The proportion of never-smokers with non-small cell lung cancer (NSCLC) is increasing, but that in Korea has not been well addressed in a large population. We aimed to evaluate the proportion and clinical features of never-smokers with NSCLC in a large single institution. We analyzed clinical data of 1860 consecutive patients who were newly diagnosed with NSCLC between June 2011 and December 2014. Of the 1860 NSCLC patients, 707 (38.0%) were never-smokers. The proportions of women (83.7% vs. 5.6%) and adenocarcinoma (89.8% vs. 44.9%) were higher among never-smokers than among ever-smokers. Significantly more never-smokers were diagnosed at a younger median age (65 vs. 68 years, P < 0.001) and earlier stage (stage I–II, 44.5% vs. 38.9%, P = 0.015) compared with ever-smokers. Epidermal growth factor receptor mutations (57.8% vs. 24.4%, P < 0.001) and anaplastic lymphoma kinase rearrangements (7.8% vs. 2.8%, P < 0.001) were more common in never-smokers, whereas Kirsten rat sarcoma viral oncogene homolog mutations (5.8% vs. 9.6%, P = 0.021) were less frequently encountered in never-smokers than in ever-smokers. Never-smokers showed longer survival after adjusting for the favorable effects of younger age, female sex, adenocarcinoma histology, better performance status, early stage disease, being asymptomatic at diagnosis, received antitumor treatment, and the presence of driver mutations (hazard ratio, 0.624; 95% confidence interval, 0.460–0.848; P = 0.003). More than one-third of the Korean patients with NSCLC were never-smokers. NSCLC in never-smokers had different clinical characteristics and major driver mutations and resulted in longer overall survival compared with NSCLC in ever-smokers.

Rationale: Differential diagnosis of pleural effusion is challenging in clinical practice. Objectives: We aimed to develop a machine learning model to classify the five common causes of pleural effusions. Methods: This retrospective study collected 49 features from clinical information, blood, and pleural fluid of adult patients who underwent diagnostic thoracentesis between October 2013 and December 2018. Pleural effusions were classified into the following five categories: transudative, malignant, parapneumonic, tuberculous, and other. The performance of five different classifiers, including multinomial logistic regression, support vector machine, random forest, extreme gradient boosting, and light gradient boosting machine (LGB), was evaluated in terms of accuracy and area under the receiver operating characteristic curve through fivefold cross-validation. Hybrid feature selection was applied to determine the most relevant features for classifying pleural effusion. Results: We analyzed 2,253 patients (training set, n = 1,459; validation set, n = 365; extra-validation set, n = 429) and found that the LGB model achieved the best performance in both validation and extra-validation sets. After feature selection, the accuracy of the LGB model with the selected 18 features was equivalent to that with all 49 features (mean ± standard deviation): 0.818 ± 0.012 and 0.777 ± 0.007 in the validation and extra-validation sets, respectively. The model’s mean area under the receiver operating characteristic curve was as high as 0.930 ± 0.042 and 0.916 ± 0.044 in the validation and extra-validation sets, respectively. In our model, pleural lactate dehydrogenase, protein, and adenosine deaminase levels were the most important factors for classifying pleural effusions. Conclusions: Our LGB model showed satisfactory performance for differential diagnosis of the common causes of pleural effusions. This model could provide clinicians with valuable information regarding the major differential diagnoses of pleural diseases.

Introduction: In the general population, short and long sleep durations have been associated with adverse health outcomes. However, this association remains unclear in patients with chronic kidney disease (CKD). We examined the relationship of sleep duration to mortality and health-related quality of life (HRQOL) in individuals with CKD. Methods: A total of 1,783 adults with CKD who participated in the 2007–2015 Korea National Health and Nutrition Examination Survey were analyzed. CKD was defined as an estimated glomerular filtration rate of <60 mL/min per 1.73 m². Participants were categorized into 3 groups according to self-reported sleep duration: 8 h (long sleepers). The outcome variables were all-cause mortality and HRQOL. HRQOL was assessed using the European Quality of Life-5 Dimensions (EQ-5D) index. Results: During a median of 6.4 years, 481 (27%) deaths occurred. In unadjusted Cox regression analysis, long sleepers with CKD had an increased risk of death (hazard ratio [HR], 1.62; 95% confidence interval [CI]: 1.26–2.09). This significant association remained after adjusting for age, sex, and BMI (HR, 1.36; 95% CI: 1.05–1.75); however, it was lost after adjusting for CKD stage, social and lifestyle factors, and presence of comorbidities (HR, 1.15; 95% CI: 0.89–1.49). Compared with 6- to 8-h sleepers with CKD, long sleepers with CKD had significantly worse HRQOL in multivariable linear regression models. The adjusted means of the EQ-5D index were 0.80 (95% CI: 0.77–0.82) for short sleepers, 0.81 (95% CI: 0.80–0.82) for 6- to 8-h sleepers, and 0.76 (95% CI: 0.73–0.79) for long sleepers (p = 0.01). Discussion/Conclusion: Long sleep duration is associated with poor HRQOL in Korean adults with CKD. The weak association between long sleep duration and mortality was attenuated after multivariable adjustment in this study.

Sleep disorders are common in critically ill patients. Unfortunately, sleep assessment is challenging in many intensive care units (ICUs). The Richards-Campbell Sleep Questionnaire (RCSQ) is a simple subjective tool that has been validated and used in many countries. This study aimed to evaluate the reliability of the Korean version of the RCSQ (K-RCSQ). This prospective, cross-sectional, observational study was conducted in the ICUs of two hospitals. In total, 52 consenting patients answered questionnaires regarding their previous night’s sleep (K-RCSQ) and the noise they experienced (range, 0–100). The K-RCSQ showed excellent internal consistency of 0.960 by Cronbach’s alpha. The mean total score of the K-RCSQ was 41.9±28.9 (range, 0–100). The mean perceived ICU noise score was 40.7±28.1 (range, 0–90). There was a significant linear correlation between noise score and average K-RCSQ score (r=–0.37, P<0.001). The K-RCSQ demonstrated excellent reliability (internal consistency). This simple tool may help assess sleep quality in critically ill patients and improve the quality of ICU care.

Current knowledge regarding the relationship between obstructive sleep apnea (OSA) and the risk of lung cancer is limited. This study aimed to evaluate associations between OSA and the incidence of lung cancer based on the Korean National Health Information Database. The study outcome was the incidence of newly diagnosed lung cancer, and a Cox proportional hazards model was used for analysis. A total of 181,070 adult patients newly diagnosed with OSA between 2011 and 2018 were matched with those without OSA by up to 1:5 propensity score matching based on age and sex. During follow-up over (mean ± standard deviation) 9.1 ± 2.0 years, 2614 incident cases of lung cancer were identified. The incidence rate was 39.51 per 100,000 person-years in the OSA group, and 24.93 per 100,000 person-years in the control group. After adjusting for income and the presence of comorbidities, the association remained significant (hazard ratio [HR] 1.95, 95% confidence interval [CI] 1.74–2.18, p-value < 0.001). The adjusted HR for incident lung cancer was 2.14 (95% CI 1.69–2.70) in female patients with OSA, and 1.90 (95% CI 1.67–2.16) in male patients with OSA. The risk of incident lung cancer increased with age, with a HR of 2.99 (95% CI 2.46–3.64) in those aged ≥ 65 years. This nationwide study showed an independent association between OSA and an increased risk of lung cancer in the Korean population.