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 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

PURPOSE: The purpose of this study was to monitor the use of health-related quality of life (HRQOL) instruments in Korean studies of patients with diabetes. METHODS: Of 86 Korean studies initially identified, 17 studies met the inclusion criteria. For each study, a description of the instrument and its psychometric properties were monitored by the Instrument Review Criteria of the Scientific Advisory Committee. These criteria include conceptual definition, attributes, taxonomy, reliability, validity, responsiveness, administrative mode, and language adaptations. RESULTS: Five generic and one diabetes specific type questionnaires were identified from the 17 studies. Of those studies, conceptual definitions with the attributes of multi-dimension and subjectiveness were provided for 11 studies (71%). In the analysis of conceptual taxonomy, only 6 studies were classified as HRQOL, while other studies were done as QOL or health status. In monitoring of psychometric properties, reliability, validity, and responsiveness were reported for 88.2%, 64.7%, and 29.4%, respectively. One generic instrument was developed with a Korean population, while the other instruments were developed for Western countries. However, language adaptations were performed for only a few of the instruments. CONCLUSION: The psychometric properties including responsiveness of most instruments warrants further research, and the development of diabetes-specific HRQOL measurements should be sought to facilitate intervention outcomes across Korean studies of patients with diabetes.
Diabetes Mellitus/*psychology ; Health Status ; Humans ; Psychometrics ; *Quality of Life ; Questionnaires ; Republic of Korea

BACKGROUND: Chronic low grade inflammation is closely linked to type II diabetes, obesity, and atherosclerosis. Macrophages play a key role in the regulation of pro- or anti-inflammatory actions at the lesion sites of disease. Components of cordyceps militaris, cordycepin and adenosine, have been used for the modulation of inflammatory diseases. The effects of cordycepin in the modulation of macrophages have yet to be elucidated. We investigated the effects of cordycepin and adenosine on the morphological changes of macrophages under the inflammatory condition of LPS and an anti-inflammatory condition involving high concentrations of adenosine. METHODS: We confirmed the mRNA levels of the M1/M2 cytokine genes through RT-PCR and morphological change. RESULTS: LPS-activated macrophages returned to their inactivated original shape, i.e., they looked like naive macrophages, through the treatment with high concentrations of cordycepin (40 microgram/ml). LPS and adenosine activated macrophages also returned to their original inactivated shapes after cordycepin treatment; however, at relatively higher levels of cordycepin than adenosine. This change did not occur with relatively low concentrations of cordycepin. Adenosine down-regulated the gene expression of M1 cytokines (IL-1beta, TNF-alpha) and chemokines (CX3CR1, RANTES), as well as cordycepin. Additionally, M2 cytokines (IL-10, IL-1ra, TGF-beta) were up-regulated by both cordycepin and adenosine. CONCLUSION: Based on these observations, both cordycepin and adenosine regulated the phenotypic switch on macrophages and suggested that cordycepin and adenosine may potentially be used as immunomodulatory agents in the treatment of inflammatory disease.
Adenosine ; Atherosclerosis ; Chemokines ; Cordyceps ; Cytokines ; Deoxyadenosines ; Gene Expression ; Inflammation ; Interleukin 1 Receptor Antagonist Protein ; Macrophages ; Obesity ; RNA, Messenger

BACKGROUND: It has been recently noticed that type 2 diabetes (T2D), one of the most common metabolic diseases, causes a chronic low-grade inflammation and activation of the innate immune system that are closely involved in the pathogenesis of T2D. Cordyceps militaris, a traditional medicinal mushroom, produces a component compound, cordycepin (3'-deoxyadenosine). Cordycepin has been known to have many pharmacological activities including immunological stimulating, anti-cancer, and anti-infection activities. The molecular mechanisms of cordycepin in T2D are not clear. In the present study, we tested the role of cordycepin on the anti-diabetic effect and anti-inflammatory cascades in LPS-stimulated RAW 264.7 cells. METHODS: We confirmed the levels of diabetes regulating genes mRNA and protein of cytokines through RT-PCR and western blot analysis and followed by FACS analysis for the surface molecules. RESULTS: Cordycepin inhibited the production of NO and pro-inflammatory cytokines such as IL-1beta, IL-6, and TNF-alpha in LPS-activated macrophages via suppressing protein expression of pro-inflammatory mediators. T2D regulating genes such as 11beta-HSD1 and PPARgamma were decreased as well as expression of co-stimulatory molecules such as ICAM-1 and B7-1/-2 were also decreased with the increment of its concentration. In accordance with suppressed pro-inflammatory cytokine production lead to inhibition of diabetic regulating genes in activated macrophages. Cordycepin suppressed NF-kappaB activation in LPS-activated macrophages. CONCLUSION: Based on these observations, cordycepin suppressed T2D regulating genes through the inactivation of NF-kappaB dependent inflammatory responses and suggesting that cordycepin will provide potential use as an immunomodulatory agent for treating immunological diseases.
11-beta-Hydroxysteroid Dehydrogenase Type 1 ; Agaricales ; Blotting, Western ; Cordyceps ; Cytokines ; Deoxyadenosines ; Immune System ; Inflammation ; Intercellular Adhesion Molecule-1 ; Interleukin-6 ; Macrophages ; Metabolic Diseases ; NF-kappa B ; PPAR gamma ; RNA, Messenger ; Tumor Necrosis Factor-alpha