Background: Lung cancer has a high incidence and mortality worldwide, and smoking, age, sex, and body mass index are known risk factors. Using a health examination cohort, we constructed a comprehensive lung cancer risk-prediction model. Methods: This study comprised 308,804 adults aged 20 years and older who underwent health examinations at one general hospital in Korea, from 2011 to 2018. We developed a lung cancer risk prediction model using a multivariate Cox proportional hazards regression analysis for lung cancer risk factors and estimated the hazard ratios and coefficients. The model evaluation included discrimination and calibration assessments. Results: Among the 308,804 adults in the study cohort, there were 338 (0.11%) patients lung cancer, with 215 males (0.07% of 169,420 males) and 123 females (0.04% of 139,384 females). The prevalence of lung cancer was higher in males and females aged over 60 years. Age, sex, body mass index, and smoking behavior were identified as risk factors for lung cancer prevalence in this model through multivariate Cox proportional hazards analysis. The C-statistic of the development cohort was 0.785 (0.749, 0.821) and that of the validation cohort was 0.823 (0.769, 0.878). Conclusion Our lung cancer risk prediction model showed statistical significance, similar to previous prediction models, among variables that included young age, female sex, and body mass index. Future improvements should focus on population-wide applicability and associated health examination policies.

Background: Lung cancer has a high incidence and mortality worldwide, and smoking, age, sex, and body mass index are known risk factors. Using a health examination cohort, we constructed a comprehensive lung cancer risk-prediction model. Methods: This study comprised 308,804 adults aged 20 years and older who underwent health examinations at one general hospital in Korea, from 2011 to 2018. We developed a lung cancer risk prediction model using a multivariate Cox proportional hazards regression analysis for lung cancer risk factors and estimated the hazard ratios and coefficients. The model evaluation included discrimination and calibration assessments. Results: Among the 308,804 adults in the study cohort, there were 338 (0.11%) patients lung cancer, with 215 males (0.07% of 169,420 males) and 123 females (0.04% of 139,384 females). The prevalence of lung cancer was higher in males and females aged over 60 years. Age, sex, body mass index, and smoking behavior were identified as risk factors for lung cancer prevalence in this model through multivariate Cox proportional hazards analysis. The C-statistic of the development cohort was 0.785 (0.749, 0.821) and that of the validation cohort was 0.823 (0.769, 0.878). Conclusion Our lung cancer risk prediction model showed statistical significance, similar to previous prediction models, among variables that included young age, female sex, and body mass index. Future improvements should focus on population-wide applicability and associated health examination policies.

Background: Lung cancer has a high incidence and mortality worldwide, and smoking, age, sex, and body mass index are known risk factors. Using a health examination cohort, we constructed a comprehensive lung cancer risk-prediction model. Methods: This study comprised 308,804 adults aged 20 years and older who underwent health examinations at one general hospital in Korea, from 2011 to 2018. We developed a lung cancer risk prediction model using a multivariate Cox proportional hazards regression analysis for lung cancer risk factors and estimated the hazard ratios and coefficients. The model evaluation included discrimination and calibration assessments. Results: Among the 308,804 adults in the study cohort, there were 338 (0.11%) patients lung cancer, with 215 males (0.07% of 169,420 males) and 123 females (0.04% of 139,384 females). The prevalence of lung cancer was higher in males and females aged over 60 years. Age, sex, body mass index, and smoking behavior were identified as risk factors for lung cancer prevalence in this model through multivariate Cox proportional hazards analysis. The C-statistic of the development cohort was 0.785 (0.749, 0.821) and that of the validation cohort was 0.823 (0.769, 0.878). Conclusion Our lung cancer risk prediction model showed statistical significance, similar to previous prediction models, among variables that included young age, female sex, and body mass index. Future improvements should focus on population-wide applicability and associated health examination policies.

Background: Lung cancer has a high incidence and mortality worldwide, and smoking, age, sex, and body mass index are known risk factors. Using a health examination cohort, we constructed a comprehensive lung cancer risk-prediction model. Methods: This study comprised 308,804 adults aged 20 years and older who underwent health examinations at one general hospital in Korea, from 2011 to 2018. We developed a lung cancer risk prediction model using a multivariate Cox proportional hazards regression analysis for lung cancer risk factors and estimated the hazard ratios and coefficients. The model evaluation included discrimination and calibration assessments. Results: Among the 308,804 adults in the study cohort, there were 338 (0.11%) patients lung cancer, with 215 males (0.07% of 169,420 males) and 123 females (0.04% of 139,384 females). The prevalence of lung cancer was higher in males and females aged over 60 years. Age, sex, body mass index, and smoking behavior were identified as risk factors for lung cancer prevalence in this model through multivariate Cox proportional hazards analysis. The C-statistic of the development cohort was 0.785 (0.749, 0.821) and that of the validation cohort was 0.823 (0.769, 0.878). Conclusion Our lung cancer risk prediction model showed statistical significance, similar to previous prediction models, among variables that included young age, female sex, and body mass index. Future improvements should focus on population-wide applicability and associated health examination policies.

BACKGROUND: Core body temperature (TC) can decrease during general anesthesia. Particularly in elderly patients, more aggressive strategies to prevent intraoperative hypothermia may be required. Here, we investigated the effect of a heated humidifier on intraoperative TC decrease in the elderly. METHODS: Twenty-four elderly patients were randomly assigned into two groups: those who used a heated humidifier (group H) and those who used a conventional ventilator circuit with a heat moisture exchanger (group C). TC was measured continuously at the esophagus at several time-points during surgery. RESULTS: In group C, TC significantly decreased 90 minutes after skin incision (P < 0.001), while significant differences were not noted in group H during surgery. Comparing the two groups, TC decreased more in group C than in group H at 60, 90, 120, and 150 minutes after skin incision (group C vs. group H: -0.6℃ vs. -0.3℃, P = 0.025; -0.7℃ vs. -0.4℃, P = 0.012; -0.9℃ vs. -0.4℃, P = 0.006; and -1.0℃ vs. -0.5℃, P = 0.013, respectively). There were no significant differences between the two groups for any other parameters. CONCLUSIONS: A heated humidifier is more effective in preventing intraoperative TC decrease in elderly patients than a heat moisture exchanger. However, further studies with a larger population are required to substantiate its clinical use.
Aged* ; Anesthesia, Closed-Circuit ; Anesthesia, General ; Body Temperature* ; Esophagus ; Heating ; Hot Temperature* ; Humans ; Humidity ; Hypothermia ; Observational Study* ; Prospective Studies* ; Skin ; Ventilators, Mechanical

Background: Data on severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) delta variant virulence are insufficient. We retrospectively compared the clinical features of adult coronavirus disease 2019 (COVID-19) patients without risk factors for severe COVID-19 who entered residential treatment centers (RTCs) before and after the delta variant outbreak. Methods: We collected medical information from two RTCs in South Korea. On the basis of nationwide delta variant surveillance, we divided the patients into two groups: 1) the delta-minor group (diagnosed from December 2020–June 2021, detection rate < 10%) and 2) the delta-dominant group (diagnosed during August 2021, detection rate > 90%). After propensity-score matching, the incidences of pneumonia, hospital transfer and need for supplemental oxygen were compared between the groups. In addition, risk factors for hospital transfer were analysed. Results: A total of 1,915 patients were included. The incidence of pneumonia (14.6% vs.9.2%, P = 0.009), all-cause hospital transfer (10.4% vs. 6.3%, P = 0.020) and COVID-19-related hospital transfer (7.5% vs. 4.8%, P = 0.081) were higher in the delta-dominant group than those in the delta-minor group. In the multivariate analysis, the delta-dominant group was an independent risk factor for all-cause (adjusted odds ratio [aOR], 1.91; 95% confidence interval [CI], 1.16–3.13; P = 0.011) and COVID-19-related hospital transfer (aOR, 1.86; 95% CI, 1.04–3.32; P = 0.036). Conclusion Hospitalization rates were increased in the adult COVID-19 patients during the delta variant nationwide outbreak. Our results showed that the delta variant may be more virulent than previous lineages.