Objectives: To propose age group classification criteria for efficient tooth loss management by ana-lyzing the distribution of tooth loss in Korean adults by age group and causes of tooth loss. In addi-tion, to determine the efficacy of a Significant Tooth Loss index. Methods: The study included 13,199 adults who participated in the seventh Korea National Health and Nutrition Examination Survey (2016-2018). The mean number of missing teeth was compared by classifying the ages into 10- and 5-year intervals. Based on this analysis, the distribution of missing teeth was determined by classifying the age groups into 15-year intervals. Subsequently, the causes of tooth loss by age group at 15-year intervals and the efficacy of the Significant Tooth Loss Index were determined. Results: Classification at 5-year age intervals was more appropriate for analyzing changes in the distribution of missing teeth than classification at 10-year age intervals. However, establishing a public oral health program for the management of tooth loss on a 5-year or 10-year basis is im-practical. Therefore, a classification method with 15-year age intervals was proposed, in which the groups were young (19-34 years), middle-aged (35-49 years), older adult (50-64 years), and elderly (65 years or older). Although the criteria for the Significant Tooth Loss Index were appropri-ate for the young, older adults, and elderly groups, modifications were required for the middle-aged group. Conclusions Age-based oral health programs for adults should be promoted to prevent tooth loss by classifying adults into different age groups based on their clinical characteristics.

Purpose: To estimate the sample size required for developing artificial intelligence (AI) that can predict soft-tissue and alveolar bone changes following orthodontic treatment. Materials and Methods: From the original data sets with N=887, consisting of 132 input and 88 output variables used to create AI models for predicting treatment changes following orthodontic treatment, six subsets of the data (n=75, 150, 300, 450, 600, and 750) were generated through random resampling procedures. The process was repeated four times, resulting in 24 different data subsets. Each data subset was used to create a total of 24 AI models using the TabNet deep neural network algorithm. The clinically acceptable prediction accuracy was defined as a less than 1.5 mm prediction error on the lower lip. The prediction errors from each AI model were compared according to sample sizes and analyzed to estimate the optimal sample size. Results: The prediction error decreased with increasing sample sizes. A training sample size greater than approximately 1650 was estimated to develop an AI model with less than 1.5 mm of prediction errors at the lower lip area. Conclusion From a statistical and research design perspective, a considerable amount of training data appears necessary to develop an AI prediction model with clinically acceptable accuracy.

Background: Barriers to treatment with intravenous thrombolysis (IVT) for patients with acute ischemic stroke (AIS) in South Korea remain incompletely characterized. We analyze a nationwide prospective cohort to determine patient-level features associated with delayed presentation and non-treatment of potential IVT-eligible patients. Methods: We identified consecutive patients with AIS from 01/2011 to 08/2023 from a multicenter and prospective acute stroke registry in Korea. Patients were defined as IVT candidates if they presented within 4.5 hours from the last known well, had no lab evidence of coagulopathy, and had National Institute of Health Stroke Scale (NIHSS) ≥ 4. Multivariable generalized linear mixed regression models were used to investigate the associations between their characteristics and the IVT candidates or the use of IVT among the candidates. Results: Among 84,103 AIS patients, 41.0% were female, with a mean age of 69 ± 13 years and presentation NIHSS of 4 [interquartile range, 1–8]. Out of these patients, 13,757 (16.4%) were eligible for IVT, of whom 8,179 (59.5%) received IVT. Female sex (adjusted risk ratio [RR], 0.90; 95% confidence interval [CI], 0.86–0.94) and lower years of education (adjusted RR, 0.90; 95% CI, 0.84–0.97 for 0–3 years, compared to ≥ 13 years) were associated with a decreased likelihood of presenting as eligible for IVT after AIS; meanwhile, young age (adjusted RR, 1.12; 95% CI, 1.01–1.24 for ≤ 44 years, compared to 75–84 years) was associated with an increased likelihood of being an IVT candidate. Among those who were eligible for IVT, only age was significantly associated with the use of IVT (adjusted RR, 1.09; 95% CI, 1.03–1.16 for age 65–74 and adjusted RR, 0.83; 95% CI, 0.76–0.90 for ≥ 85 years, respectively). Conclusion Most patients with AIS present outside IVT eligibility in South Korea, and only 60% of eligible patients were ultimately treated. We identified increased age, female sex and lower education as key features on which to focus interventions for improving IVT utilization.

Background: Prevention of contrast-induced nephropathy (CIN) is crucial in acute myocardial infarction (AMI) patients undergoing coronary interventions. Previous studies suggest that high-dose statins may aid in CIN prevention, yet comparative studies among different statin types using cystatin C (cysC) as a biomarker for CIN are absent. This study evaluated the effectiveness of high-dose rosuvastatin versus atorvastatin in preventing cysC-based CIN (cysC-CIN) in AMI patients. Methods: This multicenter registry included 431 patients (rosuvastatin 20 mg: n = 231, atorvastatin 40 mg: n = 200). The primary endpoint was cysC-CIN incidence within 48 hours post contrast; the secondary endpoints were creatinine-based CIN (cr-CIN) incidence within 72 hours post contrast and post 30 days adverse events. Results: The incidences of cysC-CIN (12.1% vs. 7.5%, P = 0.103) and cr-CIN (6.2% vs. 3.5%, P = 0.103) were higher in the atorvastatin group without significant statistical differences.Multivariable regression analysis, which was adjusted for CIN risk factors and the variables with univariate association, showed no increased odds ratio (OR) (OR, 2.185; 95% confidence interval [CI], 0.899, 5.315; P = 0.085) for cysC-CIN in the atorvastatin group compared to the rosuvastatin group. However, statin-naïve atorvastatin subgroup had significantly increased odds of cysC-CIN compared to the rosuvastatin group (OR, 2.977; 95% CI, 1.057, 8.378; P = 0.039). At post 30 days renal, cardiovascular, and mortality event rates were both low and similar between the two groups. Conclusion No significant difference in cysC-CIN incidence was found between the highdose rosuvastatin and atorvastatin groups in AMI patients and cysC was more sensitive to the early detection of CIN than creatinine.

Physician–scientists play a pivotal role in bridging clinical practice and biomedical research, advancing medical science, and tackling complex healthcare challenges. In South Korea, the declining number of medical doctors engaging in basic medical sciences has prompted the implementation of various training initiatives since the 2000s. Notable initiatives, such as the Integrated Physician–Scientist Training Program (2019) and the Global Physician–Scientist Training Program (2024), aim to cultivate multidisciplinary physician–scientists capable of addressing unmet medical needs. This study offers a comprehensive overview of the current training systems, funding mechanisms, and strategic approaches for physician–scientists in South Korea, compares them with international best practices, and proposes actionable policy recommendations to enhance their effectiveness and long-term sustainability.

Background: Because of the low prevalence of inherited retinal diseases, reports on the distribution of retinitis pigmentosa (RP)-related genes in Korean patients are scarce. The aim of this study was to determine the mutation spectrum and allele frequency and observe the final diagnoses in a Korean cohort clinically diagnosed with RP. Methods: We used whole-exome sequencing (WES) to analyze a Korean cohort of 100 unrelated patients clinically diagnosed with RP. The possible pathogenicity of each variant was assessed based on the guidelines of the American College of Medical Genetics and Genomics and Association for Molecular Pathology, in-silico prediction tools, known clinical phenotypes, and inheritance patterns. Results: Definite causative genes were detected in 60/100 patients (60.0%). Of these 60 cases, USH2A was the most common causative gene (14/60, 23.3%), followed by EYS (13/60, 21.7%) and RP1 (6/60, 10.0%). The clinical diagnosis was redefined in 9 of the 60 probands (15.0%) with causative genes after WES. Five of the 60 patients (8.3%) carried a causative variant in CHM, and the clinical diagnosis was redefined as choroideremia. Leber congenital amaurosis was diagnosed in 2/60 probands (3.3%), and RDH12 and RPGRIP1 were the causative genes in each patient. One patient (1/60, 1.7%) was diagnosed with Bietti’s crystalline dystrophy, with CYP4V2 identified as the causative gene. In another patient (1/60, 1.7%), ABCA4 variants were detected with clinical findings suggestive of cone-rod dystrophy. Conclusion This study reports the mutational spectrum of a cohort of Korean patients with a clinical diagnosis of RP who were referred for genetic testing. This study adds valuable data regarding the frequency of genes as well as their relation to the age of symptom onset and relation to other inherited retinal degenerations.

Background: With growing elderly populations, management of patients with acute stroke is increasingly important. In South Korea, the Acute Stroke Quality Assessment Program (ASQAP) has contributed to improving the quality of stroke care and practice behavior in healthcare institutions. While the mortality of hemorrhagic stroke remains high, there are only a few assessment indices associated with hemorrhagic stroke. Considering the need to develop assessment indices to improve the actual quality of care in the field of acute stroke treatment, this study aims to investigate the current status of human resources and practices related to the treatment of patients with acute stroke through a nationwide survey. Methods: For the healthcare institutions included in the Ninth ASQAP of the Health Insurance Review and Assessment Service (HIRA), data from January 2022 to December 2022 were collected through a survey on the current status and practice of healthcare providers related to the treatment of patients with acute stroke. The questionnaire consisted of 19 items, including six items on healthcare providers involved in stroke care and 10 items on the care of patients with acute stroke. Results: In the treatment of patients with hemorrhagic stroke among patients with acute stroke, neurosurgeons were the most common providers. The contribution of neurosurgeons in the treatment of ischemic stroke has also been found to be equivalent to that of neurologists. However, a number of institutions were found to be devoid of healthcare providers who perform definitive treatments, such as intra-arterial thrombectomy for patients with ischemic stroke or cerebral aneurysm clipping for subarachnoid hemorrhage. The intensity of the workload of healthcare providers involved in the care of patients with acute stroke, especially those involved in definitive treatment, was also found to be quite high. Conclusion Currently, there are almost no assessment indices specific to hemorrhagic stroke in the ASQAP for acute stroke. Furthermore, it does not reflect the reality of the healthcare providers and practices that provide definitive treatment for acute stroke. The findings of this study suggest the need for the development of appropriate assessment indices that reflect the realities of acute stroke care.

Background: The accuracy of Logical Observation Identifiers Names and Codes (LOINC) mappings is reportedly low, and the LOINC codes used for research purposes in Korea have not been validated for accuracy or usability. Our study aimed to evaluate the discrepancies and similarities in interoperability using existing LOINC mappings in actual patient care settings. Methods: We collected data on local test codes and their corresponding LOINC mappings from seven university hospitals. Our analysis focused on laboratory tests that are frequently requested, excluding clinical microbiology and molecular tests. Codes from nationwide proficiency tests served as intermediary benchmarks for comparison. A research team, comprising clinical pathologists and terminology experts, utilized the LOINC manual to reach a consensus on determining the most suitable LOINC codes. Results: A total of 235 LOINC codes were designated as optimal codes for 162 frequent tests.Among these, 51 test items, including 34 urine tests, required multiple optimal LOINC codes, primarily due to unnoted properties such as whether the test was quantitative or qualitative, or differences in measurement units. We analyzed 962 LOINC codes linked to 162 tests across seven institutions, discovering that 792 (82.3%) of these codes were consistent. Inconsistencies were most common in the analyte component (38 inconsistencies, 33.3%), followed by the method (33 inconsistencies, 28.9%), and properties (13 inconsistencies, 11.4%). Conclusion This study reveals a significant inconsistency rate of over 15% in LOINC mappings utilized for research purposes in university hospitals, underlining the necessity for expert verification to enhance interoperability in real patient care.

Background: Shortage of organ donors in the Republic of Korea has become a major problem. To address this, it has been questioned whether heart transplant (HTx) allocation should be modified to reduce priority of older patients. We aimed to evaluate post-HTx outcomes according to recipient age and specific pre-HTx conditions using a nationwide prospective cohort. Methods: We analyzed clinical characteristics of 628 patients from the Korean Organ Transplant Registry who received HTx from January 2015 to December 2020. Enrolled recipients were divided into three groups according to age. We also included comorbidities including ambulatory status. Non-ambulatory status was defined as pre-HTx support with either extracorporeal membrane oxygenation, continuous renal replacement therapy, or mechanical ventilation. Results: Of the 628 patients, 195 were < 50 years, 322 were 50–64 years and 111 were ≥ 65years at transplant. Four hundred nine (65.1%) were ambulatory and 219 (34.9%) were nonambulatory. Older recipients tended to have more comorbidities, ischemic cardiomyopathy, and received older donors. Post-HTx survival was significantly lower in older recipients (P = 0.025) and recipients with non-ambulatory status (P < 0.001). However, in contrast to non-ambulatory recipients who showed significant survival differences according to the recipient’s age (P = 0.004), ambulatory recipients showed comparable outcomes (P = 0.465). Conclusion Our results do not support use of age alone as an allocation criterion. Transplant candidate age in combination with some comorbidities such as non-ambulatory status may identify patients at a sufficiently elevated risk at which suitability of HTx should be reconsidered.

This study aimed to assess the utilization trends of pulmonary rehabilitation (PR) among lung cancer patients in Korea using the National Health Insurance Service (NHIS) database (2017 to 2021). PR was introduced and covered under the NHIS in 2016, primarily for chronic obstructive pulmonary disease, but recent evidence suggests its benefits for lung cancer patients. Data extraction was based on Korea Informative Classification of Diseases 8th revision codes C33 and C34, with PR prescriptions identified by codes MM440 and MM290.Descriptive statistical analysis was performed, and propensity score matching was used for comparison between PR and non-PR groups. Results showed a significant increase in PR utilization, with the number of patients receiving PR (MM440) rising from 1,002 in 2017 to 3,723 in 2021, indicating a 3.7-fold increase. However, the proportion of patients receiving PR remained low at 2.9% in 2021. Enhanced access to PR services and improved evaluation strategies are essential for optimizing patient outcomes.