Objectives: Intradiscal steroid injection (ISI) use has been proven as a low-risk and rapid treatment for disc degeneration disease (DDD). However, the histological effects of steroids on human discs remain poorly understood. The purpose of this study is to investigate whether ISI induces histologic degeneration of the disc. Methods: In this study, a histological analysis was carried out on the nucleus pulposus obtained from 150 patients who underwent posterior lumbar interbody fusion. Among these individuals, 59 received ISI before the surgery, while 91 did not. After staining with hematoxylin and eosin, the histological classification was performed based on chondrocyte proliferation (C1, C2, and C3) and granular matrix change (M1 and M2). Logistic regression analysis was used to identify the main factors influencing chondrocyte proliferation and granular matrix change.Additionally, histological differences between the ISI group and the non-ISI group were analyzed. Results: Chondrocyte proliferation and granular matrix changes were not significantly different between the ISI and non-ISI groups. The logistic regression analysis indicated that age is the most significant risk factor for both chondrocyte proliferation (P = 0.02) and granular matrix changes (P < 0.01). Conclusions The most crucial factor in disc degeneration is age. ISI does not accelerate the histological degeneration of chondrocyte proliferation and granular matrix. Therefore, the ISI could be considered as a histologically safe alternative in patients with DDD.

Objectives: Smart hospitals involve the application of recent information and communications technology (ICT) innovations to medical services; however, the concept of a smart hospital has not been rigorously defined. In this study, we aimed to derive the definition and service types of smart hospitals and investigate cases of each type. Methods: A literature review was conducted regarding the background and technical characteristics of smart hospitals. On this basis, we conducted a focus group interview with experts in hospital information systems, and ultimately derived eight smart hospital service types. Results: Smart hospital services can be classified into the following types: services based on location recognition and tracking technology that measures and monitors the location information of an object based on short-range communication technology; high-speed communication network-based services based on new wireless communication technology; Internet of Things-based services that connect objects embedded with sensors and communication functions to the internet; mobile health services such as mobile phones, tablets, and wearables; artificial intelligence-based services for the diagnosis and prediction of diseases; robot services provided on behalf of humans in various medical fields; extended reality services that apply hyper-realistic immersive technology to medical practice; and telehealth using ICT. Conclusions Smart hospitals can influence health and medical policies and create new medical value by defining and quantitatively measuring detailed indicators based on data collected from existing hospitals. Simultaneously, appropriate government incentives, consolidated interdisciplinary research, and active participation by industry are required to foster and facilitate smart hospitals.

Objectives: The purpose of this study was to explore new ways of creating value in the medical field and to derive recommendations for the role of medical institutions and the government. Methods: In this paper, based on expert discussion, we classified Internet of Things (IoT) technologies into four categories according to the type of information they collect (location, environmental parameters, energy consumption, and biometrics), and investigated examples of application. Results: Biometric IoT diagnoses diseases accurately and offers appropriate and effective treatment. Environmental parameter measurement plays an important role in accurately identifying and controlling environmental factors that could be harmful to patients. The use of energy measurement and location tracking technology enabled optimal allocation of limited hospital resources and increased the efficiency of energy consumption. The resulting economic value has returned to patients, improving hospitals’ cost-effectiveness. Conclusions Introducing IoT-based technology to clinical sites, including medical institutions, will enhance the quality of medical services, increase patient safety, improve management efficiency, and promote patient-centered medical services. Moreover, the IoT is expected to play an active role in the five major tasks of facility hygiene in medical fields, which are all required to deal with the COVID-19 pandemic: social distancing, contact tracking, bed occupancy control, and air quality management. Ultimately, the IoT is expected to serve as a key element for hospitals to perform their original functions more effectively. Continuing investments, deregulation policies, information protection, and IT standardization activities should be carried out more actively for the IoT to fulfill its expectations.

Background: Previously developed prediction models for type 2 diabetes mellitus (T2DM) have limited performance. We developed a deep learning (DL) based model using a cohort representative of the Korean population. Methods: This study was conducted on the basis of the National Health Insurance Service-Health Screening (NHIS-HEALS) cohort of Korea. Overall, 335,302 subjects without T2DM at baseline were included. We developed the model based on 80% of the subjects, and verified the power in the remainder. Predictive models for T2DM were constructed using the recurrent neural network long short-term memory (RNN-LSTM) network and the Cox longitudinal summary model. The performance of both models over a 10-year period was compared using a time dependent area under the curve. Results: During a mean follow-up of 10.4±1.7 years, the mean frequency of periodic health check-ups was 2.9±1.0 per subject. During the observation period, T2DM was newly observed in 8.7% of the subjects. The annual performance of the model created using the RNN-LSTM network was superior to that of the Cox model, and the risk factors for T2DM, derived using the two models were similar; however, certain results differed. Conclusion The DL-based T2DM prediction model, constructed using a cohort representative of the population, performs better than the conventional model. After pilot tests, this model will be provided to all Korean national health screening recipients in the future.

Background: Previously developed prediction models for type 2 diabetes mellitus (T2DM) have limited performance. We developed a deep learning (DL) based model using a cohort representative of the Korean population. Methods: This study was conducted on the basis of the National Health Insurance Service-Health Screening (NHIS-HEALS) cohort of Korea. Overall, 335,302 subjects without T2DM at baseline were included. We developed the model based on 80% of the subjects, and verified the power in the remainder. Predictive models for T2DM were constructed using the recurrent neural network long short-term memory (RNN-LSTM) network and the Cox longitudinal summary model. The performance of both models over a 10-year period was compared using a time dependent area under the curve. Results: During a mean follow-up of 10.4±1.7 years, the mean frequency of periodic health check-ups was 2.9±1.0 per subject. During the observation period, T2DM was newly observed in 8.7% of the subjects. The annual performance of the model created using the RNN-LSTM network was superior to that of the Cox model, and the risk factors for T2DM, derived using the two models were similar; however, certain results differed. Conclusion The DL-based T2DM prediction model, constructed using a cohort representative of the population, performs better than the conventional model. After pilot tests, this model will be provided to all Korean national health screening recipients in the future.

PURPOSE: This study aimed to evaluate the effects of meaning-centered therapy (MCT) on depressive symptoms in adults and older adults, excluding cancer patients.METHODS: Ten databases were systematically to extract peer-reviewed journal articles and dissertations in Korean or English. Two independent researchers assessed the risk of bias and the quality of the report using Scottish Intercollegiate Guidelines Network criteria.RESULTS: A total of 12 (five Korean and seven non-Korean) studies were finally selected after removing 66 of the 78 studies assessed for eligibility due to inappropriate subject inclusion and research design. Eleven studies reported that MCT was effective in reducing depressive symptoms, except for one study using web-based MCT for cancer caregivers. Those studies also showed that the effects remained at the patient follow-up sessions.CONCLUSION: The reviewed studies provide evidence suggesting that MCT may be effective in reducing depressive symptoms in adults and older adults. However, it is necessary to investigate the effectiveness of on-line MCT on the depressive symptom reduction in the future.
Adult ; Bias (Epidemiology) ; Caregivers ; Depression ; Existentialism ; Follow-Up Studies ; Humans ; Psychotherapy ; Research Design

PURPOSE: The skin pH is maintained by epidermal lactate, free fatty acids (FFAs), and free amino acids (FAAs). As a significant determinant of skin health, the skin pH is increased (less acidic) under abnormal and aged skin conditions. In a search for dietary alternatives that would promote an acidic skin pH, this study investigated the dietary effects of Lactobacillus plantarum CJLP55 isolated from Korean kimchi on the skin pH, and epidermal levels of lactate, FFAs, and FAAs in adult subjects. METHODS: Seventy eight subjects (mean age 24.9 ± 0.5 years, range 19 ~ 37 years) were assigned randomly to ingest CJLP55, Lactobacillus strain from kimchi, (n = 39, CJLP group) or placebo supplements (n = 39, placebo group) for 12 weeks in a double-blind, placebo-controlled trial. Skin pH and epidermal levels of lactate, FFAs and FFAs were assessed at 0, 6 and 12 weeks. RESULTS: Although significant decreases in skin pH were observed in both the CJLP and placebo groups at 6 weeks, the skin pH was decreased significantly only in the CJLP group at 12 weeks. In parallel, the epidermal level of lactate in the CJLP group was also increased by 25.6% at 12 weeks. On the other hand, the epidermal level of FAAs were not altered in the CJLP and placebo groups, but the epidermal level of total FFAs, including palmitic acid and stearic acid, was lower in the CJLP group than in the placebo group over 12 weeks. The changes in the other FFAs, such as palmitoleic acid and oleic acid, were similar in the CJLP and placebo groups over 12 weeks. CONCLUSION: Overall, a dietary supplement of CJLP55 promotes acidic skin pH with a selective increase in epidermal lactate in adult subjects.
Adult ; Amino Acids ; Dietary Supplements ; Fatty Acids, Nonesterified ; Hand ; Humans ; Hydrogen-Ion Concentration ; Lactic Acid ; Lactobacillus plantarum ; Lactobacillus ; Oleic Acid ; Palmitic Acid ; Skin

PURPOSE: This study was done to identify prevalence of, and factors influencing metabolic syndrome among long-term care facility patients with schizophrenia. METHODS: A cross-sectional survey was conducted using a 20-item questionnaire. Clinical data for blood triglyceride, HDL-cholesterol, and fasting blood sugar were collected from medical records. Body weight, body fat, body mass index, blood pressure, height, and abdominal circumference were measured. Data for 198 participants were analyzed using t-test, x2 test and logistic regression. RESULTS: Prevalence of metabolic syndrome was 56.1%. The number of persons who overate was significantly higher in the metabolic syndrome group than in the normal group (p<.001). Factors influencing metabolic syndrome were hyperphagia (p<.001), abdominal circumference (p<.001), systolic blood pressure (p=.040), blood triglyceride (p<.001), fasting blood sugar (p=.015), and HDL-cholesterol (p<.001). CONCLUSION: The results indicate that nurses working with patients who have chronic schizophrenic should make an effort to help patients achieve control of overeating behavior and reduce abdominal circumference to prevent metabolic syndrome.
Adipose Tissue ; Blood Glucose ; Blood Pressure ; Body Mass Index ; Body Weight ; Cross-Sectional Studies ; Fasting ; Humans ; Hyperphagia ; Logistic Models ; Long-Term Care ; Medical Records ; Mental Health* ; Metabolic Syndrome X ; Obesity ; Prevalence ; Schizophrenia* ; Triglycerides

PURPOSE: This study was conducted in order to analyze the dietary habits and food intake status according to the prevalence of depression in adults. METHODS: A total of 496 subjects, 224 men and 272 women aged 50 to 100 years were recruited from more than 13 cities in Korea. The questionnaires consisted of general characteristics, dietary life status, food intakes, the mean mini dietary assessment and satisfaction with food-related life questionnaire of the subjects to ask according to the degree of depression. Depression status was evaluated according to the Korean form of the Geriatric Depression Scale (K-GDS). RESULTS: All subjects were divided into depression or normal groups; the prevalence of depression was 13.8% (male) and 23.9% (female). People aged 65 or older were more likely to have higher prevalence of depression and to be bereaved. People in the depression group had poor appetite, almost never dined-out, and ate alone. The food intake of miscellaneous cereals, beans, tofu, chicken/duck meat, cabbage, carrot/amber, fungi, apple, pear, strawberry, grapes, and banana was significantly higher in the normal group compared with the depression group. In particular, significantly higher intake of vegetables and fruits was observed in the normal group. In addition, subjects in the depression group ate more fatty meat and were more dissatisfied with food-related life than those in the normal group. CONCLUSION: The results of this study imply that the prevalence of depression may affect the dietary habits, food intake, and dietary behaviors in the older adult population.
Adult* ; Appetite ; Brassica ; Edible Grain ; Depression* ; Eating ; Fabaceae ; Female ; Food Habits* ; Fragaria ; Fruit ; Fungi ; Humans ; Korea ; Male ; Meat ; Musa ; Prevalence ; Pyrus ; Surveys and Questionnaires ; Soy Foods ; Vegetables ; Vitis

The Korea Centers for Disease Control and Prevention (KCDC) operate infectious disease surveillance systems to monitor national disease incidence. Since 1954, Korea has collected data on various infectious diseases in accordance with the Infectious Disease Control and Prevention Act. All physicians (including those working in Oriental medicine) who diagnose a patient with an infectious disease or conduct a postmortem examination of an infectious disease case are obliged to report the disease to the system. These reported data are incorporated into the database of the National Infectious Disease Surveillance System, which has been providing web-based real-time surveillance data on infectious diseases since 2001. In addition, the KCDC analyzes reported data and publishes the Infectious Disease Surveillance Yearbook annually.
Autopsy ; Centers for Disease Control and Prevention (U.S.) ; Communicable Diseases* ; Humans ; Incidence ; Korea