Objective: We aimed to develop a machine learning (ML) model to predict 90-day unplanned readmissions for major adverse cardiovascular events (MACE) in hospitalized patients with blood cancers. Design: A retrospective population-based cohort study. Methods: We analyzed patients aged ≥18 with blood cancers (leukemia, lymphoma, myeloma) using the Nationwide Readmissions Database. MACE included acute myocardial infarction, ischemic heart disease, stroke, heart failure, revascularization, malignant arrhythmias, and cardiovascular-related death. Six ML algorithms (L2-Logistic regression, Support Vector Machine, Complement Naïve Bayes, Random Forest, XGBoost, and CatBoost) were trained on 2017-2018 data and tested on 2019 data. The SuperLearner algorithm was used for stacking models. Cost-sensitive learning addressed data imbalance, and hyperparameters were tuned using 5-fold cross-validation with Optuna framework. Performance metrics included the Area Under the Receiver Operating Characteristics Curve (ROCAUC), Precision-Recall AUC (PRAUC), balanced Brier score, and F2 score. SHapley Additive exPlanations (SHAP) values assessed feature importance, and clustering analysis identified high-risk subpopulations. Results: Among 76 957 patients, 1031 (1.34%) experienced unplanned 90-day MACE-related readmissions. CatBoost achieved the highest ROCAUC (0.737, 95% CI: 0.712-0.763) and PRAUC (0.040, 95% CI: 0.033-0.050). The SuperLearner algorithm achieved slight improvements in most performance metrics. Four leading predictive features were consistently identified across algorithms, including older age, heart failure, coronary atherosclerosis, and cardiac dysrhythmias. Twenty-three clusters were determined with the highest-risk cluster (mean log odds of 1.41) identified by nonrheumatic/unspecified valve disorders, coronary atherosclerosis, and heart failure. Conclusions: Our ML model effectively predicts MACE-related readmissions in hospitalized patients with blood cancers, highlighting key predictors. Targeted discharge strategies may help reduce readmissions and alleviate the associated healthcare burden.