1.Initial and peak serum levels of Krebs von den Lungen-6 for predicting the prognosis of patients with COVID-19
Geonui KIM ; Hyeonwoo KWON ; Sang Hyun RA ; Euijin CHANG ; Seongman BAE ; Jiwon JUNG ; Min Jae KIM ; Yong Pil CHONG ; Sang-Oh LEE ; Sang-Ho CHOI ; Yang Soo KIM ; Sung-Han KIM
The Korean Journal of Internal Medicine 2025;40(2):321-329
Background/Aims:
Krebs von den Lungen-6 (KL-6) is associated with prognosis in patients with COVID-19. However, there is limited data on the correlation between the prognosis of COVID-19 and varying KL-6 levels at different time points. We investigated the optimal cutoff values of the initial and peak serum KL-6 levels to predict mortality and evaluated their correlation with mortality.
Methods:
This retrospective cohort study collected data on serially collected serum KL-6 levels in patients hospitalized with COVID-19 between October 2020 and January 2022 at a single tertiary hospital in South Korea. The area under the receiver operating characteristic curve and Youden index were used to determine the cutoff points for the initial and peak KL-6 levels that best predicted 30-day mortality. The association between the initial and peak KL-6 values was assessed by univariate and multivariate logistic regression models.
Results:
A total of 349 patients were included in this study. The mean initial and peak KL-6 levels were significantly higher in the non-survivor group than in the survivor group. The initial and peak KL-6 values that best predicted 30-day mortality were 491.85 U/mL and 660.05 U/mL, respectively. An initial KL-6 level greater than 491.85 U/mL and a peak KL-6 level greater than 660.05 U/mL were significantly associated with 30-day mortality.
Conclusions
The initial and peak levels of KL-6 were significantly associated with 30-day mortality in hospitalized patients with COVID-19. These findings suggest that serially monitoring blood KL-6 levels could be a valuable prognostic indicator for COVID-19.
2.Fact sheet: nationwide trends in dietary intakes among Korean adults, 2013-2022
Hannah OH ; Garam JO ; Oh Yoen KIM ; Hyunjung LIM ; SuJin SONG ; Jeong-Hwa CHOI ; Jae Hyun BAE ; Eun-Sun JIN ; Rockli KIM ; Yujin LEE ; In-Kyung JEONG ; Min-Jeong SHIN ;
The Korean Journal of Internal Medicine 2025;40(3):427-437
Background/Aims:
Cardiovascular disease is the leading cause of death worldwide. This study aimed to investigate the recent nationwide trends in major dietary risk factors for dyslipidemia and atherosclerosis.
Methods:
We estimated age-standardized mean intakes of fresh fruits, fresh vegetables, whole grains, dietary fiber, and sugar-sweetened beverages (SSBs); and mean percentage of energy intake from protein, total fat, saturated fat, and polyunsaturated fat using nationally representative samples from the Korean National Health Examination and Nutrition Survey 2013–2022. To assess overall diet quality, we calculated mean Korean Healthy Eating Index (KHEI) (range 0–100, higher scores indicating greater diet quality).
Results:
In 2013–2022, there were overall decreasing trends in age-standardized mean KHEI score and intakes of fresh fruits and vegetables, whole grains, and dietary fiber; and overall increasing trends in mean intakes of SSBs, protein, and dietary fat among both male and female. The KHEI score increased in older adults aged ≥ 60 years, whereas it decreased among younger adults. Throughout the study period, younger adults tended to have lower intakes of fresh fruits, fresh vegetables, and whole grains; higher intakes of SSBs, protein, and dietary fat; and lower KHEI score. The mean KHEI score was lower in male (vs. female) and lower (vs. higher) income groups.
Conclusions
Our data suggest that, from 2013 to 2022, there was a trend toward an unhealthy diet in Korean adults. Our findings also suggest dietary inequalities among age, sex, and income groups, suggesting the need for more intense interventions targeting the vulnerable populations.
3.Korean Guidelines for Diagnosis and Management of Interstitial Lung Diseases: Connective Tissue Disease Associated Interstitial Lung Disease
Ju Hyun OH ; Jae Ha LEE ; Sung Jun CHUNG ; Young Seok LEE ; Tae-Hyeong KIM ; Tae-Jung KIM ; Joo Hun PARK ;
Tuberculosis and Respiratory Diseases 2025;88(2):247-263
Connective tissue disease (CTD), comprising a range of autoimmune disorders, is often accompanied by lung involvement, which can lead to life-threatening complications. The primary types of CTDs that manifest as interstitial lung disease (ILD) include rheumatoid arthritis, systemic sclerosis, Sjögren’s syndrome, mixed CTD, idiopathic inflammatory myopathies, and systemic lupus erythematosus. CTD-ILD presents a significant challenge in clinical diagnosis and management due to its heterogeneous nature and variable prognosis. Early diagnosis through clinical, serological, and radiographic assessments is crucial for distinguishing CTD-ILD from idiopathic forms and for implementing appropriate therapeutic strategies. Hence, we have reviewed the multiple clinical manifestations and diagnostic approaches for each type of CTD-ILD, acknowledging the diversity and complexity of the disease. The importance of a multidisciplinary approach in optimizing the management of CTD-ILD is emphasized by recent therapeutic advancements, which include immunosuppressive agents, antifibrotic therapies, and newer biological agents targeting specific pathways involved in the pathogenesis. Therapeutic strategies should be customized according to the type of CTD, the extent of lung involvement, and the presence of extrapulmonary manifestations. Additionally, we aimed to provide clinical guidance, including therapeutic recommendations, for the effective management of CTD-ILD, based on patient, intervention, comparison, outcome (PICO) analysis.
4.Better Chemotherapeutic Response of Small Cell Lung Cancer in Never Smokers than in Smokers
Ha-Young PARK ; Hyung-Joo OH ; Hwa Kyung PARK ; Joon-Young YOON ; Chang-Seok YOON ; Bo Gun KHO ; Tae-Ok KIM ; Hong-Joon SHIN ; Chul-Kyu PARK ; Yong-Soo KWON ; Yu-Il KIM ; Sung-Chul LIM ; Young-Chul KIM ; In-Jae OH
Tuberculosis and Respiratory Diseases 2025;88(2):334-341
Background:
Small cell lung cancer (SCLC) is called ‘smoker’s disease’ because it is strongly associated with smoking and most cases occur in smokers. However, it can also occur in never smokers. We investigated the clinical features of never smokers with SCLC and compared their treatment outcomes with those of smokers with SCLC.
Methods:
We retrospectively reviewed the clinical data of patients who had proven SCLC and had received chemotherapy at a single cancer center between July 2002 and April 2021.
Results:
Of 1,643 patients, 1,416 (86.2%) were enrolled in this study. A total of 162 (11.4%) and 1,254 (88.6%) patients were never smokers and smokers, respectively. There were more female never smokers than smokers (n=130; 80.2% vs. 79, 6.3%, p=0.000), and the incidence of ischemic heart disease was lower among never smokers than among smokers (4/1,416, [2.5%] vs. 83/1,416 [6.6%], p=0.036). Never smokers showed less symptoms at diagnosis than smokers (80.9% vs. 87.2%, p=0.037); however, they showed more toxicity after first-line treatment (61.7% vs. 47.8%, p=0.001). The objective response rate (ORR) was significantly higher in never smokers (74.1% vs. 59.6%, p=0.000). In the multivariate analysis, never smoking and second-line treatment were associated with a better ORR. However, progression-free survival and overall survival were not significantly different between never smokers and smokers.
Conclusion
In conclusion, never smokers accounted for 11.4% of patients with SCLC. They had distinguishing clinical characteristics and showed better chemotherapeutic responses than smokers.
5.Clinical Profiles of Multidrug-Resistant and Rifampicin-Monoresistant Tuberculosis in Korea, 2018–2021: A Nationwide Cross-Sectional Study
Jinsoo MIN ; Yousang KO ; Hyung Woo KIM ; Hyeon-Kyoung KOO ; Jee Youn OH ; Doosoo JEON ; Taehoon LEE ; Young-Chul KIM ; Sung Chul LIM ; Sung Soon LEE ; Jae Seuk PARK ; Ju Sang KIM
Tuberculosis and Respiratory Diseases 2025;88(1):159-169
Background:
This study aimed to identify the clinical characteristics of multidrug-resistant/ rifampicin-resistant tuberculosis (MDR/RR-TB) in the Republic of Korea.
Methods:
Data of notified people with tuberculosis between July 2018 and December 2021 were retrieved from the Korea Tuberculosis Cohort database. MDR/RR-TB was further categorized according to isoniazid susceptibility as follows: multidrug-resistant tuberculosis (MDR-TB), rifampicin-monoresistant tuberculosis (RMR-TB), and RR-TB if susceptibility to isoniazid was unknown. Multivariable logistic regression analysis was conducted to identify the factors associated with MDR/RR-TB.
Results:
Between 2018 and 2021, the proportion of MDR/RR-TB cases among all TB cases and TB cases with known drug susceptibility test results was 2.1% (502/24,447). The proportions of MDR/RR-TB and MDR-TB cases among TB cases with known drug susceptibility test results were 3.3% (502/15,071) and 1.9% (292/15,071), respectively. Among all cases of rifampicin resistance, 31.7% (159/502) were RMR-TB and 10.2% (51/502) were RR-TB. Multivariable logistic regression analyses revealed that younger age, foreigners, and prior tuberculosis history were significantly associated with MDR/ RR-TB.
Conclusion
Rapid identification of rifampicin resistance targeting the high-risk populations, such as younger generations, foreign-born individuals, and previously treated patients are necessary for patient-centered care.
7.Factors influencing satisfaction with medical services in medically underserved populations: an analytical cross-sectional study at a free medical clinic in the Republic of Korea
Joo Hyun KIM ; Yeon Jeong HEO ; Jae Bok KWAK ; Samil PARK ; Curie AHN ; So Hee AHN ; Bumjo OH ; Jung Sik LEE ; Jun Hyun LEE ; Ho Young LEE
Osong Public Health and Research Perspectives 2025;16(2):181-191
Objectives:
This study aimed to explore factors influencing satisfaction with medical services among medically underserved populations at the free medical clinic, providing data to improve free medical services for these populations.
Methods:
We employed a descriptive correlational study design involving 112 individuals (aged 19 years and older) from medically underserved populations who visited the clinic. Data were collected through face-to-face surveys from September to October 2023, and statistical analyses (t-tests, analysis of variance, Pearson correlation, and hierarchical multiple regression) were used to identify key predictors of satisfaction.
Results:
Perceived support from healthcare providers emerged as the strongest predictor ofsatisfaction with medical services, demonstrating a significant positive association. While socialsupport was positively correlated with perceived support from healthcare providers, it did not independently predict satisfaction.
Conclusion
These findings underscore the importance of healthcare provider and social supportin increasing satisfaction with medical services among medically underserved populations.Developing tailored healthcare programs and specialized healthcare provider training are essential strategies to improve healthcare access and outcomes for these vulnerable groups.
8.Machine Learning Prediction of Attachment Type From Bio-Psychological Factors in Patients With Depression
Yoon Jae CHO ; Jin Sun RYU ; Jeong-Ho SEOK ; Eunjoo KIM ; Jooyoung OH ; Byung-Hoon KIM
Psychiatry Investigation 2025;22(4):412-423
Objective:
Adult attachment style is linked to how an individual responds to threats or stress and is known to be related to the onset of psychiatric symptoms such as depression. However, as the current assessment of attachment type mainly relies on self-report questionnaires and can be prone to bias, there is a need to incorporate physiological factors along with psychological symptoms and history in this process. We aimed to predict the measurement of two important types of adult attachment with heart rate variability (HRV), early life stress experience, and subjective psychiatric symptoms.
Methods:
Five hundred eighty-two subjects with depressive disorder were recruited retrospectively from January 2015 to June 2021. The experience of early life stress and psychiatric symptoms were collected, and HRV measures were obtained as input for an ensembled Voting Regressor model of machine learning-based regression models, including linear regression, ElasticNet, Support Vector Machine (SVM), Random Forest, and Extreme Gradient Boosting (XGBoost).
Results:
Model performances evaluated with R-squared score averaged across 30 seeds were 0.377 and 0.188 for anxious- and avoidant-attachment, respectively. Mean absolute error averaged to 13.251 and 12.083, respectively. Shapley value importance analysis indicated that for both attachment types, the most important feature was the trait-anxiety, followed by emotional abuse, state-anxiety or self-reported depressive symptoms, and fear or helplessness felt in the moment of an early life stressor.
Conclusion
Our results provide the evidence base that may be utilized in clinical settings to predict the degree of attachment type using bio-psychological factors.
9.Virtual Reality-Based Cognitive Behavior Therapy for Major Depressive Disorder: An Alternative to Pharmacotherapy for Reducing Suicidality
Miwoo LEE ; Sooah JANG ; Hyun Kyung SHIN ; Sun-Woo CHOI ; Hyung Taek KIM ; Jihee OH ; Ji Hye KWON ; Youngjun CHOI ; Suzi KANG ; In-Seong BACK ; Jae-Ki KIM ; San LEE ; Jeong-Ho SEOK
Yonsei Medical Journal 2025;66(1):25-36
Purpose:
Cognitive behavioral therapy (CBT) has long been recognized as an effective treatment for depression and suicidality.Virtual reality (VR) technology is widely used for cognitive training for conditions such as anxiety disorder and post-traumatic stress disorder, but little research has considered VR-based CBT for depressive symptoms and suicidality. We tested the effectiveness and safety of a VR-based CBT program for depressive disorders.
Materials and Methods:
We recruited 57 participants from May 2022 through February 2023 using online advertisements. This multi-center, assessor-blinded, randomized, controlled exploratory trial used two groups: VR treatment group and treat as usual (TAU) group. VR treatment group received a VR mental health training/education program. TAU group received standard pharmacotherapy. Assessments were conducted at baseline, immediately after the 6-week treatment period, and 4 weeks after the end of the treatment period in each group.
Results:
Depression scores decreased significantly over time in both VR treatment and TAU groups, with no differences between the two groups. The suicidality score decreased significantly only in VR group. No group differences were found in the remission or response rate for depression, perceived stress, or clinical severity. No adverse events or motion sickness occurred during the VR treatment program.
Conclusion
VR CBT treatment for major depressive disorder has the potential to be equivalent to the gold-standard pharmacotherapy in reducing depressive symptoms, suicidality, and related clinical symptoms, with no difference in improvement found in this study. Thus, VR-based CBT might be an effective alternative to pharmacotherapy for depressive disorders.
10.Feasibility of a Machine Learning Classifier for Predicting Post-Induction Hypotension in Non-Cardiac Surgery
Insun PARK ; Jae Hyon PARK ; Young Hyun KOO ; Chang-Hoon KOO ; Bon-Wook KOO ; Jin-Hee KIM ; Ah-Young OH
Yonsei Medical Journal 2025;66(3):160-171
Purpose:
To develop a machine learning (ML) classifier for predicting post-induction hypotension (PIH) in non-cardiac surgeries.
Materials and Methods:
Preoperative data and early vital signs were obtained from 3669 cases in the VitalDB database, an opensource registry. PIH was defined as sustained mean arterial pressure (MAP) <65 mm Hg within 20 minutes since induction or from induction to incision. Six different ML algorithms were used to create binary classifiers to predict PIH. The primary outcome was the area under the receiver operating characteristic curve (AUROC) of ML classifiers.
Results:
A total of 2321 (63.3%) cases exhibited PIH. Among ML classifiers, the random forest regressor and extremely gradient boosting regressor showed the highest AUROC, both recording a value of 0.772. Excluding these models, the light gradient boosting machine regressor showed the second highest AUROC [0.769; 95% confidence interval (CI), 0.767–0.771], followed by the gradient boosting regressor (0.768; 95% CI, 0.763–0.772), AdaBoost regressor (0.752; 95% CI, 0.743–0.761), and automatic relevance determination regression (0.685; 95% CI, 0.669–0.701). The top three important features were mean diastolic blood pressure (DBP), minimum MAP, and minimum DBP from anesthetic induction to tracheal intubation, and these features were lower in cases with PIH (all p<0.001).
Conclusion
ML classifiers exhibited moderate performance in predicting PIH, and have the potential for real-time prediction.

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