Background and Objectives: Clinical characteristics and outcomes in acute heart failure (AHF) vary by phenotype. We assessed phenotype-specific features, treatment patterns, and outcomes in a nationwide Korean cohort. Methods: The Korean Heart Failure III registry prospectively enrolled 7,351 AHF admissions at 47 hospitals. Among 6,777 patients with available left ventricular ejection fraction (EF), phenotypes were defined as heart failure with reduced EF (HFrEF, ≤40%), mildly reduced EF (HFmrEF,41–49%), or preserved EF (HFpEF, ≥50%). The primary endpoint was a 12-month composite of all-cause death or heart transplantation, evaluated from index admission and, among hospital survivors, from discharge. We used inverse probability weighting (multinomial generalized boosted models with stabilized, trimmed weights) and weighted Cox proportional-hazards models to estimate hazard ratios (HRs). Results: Phenotype distribution was 58.9% HFrEF, 13.6% HFmrEF, and 27.5% HFpEF. Crude 12-month composite rates from index admission were 13.4% (HFrEF), 12.7% (HFmrEF), and 16.8% (HFpEF). After weighting, from index admission, HFmrEF (HR, 0.892; 95% confidence interval [CI], 0.731–1.088) and HFpEF (HR, 1.101; 95% CI, 0.939–1.291) did not differ from HFrEF; from discharge, HFpEF had modestly higher risk (HR, 1.207; 95% CI, 1.008–1.445) whereas HFmrEF did not (HR, 1.039; 95% CI, 0.844–1.279). Hyponatremia and chronic kidney disease were consistent adverse markers, while angiotensin-converting enzyme inhibitor/ angiotensin II receptor blocker use at discharge was protective. Conclusions Across the EF spectrum, phenotypes showed distinct profiles and risk. Postdischarge risk was modestly higher in HFpEF, supporting phenotype-tailored care and systematic discharge optimization in Korean patients with AHF.

Purpose: There have been efforts to find alternative samples other than standard samples of tissue or plasma for mutational analyses for lung cancer patients. However, no other sample or technique has replaced the mutational analyses using standard samples. In this prospective study, we assessed a novel bronchoscopy method, named as targeted washing technique, for detecting the epidermal growth factor receptor (EGFR) mutation. Materials and Methods: A 3.0-mm ultrathin bronchoscope was precisely navigated to the target lung lesion with the assistance of virtual bronchoscopic navigation and fluoroscopy. Once the bronchoscope is placed in front of target lung lesion, 0.9% normal saline was instilled for targeted washing. EGFR testing using targeted washing fluid (TWF) was compared to standard methods using plasma or tumor tissue. Results: In 41 TWF samples, the T790M mutation was detected in tissue, plasma, and TWF samples at rates of 22.0%, 9.8%, and 29.3%, respectively. The overall EGFR T790M detection rate using tissue, plasma, or TWF samples was 36.6%, with TWF samples increasing the T790M mutation detection rate by up to 10%. The accuracy of T790M mutation detection using TWF sample was 82.9% compared with standard samples. Four patients were found to have the EGFR T790M mutation solely through EGFR testing using TWF, which repeated rebiopsies using either plasma or tissue finally confirmed to have the T790M mutation. Conclusion We demonstrated the clinical potential of targeted washing technique for molecular testing, which can be a good option to overcome spatial heterogeneity, low sensitivity of plasma sample or technical limitations in collecting tumor tissues.

Purpose: This study aimed to identify predictive factors affecting adolescents’ subjective happiness using data from the 2023 Korea Youth Risk Behavior Survey. A random forest model was applied to determine the strongest predictive factors, and its predictive performance was compared with traditional regression models. Methods: Responses from a total of 44,320 students from grades 7 to 12 were analyzed. Data pre-processing involved handling missing values and selecting variables to construct an optimal dataset. The random forest model was employed for prediction, and SHAP (Shapley Additive Explanations) analysis was used to assess variable importance. Results: The random forest model demonstrated a stable predictive performance, with an R2 of .37. Mental and physical health factors were found to significantly affect subjective happiness. Adolescents’ subjective happiness was most strongly influenced by perceived stress, perceived health, experiences of loneliness, generalized anxiety disorder, suicidal ideation, economic status, fatigue recovery from sleep, and academic performance. Conclusion This study highlights the utility of machine learning in identifying factors influencing adolescents’ subjective happiness, addressing limitations of traditional regression approaches. These findings underscore the need for multidimensional interventions to improve mental and physical health, reduce stress and loneliness, and provide integrated support from schools and communities to enhance adolescents’ subjective happiness.

Purpose: This study aimed to identify predictive factors affecting adolescents’ subjective happiness using data from the 2023 Korea Youth Risk Behavior Survey. A random forest model was applied to determine the strongest predictive factors, and its predictive performance was compared with traditional regression models. Methods: Responses from a total of 44,320 students from grades 7 to 12 were analyzed. Data pre-processing involved handling missing values and selecting variables to construct an optimal dataset. The random forest model was employed for prediction, and SHAP (Shapley Additive Explanations) analysis was used to assess variable importance. Results: The random forest model demonstrated a stable predictive performance, with an R2 of .37. Mental and physical health factors were found to significantly affect subjective happiness. Adolescents’ subjective happiness was most strongly influenced by perceived stress, perceived health, experiences of loneliness, generalized anxiety disorder, suicidal ideation, economic status, fatigue recovery from sleep, and academic performance. Conclusion This study highlights the utility of machine learning in identifying factors influencing adolescents’ subjective happiness, addressing limitations of traditional regression approaches. These findings underscore the need for multidimensional interventions to improve mental and physical health, reduce stress and loneliness, and provide integrated support from schools and communities to enhance adolescents’ subjective happiness.

Purpose: This study aimed to identify predictive factors affecting adolescents’ subjective happiness using data from the 2023 Korea Youth Risk Behavior Survey. A random forest model was applied to determine the strongest predictive factors, and its predictive performance was compared with traditional regression models. Methods: Responses from a total of 44,320 students from grades 7 to 12 were analyzed. Data pre-processing involved handling missing values and selecting variables to construct an optimal dataset. The random forest model was employed for prediction, and SHAP (Shapley Additive Explanations) analysis was used to assess variable importance. Results: The random forest model demonstrated a stable predictive performance, with an R2 of .37. Mental and physical health factors were found to significantly affect subjective happiness. Adolescents’ subjective happiness was most strongly influenced by perceived stress, perceived health, experiences of loneliness, generalized anxiety disorder, suicidal ideation, economic status, fatigue recovery from sleep, and academic performance. Conclusion This study highlights the utility of machine learning in identifying factors influencing adolescents’ subjective happiness, addressing limitations of traditional regression approaches. These findings underscore the need for multidimensional interventions to improve mental and physical health, reduce stress and loneliness, and provide integrated support from schools and communities to enhance adolescents’ subjective happiness.

Background: While Korea maintains a low prevalence of human immunodeficiency virus (HIV), the number of newly diagnosed cases has been steadily rising, reaching approximately 1,000 annually in recent years. The 2022 annual report from the Korea Disease Control and Prevention Agency revealed that women living with HIV (WLWH) constitute 6.4% of the total confirmed people living with the HIV population, totaling 1,219 individuals. Despite this, only a few studies have focused on WLWH in Korea. This study aims to analyze the epidemiological and clinical characteristics of WLWH in Korea. Materials and Methods: We retrospectively collected data by reviewing the medical records of all WLWH who visited 10 urban referral hospitals across Korea between January 2005 and May 2023. Results: A total of 443 WLWH were enrolled in this study. The predominant risk exposure was heterosexual contact, with 235 (53%) participants either married or cohabiting with a male partner at their initial clinic visit. Among the participants, 334 (77.7%) were Korean, 27 (6.1%) were Southeast Asian, and 19 (4.3%) were African. Antiretroviral therapy was initiated by 404 WLWH (91.2%). We observed 118 pregnancies in WLWH following their HIV diagnosis, resulting in 78 live births (66.1%), 18 induced abortions (15.2%), 10 pre-viable fetal losses (8.5%), and four stillbirths (3.4%). Over a cumulative follow-up duration of 3,202.1 years, the incidence rates of breast and cervical cancers were both 2.18 per 1,000 person-years. Additionally, the incidence rates of pelvic inflammatory disease, cervical intraepithelial neoplasm (above grade II), and osteoporosis were 4.67, 11.21, and 13.39 per 1,000 patient-years, respectively. Conclusion This is the first multicenter study to investigate the clinical and epidemiological characteristics of WLWH in Korea. The incidence and prevalence of diseases in women, including breast cancer, cervical cancer, and chronic comorbidities, are high in WLWH in Korea; therefore, further research and efforts are needed to manage these diseases.

Background: While Korea maintains a low prevalence of human immunodeficiency virus (HIV), the number of newly diagnosed cases has been steadily rising, reaching approximately 1,000 annually in recent years. The 2022 annual report from the Korea Disease Control and Prevention Agency revealed that women living with HIV (WLWH) constitute 6.4% of the total confirmed people living with the HIV population, totaling 1,219 individuals. Despite this, only a few studies have focused on WLWH in Korea. This study aims to analyze the epidemiological and clinical characteristics of WLWH in Korea. Materials and Methods: We retrospectively collected data by reviewing the medical records of all WLWH who visited 10 urban referral hospitals across Korea between January 2005 and May 2023. Results: A total of 443 WLWH were enrolled in this study. The predominant risk exposure was heterosexual contact, with 235 (53%) participants either married or cohabiting with a male partner at their initial clinic visit. Among the participants, 334 (77.7%) were Korean, 27 (6.1%) were Southeast Asian, and 19 (4.3%) were African. Antiretroviral therapy was initiated by 404 WLWH (91.2%). We observed 118 pregnancies in WLWH following their HIV diagnosis, resulting in 78 live births (66.1%), 18 induced abortions (15.2%), 10 pre-viable fetal losses (8.5%), and four stillbirths (3.4%). Over a cumulative follow-up duration of 3,202.1 years, the incidence rates of breast and cervical cancers were both 2.18 per 1,000 person-years. Additionally, the incidence rates of pelvic inflammatory disease, cervical intraepithelial neoplasm (above grade II), and osteoporosis were 4.67, 11.21, and 13.39 per 1,000 patient-years, respectively. Conclusion This is the first multicenter study to investigate the clinical and epidemiological characteristics of WLWH in Korea. The incidence and prevalence of diseases in women, including breast cancer, cervical cancer, and chronic comorbidities, are high in WLWH in Korea; therefore, further research and efforts are needed to manage these diseases.