Purpose: This study aimed to validate pivotal pre-test probability (PTP)-coronary artery disease (CAD) models (CAD consortium model and IJC-CAD model). Materials and Methods: Traditional PTP models-CAD consortium models: two traditional PTP models were used under the CAD consortium framework, namely CAD1 and CAD2. Machine learning (ML)-based PTP models: two ML-based PTP models were derived from CAD1 and CAD2, and used to enhance predictive capabilities [ML-CAD2 and ML-IJC (IJC-CAD)]. The primary endpoint was obstructive CAD. The performance evaluation of these PTP models was conducted using receiver-operating characteristic analysis. Results: The study included 238 participants, among whom 157 individuals (65.9% of the total sample) had CAD. The IJC-CAD model demonstrated the highest performance with an area under the curve (AUC) of 0.860 [95% confidence interval (CI): 0.812– 0.909]. Following this, the ML-CAD2 model exhibited an AUC of 0.814 (95% CI: 0.758–0.870), CAD1 showed an AUC of 0.767 (95% CI: 0.705–0.830), and CAD2 had an AUC of 0.785 (95% CI: 0.726–0.845). Each of the PTP models was adjusted to have a CAD score cutoff that classified cases with a sensitivity of over 95%. The respective cutoff values were as follows: CAD1 and CAD2 >12, MLCAD2 >0.380, and IJC-CAD >0.367. All PTP models achieved a CAD sensitivity of over 95%. Similar to the AUC performance, the accuracy of the PTP models was highest for IJC-CAD, reaching 80.3%. The accuracy of ML-CAD2 was 77.7%, while that for CAD1 and CAD2 was 74.8% and 75.2%, respectively. Conclusion ML-CAD2 and IJC-CAD showed superior performance compared to traditional existing models (CAD1 and CAD2)

Purpose: Smoking may have a protective role in developing ulcerative colitis (UC) but have the opposite effect on Crohn’s disease (CD). This study aimed to determine the risk of developing inflammatory bowel disease (IBD) according to smoking status and onset age of smoking. Materials and Methods: We collected data on the smoking experiences of participants aged 20–39 years who underwent biannual examinations provided by the Korean National Health Screening Program from 2009 to 2012. IBD diagnosis was identified using the National Health Insurance Service. The risk of IBD according to smoking status and onset age of smoking was analyzed after adjusting for major clinical variables. Results: During a median 10.59-year follow-up, the risk of UC in ex-smokers was significantly higher than that in non-smokers, and the earlier ex-smokers started smoking, the higher risk of UC [ex-smokers whose onset age of smoking was <20 years, adjusted hazard ratio (aHR) 1.928, 95% confidence interval (CI)=1.649–2.255; 20–24 years, aHR 1.728, 95% CI=1.541–1.939; 25–29 years, aHR 1.676, 95% CI=1.489–1.887; ≥30 years, aHR 1.226, 95% CI=1.010–1.486]. The risk of UC was significantly lower in current smokers whose onset age of smoking was 25–29 years than in non-smokers (aHR 0.825, 95% CI=0.709–0.959). The risk of CD did not differ according to smoking status and onset age of smoking. Conclusion Ex-smokers who started smoking at a young age have a high risk of UC, even after adjusting for the smoking amount.

Hospital-acquired pneumonia (HAP) and ventilator-associated pneumonia (VAP) are correlated with high morbidity and mortality rates. Guidelines that consider local epidemiologic data are fundamental for identifying optimal treatment strategies. However, Korea has no HAP/VAP guidelines. This study was conducted by a committee of nine experts from the Korean Academy of Tuberculosis and Respiratory Diseases Respiratory Infection Study Group using the results of Korean HAP/VAP epidemiologic studies. Eleven key questions for HAP/VAP diagnosis and treatment were addressed. The Convergence of Opinion on Suggestions and Evidence (CORE) process was used to derive suggestions, and evidence levels and recommendation grades were in accordance with the Grading of Recommendations Assessment Development and Evaluation (GRADE) methodology. Suggestions were made for the 11 key questions pertinent to diagnosis, biomarkers, antibiotics, and treatment strategies for adult patients with HAP/VAP. Using the CORE process and GRADE methodology, the committee generated a series of recommendations for HAP/VAP diagnosis and treatment in the Korean context.

Background: Kelch-like ECH-associated protein 1 (KEAP1)–nuclear factor erythroid- 2-related factor 2 (NRF2) pathway is a major regulator protecting cells from oxidative and metabolic stress. Studies have revealed that this pathway is involved in mediating resistance to cytotoxic chemotherapy and immunotherapy; however, its implications in oncogene-addicted tumors are largely unknown. This study aimed to elucidate whether this pathway could be a potential therapeutic target for epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer. Methods: We measured the baseline expression of NRF2 using EGFR-mutant parental cells and acquired gefitinib resistant cells. We investigated whether NRF2 inhibition affected cell death in vitro and tumor growth in vivo using a xenograft mouse model, and compared the transcriptional changes before and after NRF2 inhibition. Results: Baseline NRF2 expression was enhanced in PC9 and PC9 with gefitinib resistance (PC9/GR) cells than in other cell lines, with a more prominent expression in PC9/ GR. The NRF2 inhibitor induced NRF2 downregulation and cell death in a dose-dependent manner. Cotreatment with an NRF2 inhibitor enhanced osimertinib-induced cell death in vitro, and potentiated tumor growth inhibition in a PC9/GR xenograft model. Finally, RNA sequencing revealed that NRF2 inhibition resulted in the altered expression of multiple genes involved in various signaling pathways. Conclusion We identified that NRF2 inhibition enhanced cell death and inhibited tumor growth in tyrosine kinase inhibitor (TKI)-resistant lung cancer with EGFR-mutation. Thus, NRF2 modulation may be a novel therapeutic strategy to overcome the resistance to EGFR-TKIs.

Purpose: This study aimed to validate pivotal pre-test probability (PTP)-coronary artery disease (CAD) models (CAD consortium model and IJC-CAD model). Materials and Methods: Traditional PTP models-CAD consortium models: two traditional PTP models were used under the CAD consortium framework, namely CAD1 and CAD2. Machine learning (ML)-based PTP models: two ML-based PTP models were derived from CAD1 and CAD2, and used to enhance predictive capabilities [ML-CAD2 and ML-IJC (IJC-CAD)]. The primary endpoint was obstructive CAD. The performance evaluation of these PTP models was conducted using receiver-operating characteristic analysis. Results: The study included 238 participants, among whom 157 individuals (65.9% of the total sample) had CAD. The IJC-CAD model demonstrated the highest performance with an area under the curve (AUC) of 0.860 [95% confidence interval (CI): 0.812– 0.909]. Following this, the ML-CAD2 model exhibited an AUC of 0.814 (95% CI: 0.758–0.870), CAD1 showed an AUC of 0.767 (95% CI: 0.705–0.830), and CAD2 had an AUC of 0.785 (95% CI: 0.726–0.845). Each of the PTP models was adjusted to have a CAD score cutoff that classified cases with a sensitivity of over 95%. The respective cutoff values were as follows: CAD1 and CAD2 >12, MLCAD2 >0.380, and IJC-CAD >0.367. All PTP models achieved a CAD sensitivity of over 95%. Similar to the AUC performance, the accuracy of the PTP models was highest for IJC-CAD, reaching 80.3%. The accuracy of ML-CAD2 was 77.7%, while that for CAD1 and CAD2 was 74.8% and 75.2%, respectively. Conclusion ML-CAD2 and IJC-CAD showed superior performance compared to traditional existing models (CAD1 and CAD2)

Purpose: Smoking may have a protective role in developing ulcerative colitis (UC) but have the opposite effect on Crohn’s disease (CD). This study aimed to determine the risk of developing inflammatory bowel disease (IBD) according to smoking status and onset age of smoking. Materials and Methods: We collected data on the smoking experiences of participants aged 20–39 years who underwent biannual examinations provided by the Korean National Health Screening Program from 2009 to 2012. IBD diagnosis was identified using the National Health Insurance Service. The risk of IBD according to smoking status and onset age of smoking was analyzed after adjusting for major clinical variables. Results: During a median 10.59-year follow-up, the risk of UC in ex-smokers was significantly higher than that in non-smokers, and the earlier ex-smokers started smoking, the higher risk of UC [ex-smokers whose onset age of smoking was <20 years, adjusted hazard ratio (aHR) 1.928, 95% confidence interval (CI)=1.649–2.255; 20–24 years, aHR 1.728, 95% CI=1.541–1.939; 25–29 years, aHR 1.676, 95% CI=1.489–1.887; ≥30 years, aHR 1.226, 95% CI=1.010–1.486]. The risk of UC was significantly lower in current smokers whose onset age of smoking was 25–29 years than in non-smokers (aHR 0.825, 95% CI=0.709–0.959). The risk of CD did not differ according to smoking status and onset age of smoking. Conclusion Ex-smokers who started smoking at a young age have a high risk of UC, even after adjusting for the smoking amount.

Background and Objectives: Evidence remains limited on the real-world prescription of very low-dose oral anticoagulation among frail patients with atrial fibrillation (AF). We described the practice patterns, effectiveness, and safety of very low-dose edoxaban (15 mg once daily). Methods: Patients with AF prescribed edoxaban 15 mg once daily in 2 tertiary hospitals between 2016 and September 2022 were included. Baseline clinical characteristics and clinical outcomes of interest were thromboembolic and bleeding events. Results: A total of 674 patients were included (mean age 78.3±9.1, 49.7% aged ≥80 years, 49.3% women, median follow-up 1.0±1.2 years). Mean CHA 2 DS 2 -VASc score was 3.9±1.6, and the modified HAS-BLED score was 2.0±1.1. Between 2016 and 2022, the number of very lowdose edoxaban prescriptions increased. The main reasons for the prescription of very lowdose were low body weight (55.5% below 60 kg), anaemia (62.8%), chronic kidney disease (40.2%), active cancer (15.3%), concomitant anti-platelet use (26.7%), and prior major bleeding (19.7%). During a median follow-up duration of 8 (interquartile range 3–16) months, overall thromboembolic and bleeding events occurred in 16 (2.3%) and 88 (13.1%) patients, respectively. Compared to the expected event rates on the established risk scoring systems, patients receiving very low-dose edoxaban demonstrated a 61% reduction in ischemic stroke, a 68% reduction of ischemic stroke/transient ischemic attack/systemic embolism, whereas a 49% increase in major bleeding. Conclusions The prescription of very low-dose edoxaban was increased over time, attributable to various clinical factors. The use of very low-dose edoxaban reduced the expected risk of thromboembolic events.

Background: Sleep disorders and insomnia are prevalent worldwide, with negative health outcomes. The Pittsburgh Sleep Quality Index (PSQI) is a widely used self-report assessment tool for evaluating sleep quality, comprising seven subdomains. The Korean version of the PSQI (PSQI-K) has been tested for reliability and validity in small sample sizes but lacks large-scale validation using objective measures. Methods: This study was conducted with 268 Korean adults attending health check programs. Participants completed the PSQI-K questionnaire and wore Fitbit devices (Fitbit Inc., USA) to ascertain sleep parameters. Reliability was analyzed using the Cronbach’s α coefficient, and construct validity was determined through factor analysis. Criteria validity was assessed by correlating their index scores with Fitbit sleep parameters. We identified the optimal cutoff for detecting sleep disorders. Results: The Cronbach’s α coefficient was 0.61, indicating adequate internal consistency. Factor analysis revealed three factors, explaining 48.2% of sleep quality variance. The index scores were negatively correlated with Fitbit sleep efficiency, total sleep time, and number of awakenings (P<0.05). The optimal cutoff point for identifying sleep disorder groups was ≥6. Conclusion The PSQI-K demonstrated good reliability and validity when correlated with Fitbit sleep parameters, offering a practical screening tool for identifying sleep disorders among Korean adults. Cutoff scores can help identify patients for sleep interventions. However, further large-scale studies are required to validate these findings.

Background/Aims: Hepatocellular carcinoma (HCC) exhibits high de novo recurrence rates post-resection. Current post-surgery recurrence prediction methods are limited, emphasizing the need for reliable biomarkers to assess recurrence risk. We aimed to develop methylation-based markers for classifying HCC patients and predicting their risk of de novo recurrence post-surgery. Methods: In this retrospective cohort study, we analyzed data from HCC patients who underwent surgical resection in Korea, excluding those with recurrence within one year post-surgery. Using the Infinium Methylation EPIC array on 140 samples in the discovery cohort, we classified patients into low- and high-risk groups based on methylation profiles. Distinctive markers were identified through random forest analysis. These markers were validated in the cancer genome atlas (n=217), Validation cohort 1 (n=63) and experimental Validation using a methylation-sensitive high-resolution melting (MS-HRM) assay in Validation cohort 1 and Validation cohort 2 (n=63). Results: The low-risk recurrence group (methylation group 1; MG1) showed a methylation average of 0.73 (95% confidence interval [CI] 0.69–0.77) with a 23.5% recurrence rate, while the high-risk group (MG2) had an average of 0.17 (95% CI 0.14–0.20) with a 44.1% recurrence rate (P<0.03). Validation confirmed the applicability of methylation markers across diverse populations, showing high accuracy in predicting the probability of HCC recurrence risk (area under the curve 96.8%). The MS-HRM assay confirmed its effectiveness in predicting de novo recurrence with 95.5% sensitivity, 89.7% specificity, and 92.2% accuracy. Conclusions Methylation markers effectively classified HCC patients by de novo recurrence risk, enhancing prediction accuracy and potentially offering personalized management strategies.

This study compares biomarker levels among environmentally vulnerable residents in Korea, the general Korean population, and Asians in the United States. We selected 953 exposed residents and 204 controls from the Forensic Research via Omics Markers in Environmental Health Vulnerable Areas (FROM) study (2021-2023), 4,239 participants from the fourth Korean National Environmental Health Survey (2018-2020), and 996 Asians from the U.S. National Health and Nutrition Examination Survey (2017-March 2020). The analyzed biomarkers included blood and urinary metals, urinary metabolites of polycyclic aromatic hydrocarbons, nicotine, volatile organic compounds, and serum perfluorocarbon metabolites. The highest median biomarker levels varied by pollution source among older adults. In refineries, blood lead and cadmium (Cd), as well as urinary Cd and 2-hydroxyfluorene, were highest. Abandoned metal mines exhibited the highest blood and urinary mercury, urinary Cd, total arsenic (As), 2-naphthol, and cotinine levels. Coal-fired power plants showed the highest urinary 1- hydroxyphenanthrene levels, while cement factories had the highest urinary As3+ levels. Sprawls demonstrated the highest urinary monomethylarsonic acid, 1-hydroxypyrene, and phenylglyoxylic acid levels, and industrial areas recorded the highest levels of trans, trans-muconic acid, benzylmercapturic acid, and 2-methylhippuric acid. In general, biomarker levels were higher among exposed residents in the FROM study than in the general population; however, urinary 2-hydroxyfluorene and As5+ levels did not differ significantly. Exposure to pollution sources in environmentally vulnerable areas may elevate biomarker levels in residents.