Assessing the Feasibility and Efficacy of Pre-Sleep Dim Light Therapy for Adults with Insomnia: A Pilot Study.

Background: Insomnia is increasingly recognized for its marked impact on public health and is often associated with various adverse health outcomes, including cardiovascular diseases and mental health disorders. The aim of this study was to investigate the efficacy of pre-sleep dim light therapy (LT) as a non-pharmacological intervention for insomnia in adults, assessing its influence on sleep parameters and circadian rhythms. Methods: A randomized, open-label, two-arm clinical trial was conducted over two weeks with 40 participants aged 20-60 years, all of whom had sleep disorders (CRIS, KCT0008501). They were allocated into control and LT groups. The LT group received exposure to warm-colored light, minimizing the blue spectrum, before bedtime. The study combined subjective evaluation via validated, sleep-related questionnaires, objective sleep assessments via actigraphy, and molecular analyses of circadian clock gene expression in peripheral blood mononuclear cells. Baseline characteristics between the two groups were compared using an independent t-test for continuous variables and the chi-squared test for categorical variables. Within-group differences were assessed using the paired t-test. Changes between groups were analyzed using linear regression, adjusting for each baseline value and body mass index. The patterns of changes in sleep parameters were calculated using a linear mixed model. Results: The LT group exhibited significant improvements in sleep quality (difference in difference [95% CI]; -2.00 [-3.58, -0.43], and sleep efficiency (LT: 84.98 vs. control: 82.11, p = 0.032), and an advanced Dim Light Melatonin Onset compared to the control group (approximately 30 min). Molecular analysis indicated a significant reduction in CRY1 gene expression after LT, suggesting an influence on circadian signals for sleep regulation. Conclusions: This study provides evidence for the efficacy of LT in improving sleep quality and circadian rhythm alignment in adults with insomnia. Despite limitations, such as a small sample size and short study duration, the results underscore the potential of LT as a viable non-pharmacological approach for insomnia. Future research should expand on these results with larger and more diverse cohorts followed over a longer period to validate and further elucidate the value of LT in sleep medicine. Trial registration: The trial was registered with the Clinical Research Information Service (KCT0008501).

Feasibility and Efficacy of Morning Light Therapy for Adults with Insomnia: A Pilot, Randomized, Open-Label, Two-Arm Study.

Background and Objectives: Light therapy (LT) is used as an adjunctive treatment for sleep problems. This study evaluates the impact of LT on sleep quality and sleep-related parameters in patients with sleep disorders. Materials and Methods: We performed a pilot, randomized, open-label clinical trial. Fourteen patients aged 20-60 years with insomnia were randomized into the control and LT groups (1:1 ratio). The LT group was instructed to use a device that provides bright LT (6000 K, 380 lux, wavelength 480 nm) for at least 25 min before 09:00 a.m. for two weeks. A self-reported questionnaire was used to evaluate circadian preference, mood, and sleep-related parameters. We analyzed serum cortisol levels and clock genes' expression. Results: The Epworth Sleepiness Scale (ESS), insomnia severity index(ISI), and Pittsburgh Sleep Quality index(PSQI) were significantly improved within the LT group only after the two-week period. When comparing the two groups, only the change in ESS was significant (mean difference, control: -0.14 vs. LT: -1.43, p = 0.021) after adjusting for the baseline characteristics. There were no significant differences in serum cortisol or clock genes' expression. Conclusions: LT can improve daytime sleepiness in patients with sleep disorders; however, further well-designed studies are warranted to confirm its efficacy.

Automatic Grading of Stroke Symptoms for Rapid Assessment Using Optimized Machine Learning and 4-Limb Kinematics: Clinical Validation Study.

BACKGROUND: Subtle abnormal motor signs are indications of serious neurological diseases. Although neurological deficits require fast initiation of treatment in a restricted time, it is difficult for nonspecialists to detect and objectively assess the symptoms. In the clinical environment, diagnoses and decisions are based on clinical grading methods, including the National Institutes of Health Stroke Scale (NIHSS) score or the Medical Research Council (MRC) score, which have been used to measure motor weakness. Objective grading in various environments is necessitated for consistent agreement among patients, caregivers, paramedics, and medical staff to facilitate rapid diagnoses and dispatches to appropriate medical centers. OBJECTIVE: In this study, we aimed to develop an autonomous grading system for stroke patients. We investigated the feasibility of our new system to assess motor weakness and grade NIHSS and MRC scores of 4 limbs, similar to the clinical examinations performed by medical staff. METHODS: We implemented an automatic grading system composed of a measuring unit with wearable sensors and a grading unit with optimized machine learning. Inertial sensors were attached to measure subtle weaknesses caused by paralysis of upper and lower limbs. We collected 60 instances of data with kinematic features of motor disorders from neurological examination and demographic information of stroke patients with NIHSS 0 or 1 and MRC 7, 8, or 9 grades in a stroke unit. Training data with 240 instances were generated using a synthetic minority oversampling technique to complement the imbalanced number of data between classes and low number of training data. We trained 2 representative machine learning algorithms, an ensemble and a support vector machine (SVM), to implement auto-NIHSS and auto-MRC grading. The optimized algorithms performed a 5-fold cross-validation and were searched by Bayes optimization in 30 trials. The trained model was tested with the 60 original hold-out instances for performance evaluation in accuracy, sensitivity, specificity, and area under the receiver operating characteristics curve (AUC). RESULTS: The proposed system can grade NIHSS scores with an accuracy of 83.3% and an AUC of 0.912 using an optimized ensemble algorithm, and it can grade with an accuracy of 80.0% and an AUC of 0.860 using an optimized SVM algorithm. The auto-MRC grading achieved an accuracy of 76.7% and a mean AUC of 0.870 in SVM classification and an accuracy of 78.3% and a mean AUC of 0.877 in ensemble classification. CONCLUSIONS: The automatic grading system quantifies proximal weakness in real time and assesses symptoms through automatic grading. The pilot outcomes demonstrated the feasibility of remote monitoring of motor weakness caused by stroke. The system can facilitate consistent grading with instant assessment and expedite dispatches to appropriate hospitals and treatment initiation by sharing auto-MRC and auto-NIHSS scores between prehospital and hospital responses as an objective observation.

The relationship between metabolic syndrome and the incidence of colorectal cancer.

OBJECTIVES: This study evaluated the incidence of colorectal cancer (CRC) according to the number of metabolic syndrome (MetS) components. METHODS: Using health checkup and insurance claims data of 6,365,409 subjects, the occurrence of CRC according to stage of MetS by sex was determined from the date of the health checkup in 2009 until December 31, 2018. RESULTS: Cumulative incidence rates (CIR) of CRC in men and women was 3.9 and 2.8 per 1000 (p < 0.001), respectively. CIR of CRC for the normal, pre-MetS, and MetS groups in men was 2.6, 3.9, and 5.5 per 1000 (p < 0.001) and CIR in women was 2.1, 2.9, and 4.5 per 1000 (p < 0.001), respectively. Compared with the normal group, the hazard ratio (HR) of CRC for the pre-MetS group was 1.25 (95% CI 1.17-1.33) in men and 1.09 (95% CI 1.02-1.17) in women, and the HR of CRC for the MetS group was 1.54 (95% CI 1.43-1.65) in men and 1.39 (95% CI 1.26-1.53) in women after adjustment. CONCLUSIONS: We found that MetS is a risk factor for CRC in this study. Therefore, the prevention and active management of MetS would contribute to the prevention of CRC.

Retrospective observation on contribution and limitations of screening for breast cancer with mammography in Korea: detection rate of breast cancer and incidence rate of interval cancer of the breast.

BACKGROUND: The purpose of this study was to determine the benefits and limitations of screening for breast cancer using mammography. METHODS: Descriptive design with follow-up was used in the study. Data from breast cancer screening and health insurance claim data were used. The study population consisted of all participants in breast cancer screening from 2009 to 2014. Crude detection rate, positive predictive value and sensitivity and specificity of breast cancer screening and, incidence rate of interval cancer of the breast were calculated. RESULTS: The crude detection rate of breast cancer screening per 100,000 participants increased from 126.3 in 2009 to 182.1 in 2014. The positive predictive value of breast cancer screening per 100,000 positives increased from 741.2 in 2009 to 1,367.9 in 2014. The incidence rate of interval cancer of the breast per 100,000 negatives increased from 51.7 in 2009 to 76.3 in 2014. The sensitivities of screening for breast cancer were 74.6% in 2009 and 75.1% in 2014 and the specificities were 83.1% in 2009 and 85.7% in 2014. CONCLUSIONS: To increase the detection rate of breast cancer by breast cancer screening using mammography, the participation rate should be higher and an environment where accurate mammography and reading can be performed and reinforcement of quality control are required. To reduce the incidence rate of interval cancer of the breast, it will be necessary to educate women after their 20s to perform self-examination of the breast once a month regardless of participation in screening for breast cancer.

Effectiveness of the triglyceride-glucose index and triglyceride-glucose-related indices in predicting cardiovascular disease in middle-aged and older adults: A prospective cohort study.

BACKGROUNDS: Cardiovascular disease (CVD) risk assessment is a crucial component of public health. We aimed to determine the predictive value of the triglyceride-glucose (TyG) index and TyG-related indices for new-onset CVD. METHODS: This prospective study included 7,808 participants aged 40-69 years from the Ansung-Ansan cohort database. Our analysis was stratified by diabetes status. The hazard ratio (HR) with a 95% confidence interval (CI) for incident CVD was computed using multiple Cox proportional-hazards regression models. To evaluate the predictive performance of these indices for new-onset CVD, we calculated the Harrell's C-index (95% CI). RESULTS: In this study, a total of 6,890 participants did not have diabetes at baseline, while 918 participants had diabetes. In participants without diabetes, compared to the lowest tertile, fully adjusted HR and 95% CI for new-onset CVD in the highest tertile were as follows: TyG (HR 1.42, 95% CI 1.06-1.90), TyG-body mass index (BMI) (HR 1.92, 95% CI 1.19-3.10), TyG-waist circumference (WC) (HR 2.37, 95% CI 1.61-3.49), and TyG-waist-to-height ratio (WHtR) (HR 2.20, 95% CI 1.47-3.28). However, no significant associations were observed between TyG, modified TyG indices, and new-onset CVD in participants with diabetes. Notably, the C-indice of TyG-WC and TyG-WHtR were significantly higher than those of TyG and TyG-BMI in participants without diabetes. CONCLUSIONS: TyG-BMI, TyG-WC, and TyG-WHtR were associated with an increased risk of new-onset CVD in participants without diabetes. Furthermore, TyG-WC and TyG-WHtR showed better predictive performances for new-onset CVD than TyG and TyG-BMI in participants without diabetes.

Comprehensive assessment of the combined impact of dyslipidemia and inflammation on chronic kidney disease development: A prospective cohort study.

BACKGROUND: There remains a limited comprehensive understanding of how dyslipidemia and chronic inflammation collectively contribute to the development of chronic kidney disease (CKD). OBJECTIVE: We aimed to identify clusters of individuals with five variables, including lipid profiles and C-reactive protein (CRP) levels, and to assess whether the clusters were associated with incident CKD risk. METHODS: We used the Korean Genome and Epidemiology Study-Ansan and Ansung data. K-means clustering analysis was performed to identify distinct clusters based on total cholesterol, triglyceride, non-high-density lipoprotein (HDL)-C, HDL-C, and CRP levels. Cox proportional hazards models were used to examine the association between incident CKD risk and the different clusters. RESULTS: During the mean 10-year follow-up period, CKD developed in 1,645 participants (690 men and 955 women) among a total of 8,053 participants with a mean age of 51.8 years. Four distinct clusters were identified: C1, low cholesterol group (LC); C2, high-density lipoprotein cholesterol group (HC); C3, insulin resistance and inflammation group (IIC); and C4, dyslipidemia and inflammation group (DIC). Cluster 4 had a significantly higher risk of incident CKD compared to clusters 2 (hazard ratio (HR) 1.455 [95% confidence interval (CI) 1.234-1.715]; p < 0.001) and cluster 1 (HR 1.264 [95% CI 1.067-1.498]; p = 0.007) after adjusting for confounders. Cluster 3 had a significantly higher risk of incident CKD compared to clusters 2 and 1. CONCLUSION: Clusters 4 and 3 had higher risk of incident CKD compared to clusters 2 and 1. The combination of dyslipidemia with inflammation or insulin resistance with inflammation appears to be pivotal in the development of incident CKD.

Agreement and Reliability Analysis of Machine Learning Scaling and Wireless Monitoring in the Assessment of Acute Proximal Weakness by Experts and Non-Experts: A Feasibility Study.

Assessing the symptoms of proximal weakness caused by neurological deficits requires the knowledge and experience of neurologists. Recent advances in machine learning and the Internet of Things have resulted in the development of automated systems that emulate physicians' assessments. The application of those systems requires not only accuracy in the classification but also reliability regardless of users' proficiency in the real environment for the clinical point-of-care and the personalized health management. This study provides an agreement and reliability analysis of using a machine learning-based scaling of Medical Research Council (MRC) proximal scores to evaluate proximal weakness by experts and non-experts. The system trains an ensemble learning model using the signals from sensors attached to the limbs of patients in a neurological intensive care unit. For the agreement analysis, we investigated the percent agreement of MRC proximal scores and Bland-Altman plots of kinematic features between the expert- and non-expert scaling. We also analyzed the intra-class correlation coefficients (ICCs) of kinematic features and Krippendorff's alpha of the observers' scaling for the reliability analysis. The mean percent agreement between the expert- and the non-expert scaling was 0.542 for manual scaling and 0.708 for autonomous scaling. The ICCs of kinematic features measured using sensors ranged from 0.742 to 0.850, whereas the Krippendorff's alpha of manual scaling for the three observers was 0.275. The autonomous assessment system can be utilized by the caregivers, paramedics, or other observers during an emergency to evaluate acute stroke patients.

Age-Standardized Breast Cancer Detection Rates of Breast Cancer Screening Program by Age Group in Korea; Comparison with Age-Standardized Incidence Rates from the Korea Central Cancer Registry.

To compare the epidemiological characteristics of a breast cancer screening program of patients between 40-69 years of age and ≥70 years of age, we calculated the age-standardized detection rate of the breast cancer screening program and compared it with the age-standardized incidence rate from the Korea Central Cancer Registry. The data of the breast cancer screening program from January 2009 to December 2016 and the data of the health insurance claims from January 2006 to August 2017 were used. In the 40-69 year age group, the age-standardized detection rate of breast cancer increased annually from 106.1 in 2009 to 158.6 in 2015 and did not differ from the age-standardized incidence rate. In the ≥70 year age group, the age-standardized detection rate of breast cancer increased annually from 65.7 in 2009 to 120.3 in 2015 and was 1.9 to 2.7 fold of the age­standardized incidence rate. It shows that the early detection effect of breast cancer screening was greater for patients over 70 years old. Further studies are needed to evaluate the effect of breast cancer detection in the ≥70 year age group on all-cause mortality or breast cancer mortality.

The New Diagnosis-Related Group Reimbursement System and Laboratory Test Quality in Korea: Analysis of External Quality Assessment Results.

Korea introduced a new diagnosis-related group (NDRG), which is a mixed-bundle reimbursement system. We evaluated the effects of NDRGs on laboratory test quality by analyzing data over three years (2016-2018) from the Korean Association of External Quality Assessment Service (KEQAS). A total of 42 NDRG-participating hospitals (CASE), 84 non-participating similar size-hospitals (CON-1), and 42 tertiary hospitals (CON-2) were included. We assumed the proportion of KEQAS results with a larger than 2 standard deviation index (SDI) to be a bad laboratory quality marker (BLQM). CASE BLQMs were lower than CON-1 BLQMs for more than 2 years in alkaline phosphatase (ALP), alanine aminotransferase (ALT), chloride, glucose, sodium, and total protein, and higher in creatinine. CASE BLQMs were higher than CON-2 BLQMs for more than 2 years in ALP, chloride, creatinine, glucose, lactate dehydrogenase (LDH), phosphorus, potassium, sodium, total calcium, total cholesterol, triglyceride, and uric acid. Mean SDIs for general chemistry tests were not significantly different depending on NDRG participation. However, the NDRG is currently a pilot program that compensates the amount of each institution's reimbursement based on the fee-for-service system, and most participants were public hospitals. Thus, the effects of NDRGs on laboratory test quality should be re-evaluated after the NDRG program has stabilized and more private hospitals are participating.

Status of Quality Control for Laboratory Tests of Medical Institutions in Korea: Analysis of 10 Years of Data on External Quality Assessment Participation.

External quality assessment (EQA) is a commonly used tool to track the performance of laboratory tests. In Korea, EQA participation is not mandatory, and even basic data about EQA participation are not available. We used data of a 10-year period extracted from two databases (2009-2018): (1) the database of the National Health Insurance Service to calculate the number of medical institutions that claimed health insurance benefits, and (2) the database of the Korean Association of External Quality Assessment Service to calculate the number of medical institutions participating in EQA. The proportion of institutions that made claims for the performance of laboratory testing throughout the 10 years were 73.6%-76.0% for clinics, 91.9%-97.5% for long-term care hospitals, 97.9%-99.5% for small to medium hospitals, 99.6%-100% for general hospitals, and 100% for tertiary hospitals. The mean EQA participation rate of institutions that performed laboratory testing for the 10 years was 1.9% for clinics, 3.1% for long-term care hospitals, 27.7% for small to medium hospitals, 96.6% for general hospitals, and 100% for tertiary hospitals. The mean EQA participation of clinics, long-term care hospitals, and small to medium hospitals are increasing but is still not sufficient. Regulatory approaches are needed to increase participation rates. This result would be used for health policymaking on the quality improvement of laboratory tests.