Machine-learning model for predicting depression in second-hand smokers in cross-sectional data using the Korea National Health and Nutrition Examination Survey.

Objective: Depression among non-smokers at risk of second-hand smoke (SHS) exposure has been a neglected public health concern despite their vulnerability. The objective of this study was to develop high-performance machine-learning (ML) models for the prediction of depression in non-smokers and to identify important predictors of depression for second-hand smokers. Methods: ML algorithms were created using demographic and clinical data from the Korea National Health and Nutrition Examination Survey (KNHANES) participants from 2014, 2016, and 2018 (N = 11,463). The Patient Health Questionnaire was used to diagnose depression with a total score of 10 or higher. The final model was selected according to the area under the curve (AUC) or sensitivity. Shapley additive explanations (SHAP) were used to identify influential features. Results: The light gradient boosting machine (LGBM) with the highest positive predictive value (PPV; 0.646) was selected as the best model among the ML algorithms, whereas the support vector machine (SVM) had the highest AUC (0.900). The most influential factors identified using the LGBM were stress perception, followed by subjective health status and quality of life. Among the smoking-related features, urine cotinine levels were the most important, and no linear relationship existed between the smoking-related features and the values of SHAP. Conclusions: Compared with the previously developed ML models, our LGBM models achieved excellent and even superior performance in predicting depression among non-smokers at risk of SHS exposure, suggesting potential goals for depression-preventive interventions for non-smokers during public health crises.

Effect of the probiotic Weissella cibaria CMS1 on the immune response and the oral microbiome: a randomized, double-blind, placebo-controlled, parallel study.

The oral cavity connects the external environment and the respiratory and digestive systems, and the oral microbial ecosystem is complex and plays a crucial role in overall health and immune defense against external threats. Recently, the potential use of probiotics for disease prevention and treatment has gained attention. This study aimed to assess the effect of Weissella cibaria CMS1 (W. cibaria CMS1) consumption on the oral microbiome and immune function in healthy individuals through a 12-week clinical trial. This randomized, double-blind, placebo-controlled, parallel trial enrolled 90 healthy subjects. The consumption of W. cibaria CMS1 significantly increased salivary immunoglobulin A (p = 0.046) and decreased tumor necrosis factor-α (TNF-α) levels (p = 0.008). Analysis of the oral microbiota revealed changes in beta diversity, increased abundance of Firmicutes and Actinobacteria, and decreased abundance of Bacteroidetes and Fusobacteria after 12 weeks of consuming W. cibaria CMS1. Significant increases in various strains, including Lactobacillales, Bacilli, Streptococcaceae, Streptococcus, and Firmicutes, were observed in the W. cibaria CMS1 group after 12 weeks of intake. Additionally, Fusobacteriia Fusobacteriales Fusobacteriaceae and Fusobacteriia Fusobacteriales Fusobacteriaceae Fusobacterium exhibited a positive correlation with TNF-α. These findings demonstrate the positive effect of W. cibaria CMS1 on the oral environment and immune function.

Effects of the COVID-19 Pandemic on the Medical Use of Elderly Patients with Hypertension: A Nationwide Cohort Study in Korea.

Background: The coronavirus disease 2019 (COVID-19) pandemic has disrupted healthcare services, including chronic disease management, for vulnerable groups, such as older individuals with hypertension. This study aimed to evaluate hypertension management in South Korea's elderly population during the pandemic using treatment consistency indices such as the continuity of care (COC), modified, modified continuity index (MMCI), and most frequent provider continuity (MFPC). Methods: This study used the Korea Disease Control and Prevention Agency-COVID-19-National Health Insurance Service cohort (K-COV-N cohort) from the National Health Insurance Service between 2017 and 2021. The research included a total of 4,097,299 hypertensive patients aged 65 years or older. We defined 2018 and 2019 as the baseline period before the COVID-19 pandemic and 2020 and 2021 as the COVID-19 period and calculated the indices of medical continuity (number of visits, COC, MMCI, and MFPC) on a yearly basis. Results: The number of visits decreased during the COVID-19 period compared to the baseline period (59.64±52.75 vs. 50.49±50.33, P<0.001). However, COC, MMCI, and MFPC were not decreased in the baseline period compared to the COVID-19 period (0.71±0.21 vs. 0.71±0.22, P<0.001; 0.97±0.05 vs. 0.96±0.05, P<0.001; 0.8±0.17 vs. 0.8±0.17, P<0.001, respectively). Conclusion: COVID-19 had no significant impact on the continuity of care but affected the frequency of outpatient visits for older patients with hypertension. However, this study highlights the importance of addressing healthcare inequalities, especially in older patients with hypertension, during pandemics and advocates for policy changes to ensure continued care for vulnerable populations.

Analysis of HTT CAG repeat expansion among healthy individuals and patients with chorea in Korea.

BACKGROUND: Although the epidemiology of Huntington's disease (HD) in Korea differs notably from that in Western countries, the genetic disparities between these regions remain unclear. OBJECTIVE: To investigate the characteristics and clinical significance of cytosine-adenine-guanine (CAG) repeat size associated with HD in the Korean population. METHODS: We analyzed the CAG repeat lengths of the HTT gene in 941 healthy individuals (1,882 alleles) and 954 patients with chorea (1,908 alleles) from two referral hospitals in Korea. We presented normative CAG repeat length data for the Korean population and computed the reduced penetrance (36-39 CAG) and intermediate allele (27-35 CAG) frequencies in the two groups. Furthermore, we investigated the relationship between intermediate alleles and chorea development using logistic regression models in individuals aged ≥55 years. RESULTS: The mean (±standard deviation) CAG repeat length in healthy individuals was 17.5 ± 2.0, with a reduced penetrance allele frequency of 0.05 % (1/1882) and intermediate allele frequency of 0.69 % (13/1882). We identified 213 patients with genetically confirmed HD whose CAG repeat length ranged from 39 to 140, with a mean of 45.2 ± 7.9 in the longer allele. Compared with normal CAG repeat alleles, intermediate CAG repeat alleles were significantly related to a higher risk of developing chorea (age of onset range, 63-84 years) in individuals aged ≥55 years. CONCLUSIONS: This study provides insights into the specific characteristics of CAG repeat lengths in the HTT gene in the Korean population. The reduced penetrance and intermediate allele frequencies in the Korean general population seem to be lower than those reported in Western populations. The presence of intermediate alleles may increase the risk of chorea in the Korean elderly population, which requires further large-scale investigations.

Effect of anti-obesity agent HSG4112 on overweight and obese patients following 12 weeks of oral treatment: a study protocol for a randomised, double-blind, placebo-controlled, parallel-group, phase 2a clinical trial.

BACKGROUND: Glaceum Inc. has proposed HSG4112, a structural analogue of glabridin, as a novel anti-obesity compound. Animal studies and phase I human trials have shown that HSG4112 improves energy consumption, normalises weight, and is safe and drug-resistant. Based on these results, the company plans to conduct a phase 2a clinical trial to determine the safety and efficacy of HSG4112 in overweight and obese patients. METHODS: A 16-week randomised, double-blind, placebo-controlled, parallel-group trial will be conducted at five large hospitals in South Korea to assess the safety and efficacy of HSG4112 in overweight and obese patients. Participants who meet the inclusion/exclusion criteria will be assigned a subject number and randomly assigned to one of the four treatment groups (one group receiving a placebo) in a 1:1:1:1 ratio. The study's primary outcome will be to monitor the change in body weight (kg) from baseline to the end of treatment while monitoring safety and tolerability. DISCUSSION: This trial will evaluate the efficacy and safety of HSG4112 in overweight and obese adults. Upon proving the safety and effectiveness of the newly developed mechanism, it might significantly improve the perception of the product among medical personnel and obese patients. Furthermore, it may aid in managing chronic conditions that require long-term treatment. Trial registration: ClinicalTrials.gov, identifier [NCT05197556].

The Evaluation of Web-Based Communication Interventions to Support Decisions About COVID-19 Vaccination Among Patients With Underlying Medical Conditions: Protocol for a Randomized Controlled Trial.

BACKGROUND: The timeliness of raising vaccine acceptance and uptake among the public is essential to overcoming COVID-19; however, the decision-making process among patients with underlying medical conditions is complex, leading individuals to vaccine hesitancy because of their health status. Although vaccine implementation is more effective when deployed as soon as possible, vaccine hesitancy is a significant threat to the success of vaccination programs. OBJECTIVE: This study aims to evaluate the effectiveness of a communication tool for patients with underlying medical conditions who should decide whether to receive a COVID-19 vaccine. METHODS: This 3-arm prospective randomized controlled trial will test the effect of the developed communication intervention, which is fully automated, patient decision aid (SMART-DA), and user-centered information (SMART-DA-α). The web-based intervention was developed to help decision-making regarding COVID-19 vaccination among patients with underlying medical conditions. Over 450 patients will be enrolled on the web from a closed panel access website and randomly assigned to 1 of 3 equal groups stratified by their underlying disease, sex, age, and willingness to receive a COVID-19 vaccine. SMART-DA-α provides additional information targeted at helping patients' decision-making regarding COVID-19 vaccination. Implementation outcomes are COVID-19 vaccination intention, vaccine knowledge, decisional conflict, stress related to decision-making, and attitudes toward vaccination, and was self-assessed through questionnaires. RESULTS: This study was funded in 2020 and approved by the Clinical Research Information Service, Republic of Korea. Data were collected from December 2021 to January 2022. This paper was initially submitted before data analysis. The results are expected to be published in the winter of 2023. CONCLUSIONS: We believe that the outcomes of this study will provide valuable new insights into the potential of decision aids for supporting informed decision-making regarding COVID-19 vaccination and discovering the barriers to making informed decisions regarding COVID-19 vaccination, especially among patients with underlying medical conditions. This study will provide knowledge about the common needs, fears, and perceptions concerning vaccines among patients, which can help tailor information for individuals and develop policies to support them. TRIAL REGISTRATION: Korea Clinical Information Service KCT0006945; https://cris.nih.go.kr/cris/search/detailSearch.do/20965. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/42837.

Association between weekend catch-up sleep and the risk of depression among Korean middle-aged adults.

Determining whether weekend catch-up sleep (CUS) is related to high risk of depression in the general middle-aged population in Korea. This study is a cross-sectional study analyzing data from 2016 to 2017 collected in the Korea National Health and Nutrition Examination Survey VII-1, 2; less than 35 years, and more than 65 years were excluded. Interviews on sociodemographic characteristics, mood and sleep-related profiles, and comorbid medical conditions were conducted. Participants were divided into three groups according to weekday sleeping time (< 6 h, 6 to ≤ 8 h, and ≥ 8 h). Weekend CUS was identified when nocturnal sleep extension occurred over the weekend. The risk of depression was evaluated using the PHQ-9. The PHQ-9 score differed among the three groups. The prevalence of moderate to severe depressive symptom and PHQ-9 score ≥ 10 was the highest in the group sleep over 8 h and the next highest in the group sleep less than 6 h. In the group sleep less than 6 h, PHQ-9 score ≥ 10 was significantly higher in the without CUS group than the with CUS group. The risk of depression in middle-aged individuals was associated with both short and long sleep duration, and the severity and prevalence of depression were lower in the group with CUS when a shortened sleep pattern was observed. Supplementary Information: The online version contains supplementary material available at 10.1007/s41105-022-00415-3.

The clinical course of hospitalized COVID-19 patients and aggravation risk prediction models: a retrospective, multi-center Korean cohort study.

Background: Understanding the clinical course and pivotal time points of COVID-19 aggravation is critical for enhancing patient monitoring. This retrospective, multi-center cohort study aims to identify these significant time points and associate them with potential risk factors, leveraging data from a sizable cohort with mild-to-moderate symptoms upon admission. Methods: This study included data from 1,696 COVID-19 patients with mild-to-moderate clinical severity upon admission across multiple hospitals in Daegu-Kyungpook Province (Daegu dataset) between February 18 and early March 2020 and 321 COVID-19 patients at Seoul Boramae Hospital (Boramae dataset) collected from February to July 2020. The approach involved: (1) identifying the optimal time point for aggravation using survival analyses with maximally selected rank statistics; (2) investigating the relationship between comorbidities and time to aggravation; and (3) developing prediction models through machine learning techniques. The models were validated internally among patients from the Daegu dataset and externally among patients from the Boramae dataset. Results: The Daegu dataset showed a mean age of 51.0 ± 19.6 years, with 8 days for aggravation and day 5 being identified as the pivotal point for survival. Contrary to previous findings, specific comorbidities had no notable impact on aggravation patterns. Prediction models utilizing factors including age and chest X-ray infiltration demonstrated promising performance, with the top model achieving an AUC of 0.827 in external validation for 5 days aggravation prediction. Conclusion: Our study highlights the crucial significance of the initial 5 days period post-admission in managing COVID-19 patients. The identification of this pivotal time frame, combined with our robust predictive models, provides valuable insights for early intervention strategies. This research underscores the potential of proactive monitoring and timely interventions in enhancing patient outcomes, particularly for those at risk of rapid aggravation. Our findings offer a meaningful contribution to understanding the COVID-19 clinical course and supporting healthcare providers in optimizing patient care and resource allocation.

Machine learning models to predict the maximum severity of COVID-19 based on initial hospitalization record.

Background: As the worldwide spread of coronavirus disease 2019 (COVID-19) continues for a long time, early prediction of the maximum severity is required for effective treatment of each patient. Objective: This study aimed to develop predictive models for the maximum severity of hospitalized COVID-19 patients using artificial intelligence (AI)/machine learning (ML) algorithms. Methods: The medical records of 2,263 COVID-19 patients admitted to 10 hospitals in Daegu, Korea, from February 18, 2020, to May 19, 2020, were comprehensively reviewed. The maximum severity during hospitalization was divided into four groups according to the severity level: mild, moderate, severe, and critical. The patient's initial hospitalization records were used as predictors. The total dataset was randomly split into a training set and a testing set in a 2:1 ratio, taking into account the four maximum severity groups. Predictive models were developed using the training set and were evaluated using the testing set. Two approaches were performed: using four groups based on original severity levels groups (i.e., 4-group classification) and using two groups after regrouping the four severity level into two (i.e., binary classification). Three variable selection methods including randomForestSRC were performed. As AI/ML algorithms for 4-group classification, GUIDE and proportional odds model were used. For binary classification, we used five AI/ML algorithms, including deep neural network and GUIDE. Results: Of the four maximum severity groups, the moderate group had the highest percentage (1,115 patients; 49.5%). As factors contributing to exacerbation of maximum severity, there were 25 statistically significant predictors through simple analysis of linear trends. As a result of model development, the following three models based on binary classification showed high predictive performance: (1) Mild vs. Above Moderate, (2) Below Moderate vs. Above Severe, and (3) Below Severe vs. Critical. The performance of these three binary models was evaluated using AUC values 0.883, 0.879, and, 0.887, respectively. Based on results for each of the three predictive models, we developed web-based nomograms for clinical use (http://statgen.snu.ac.kr/software/nomogramDaeguCovid/). Conclusions: We successfully developed web-based nomograms predicting the maximum severity. These nomograms are expected to help plan an effective treatment for each patient in the clinical field.

Comparative analysis of the oral microbiome of burning mouth syndrome patients.

Burning mouth syndrome (BMS) is a chronic pain condition accompanied by unpleasant burning sensations of the oral mucosa. While multiple factors were proposed for the etiology, evidence suggested a neuropathic pain origin while others suspected the use of antibiotics as the underlying cause. Interestingly, several reports demonstrated the intimate interaction of the nervous system and the microbiome. The current study aims to elucidate the correlation of the oral microbiome with the pathophysiology of the primary BMS. Microbiome samples obtained from the unstimulated whole saliva of 19 primary BMS patients and 22 healthy controls were sequenced and analyzed of the V3-V4 region of 16S rRNA gene. There was a distinct difference in the microbial composition between the BMS and the control groups at all taxonomic levels. Alpha diversity indexes of the oral microbiome were significantly lower in the BMS group. The samples were readily distinguished by multidimensional scaling analysis and linear discriminant analysis effect size. Streptococcus, Rothia, Bergeyella, and Granulicatella genus were dominant in the BMS group, while Prevotella, Haemophilus, Fusobacterium, Campylobacter, and Allorevotella genus were more abundant in the healthy group. Distinct microbiome signatures of BMS patients suggested a diagnostic value and a potential role in the pathogenesis of BMS.

Factors related to the success of smoking cessation: A retrospective cohort study in Korea.

INTRODUCTION: Every year, at least half of the smokers in South Korea attempt to quit smoking. However, the Korean smoking rate remains still high among OECD countries. This study aimed to identify the factors that influence the success of smoking cessation efforts. METHODS: The study included 1395 smokers, who participated in a 12-week program comprising doctor counseling and pharmacological treatment (i.e. varenicline), conducted at smoking cessation clinics in two general hospitals from 2015 to 2019. The participants responded to a survey questionnaire inquiring about their smoking behaviors at the first visit to the clinic. After completing the program, they were asked whether they succeeded in smoking cessation. Based on participants' reported success or failure, multivariable logistic regression analyses were conducted to obtain adjusted odds ratios (AORs) and 95% confidence intervals (CIs) for factors related to smoking cessation success. RESULTS: Following the 12-week program, 39.6% of the participants (n=553) succeeded in smoking cessation. Lower rates of nicotine dependence (AOR=0.73; 95% Cl: 0.54-0.98) and lower total amounts of smoking (AOR=0.67; 95% Cl: 0.47-0.95) were significantly associated with higher success rates in smoking cessation. In addition, smokers who participated in the program for at least 8 weeks (AOR=7.16; 95% Cl: 5.57-9.20) and smokers who had hypertension (AOR=1.40; 95% Cl: 1.07-1.85) or a cardiovascular disease (AOR=1.68; 95% Cl: 1.03-2.75) achieved higher success rates. CONCLUSIONS: Smokers' success in smoking cessation was influenced by the period of visits to the smoking cessation clinic, the severity of nicotine dependence, and the presence of a cardiovascular disease including hypertension. Using these factors, smoking cessation strategy may be improved and personalized for individuals.

Yellow Yeast Rice Prepared Using Aspergillus terreus DSMK01 Lowers Cholesterol Levels by Stimulating Bile Salt Export Pump in Subjects with Mild-to-Moderate Hypercholesterolemia: A Randomized Controlled Trial.

SCOPE: Aspergillus terreus is an industrial microorganism used in the brewing and sauce industries. It produces monacolin K, a natural statin. The study conducted an 8-week randomized controlled trial with hypercholesterolemic subjects to examine the hypocholesterolemic effects and mechanisms of supplementation with yellow yeast rice (YYR) prepared by growing Aspergillus fungi on steamed rice. METHODS AND RESULTS: YYR supplementation markedly reduced total cholesterol, LDL, and apolipoprotein B100 levels in plasma compared with the placebo. In addition, YYR induced a significantly increased ATP binding cassette subfamily B member 11 (ABCB11) gene expression compared with the placebo, indicating the role of YYR in lowering intrahepatic cholesterol availability by stimulating the bile salt export pump. Upregulation of LDL receptor (LDLR) and 3-methylglutaryl-CoA reductase (HMGCR) gene expressions provided additional evidence to support the role of YYR in reducing hepatic cholesterol availability. Plasma metabolomic profiling revealed the possibility of diminishing bile acid absorption. Finally, Spearman rank analysis showed correlations of plasma cholesterol profiles with HMGCR and LDLR gene expressions (negative) and plasma bile acids (positive). Plasma bile acids also correlated with ABCB11 (negative) and LDLR (positive) gene expressions. CONCLUSION: These findings suggest that daily YYR supplementation exerted hypocholesterolemic effects in mild-to-moderate hypercholesterolemic subjects by reducing intrahepatic cholesterol availability through stimulating bile salt export pumps and inhibiting cholesterol biosynthesis.

Clinical Practice Guidelines for Managing Frailty in Community-Dwelling Korean Elderly Adults in Primary Care Settings.

Aging has become a global problem, and the interest in healthy aging is growing. Healthy aging involves a focus on the maintenance of the function and well-being of elderly adults, rather than a specific disease. Thus, the management of frailty, which is an accumulated decline in function, is important for healthy aging. The adaptation method was used to develop clinical practice guidelines on frailty management that are applicable in primary care settings. The guidelines were developed in three phases: preparation (organization of committees and establishment of the scope of development), literature screening and evaluation (selection of the clinical practice guidelines to be adapted and evaluation of the guidelines using the Korean Appraisal of Guidelines for Research and Evaluation II tool), and confirmation of recommendations (three rounds of Delphi consensus and internal and external reviews). A total of 16 recommendations (five recommendations for diagnosis and assessment, 11 recommendations for intervention of frailty) were made through the guideline development process. These clinical practice guidelines provide overall guidance on the identification, evaluation, intervention, and monitoring of frailty, making them applicable in primary care settings. As aging and "healthy aging" become more and more important, these guidelines are also expected to increase in clinical usefulness.

Microbiota of Breast Tissue and Its Potential Association with Regional Recurrence of Breast Cancer in Korean Women.

Recent studies have reported dysbiosis of the microbiome in breast tissue collected from patients with breast cancer and the association between the microbiota and disease progression. However, the role of the microbiota in breast tissue remains unclear, possibly due to the complexity of breast cancer and various factors, including racial and geographical differences, influencing microbiota in breast tissue. Here, to determine the potential role of microbiota in breast tumor tissue, we analyzed 141 tissue samples based on three different tissue types (tumor, adjacent normal, and lymph node tissues) from the same patients with breast cancer in Korea. The microbiota was not simply distinguishable based on tissue types. However, the microbiota could be divided into two cluster types, even within the same tissue type, and the clinicopathologic factors were differently correlated in the two cluster types. Risk of regional recurrence was also significantly different between the microbiota cluster types (p = 0.014). In predicted function analysis, the pentose and glucuronate interconversions were significantly different between the cluster types (q < 0.001), and Enterococcus was the main genus contributing to these differences (q < 0.01). Results showed that the microbiota of breast tissue could interact with the host and influence the risk of regional recurrence. Although further studies would be recommended to validate our results, this study could expand our understanding on the breast tissue microbiota, and the results might be applied to develop novel prediction methods and treatments for patients with breast cancer.

Associations of Diet Quality and Sleep Quality with Obesity.

Short sleep duration or poor sleep quality has been associated with an increased risk of obesity. Although the underlying mechanism remains unclear, one proposed pathway is poor diet quality. This cross-sectional study investigated whether diet quality modifies the association between sleep status and obesity in Korean adults. We used the baseline data and samples of 737 men and 428 women (n = 1165) aged 19-64, who participated in the prospective Ewha-Boramae cohort study. Sleep duration was dichotomized into ≥7 h (adequate) and <7 h (insufficient). Pittsburgh Sleep Quality Index (PSQI) values, reflecting sleep quality, were dichotomized into >5 (poor quality) and ≤5 (good quality). Diet quality was evaluated by the Recommended Food Score (RFS). Obesity was associated with higher rates of insufficient sleep and poor sleep quality in women, but not in men. After adjustment for covariates, women with poor sleep quality had a higher risk of obesity than women with good sleep quality (OR = 2.198; 95% CI = 1.027-4.704); this association occurred only in the group with RFS ≤ median score. Our findings support a significant association between sleep quality and obesity, and this association has been potentially modified by dietary quality in women.

A Machine Learning Algorithm for Quantitatively Diagnosing Oxidative Stress Risks in Healthy Adult Individuals Based on Health Space Methodology: A Proof-of-Concept Study Using Korean Cross-Sectional Cohort Data.

Oxidative stress aggravates the progression of lifestyle-related chronic diseases. However, knowledge and practices that enable quantifying oxidative stress are still lacking. Here, we performed a proof-of-concept study to predict the oxidative stress status in a healthy population using retrospective cohort data from Boramae medical center in Korea (n = 1328). To obtain binary performance measures, we selected healthy controls versus oxidative disease cases based on the "health space" statistical methodology. We then developed a machine learning algorithm for discrimination of oxidative stress status using least absolute shrinkage and selection operator (LASSO)/elastic net regression with 10-fold cross-validation. A proposed fine-tune model included 16 features out of the full spectrum of diverse and complex data. The predictive performance was externally evaluated by generating receiver operating characteristic curves with area under the curve of 0.949 (CI 0.925 to 0.974), sensitivity of 0.923 (CI 0.879 to 0.967), and specificity of 0.855 (CI 0.795 to 0.915). Moreover, the discrimination power was confirmed by applying the proposed diagnostic model to the full dataset consisting of subjects with various degrees of oxidative stress. The results provide a feasible approach for stratifying the oxidative stress risks in the healthy population and selecting appropriate strategies for individual subjects toward implementing data-driven precision nutrition.

The relationship between smoking cigarettes and metabolic syndrome: A cross-sectional study with non-single residents of Seoul under 40 years old.

INTRODUCTION: Young adults receive health screenings at lower rates than other age groups, and it may be difficult to detect diseases in the early stages for this group. We examined differences in health status relative to smoking in a young age group using the results of health screenings conducted in engaged and newly married couples in a cross-sectional database. METHODS: The participants in this study were 808 young adults who visited a municipal hospital health screening center from July 2017 to March 2019. They completed a self-administered questionnaire, and physical measurements and a blood test were taken. They were classified into non-cigarette smokers, past cigarette smokers, and current cigarette smokers according to smoking behavior. In this study, we compared metabolic syndrome, the main components of which include obesity, high blood pressure, high blood triglycerides, low levels of HDL cholesterol and insulin resistance, with smoking behavior. RESULTS: The mean age of the participants was 30.9±3.3 years (males 32.0±3.2, females 29.8±3.1), and 13.9% were current cigarette smokers (males 22.8%, females 5.1%). The proportion of men in their 30s was 76.6% for male group and 50.0% for female group, indicating that the male group had a relatively higher proportion of older and current smokers. Significant differences were found in age, sex, blood pressure, metabolic abnormalities, and drinking status according to smoking status. Cigarette smokers had a 2.4-fold greater risk of metabolic syndrome (95% confidence interval [CI], 1.43-3.96) than non-cigarette smokers; in particular, they had a 2.6-fold (95% CI, 1.44-4.55) greater risk of hypertriglyceridemia and a three-fold (95% CI, 1.45-6.35) greater risk of low HDL cholesterol. CONCLUSIONS: In comparison with non-single, young and generally healthy city dwellers, the risk of metabolic syndrome was significantly higher in smokers than in non-smokers, and in particular, it was confirmed that the risk of hypertriglyceridemia and low HDL cholesterolemia was higher. Smoking cessation is necessary, even for the young, because smoking may cause changes in blood lipids even if the smoking duration is short.

Spore-forming Bacillus coagulans SNZ 1969 improved intestinal motility and constipation perception mediated by microbial alterations in healthy adults with mild intermittent constipation: A randomized controlled trial.

The spore-forming Bacillus coagulans has attracted attention for their therapeutic action in the colon. However, the mechanism of this action remains unclear. In this study, healthy subjects with mild intermittent constipation were supplemented with B. coagulans SNZ 1969 (BC) or the placebo for 8 weeks (n = 80). Then, we assessed colonic transit time (CTT), weekly complete spontaneous bowel movement (CSBM) scores, bowel discomfort symptom (BDS) scores, and 16S rRNA fecal microbiome profiles. The association between the critically altered gut microbiome and clinical outcomes was analyzed using redundancy analysis (RDA) and validated by receiver operating characteristic (ROC) curves. BC supplementation significantly improved CTT (p = 0.031), CSBM at weeks 2 (p = 0.045) and 9 (p = 0.038), and BDS at weeks 3 (p = 0.019) and 6 (p = 0.029) compared with the placebo, while altering the community composition of the gut microbiota. We also confirmed that BC was effectively delivered to the gut. Finally, the multivariate redundancy analysis concluded that BC-induced enrichment of Lactobacillales and diminishment of Synergistales were related to CTT improvements. This study provides important new data on how spore-forming B. coagulans SNZ 1969 contributes to improving gut motility and presents evidence supporting the use of B. coagulans SNZ 1969 in adults with mild intermittent constipation and habitual low intake of fruit and vegetables.

Prediction Models for the Clinical Severity of Patients With COVID-19 in Korea: Retrospective Multicenter Cohort Study.

BACKGROUND: Limited information is available about the present characteristics and dynamic clinical changes that occur in patients with COVID-19 during the early phase of the illness. OBJECTIVE: This study aimed to develop and validate machine learning models based on clinical features to assess the risk of severe disease and triage for COVID-19 patients upon hospital admission. METHODS: This retrospective multicenter cohort study included patients with COVID-19 who were released from quarantine until April 30, 2020, in Korea. A total of 5628 patients were included in the training and testing cohorts to train and validate the models that predict clinical severity and the duration of hospitalization, and the clinical severity score was defined at four levels: mild, moderate, severe, and critical. RESULTS: Out of a total of 5601 patients, 4455 (79.5%), 330 (5.9%), 512 (9.1%), and 301 (5.4%) were included in the mild, moderate, severe, and critical levels, respectively. As risk factors for predicting critical patients, we selected older age, shortness of breath, a high white blood cell count, low hemoglobin levels, a low lymphocyte count, and a low platelet count. We developed 3 prediction models to classify clinical severity levels. For example, the prediction model with 6 variables yielded a predictive power of >0.93 for the area under the receiver operating characteristic curve. We developed a web-based nomogram, using these models. CONCLUSIONS: Our prediction models, along with the web-based nomogram, are expected to be useful for the assessment of the onset of severe and critical illness among patients with COVID-19 and triage patients upon hospital admission.