• Journal of Dental Anesthesia and Pain Medicine
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• v.21 no.2
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• pp.99-111
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• 2021

Background: Attention deficit hyperactivity disorder (ADHD) is characterized by a persistent pattern of inattention and/or hyperactivity-impulsivity that interferes with functioning or development. It has a worldwide pooled prevalence of 5.29%. The characteristics of ADHD can increase the probability of dental treatment, while special behavior management can be required to allow proper treatment. In South Korea, the use of sedation in dental treatment has rapidly increased in recent decades. The present study aimed to investigate the trend and effects of sedation in patients with ADHD undergoing dental treatment in South Korea. Methods: The study used customized health information data provided by the Korean National Health Insurance Service. Among patients with the record of sedative use during the period from January 2007 to September 2019, those with International Classification of Diseases-10 codes for ADHD (F90, F91) were selected; the data of their overall insurance claims for dental treatment were then analyzed. The patients' age, gender, sedative use, and dental treatment were analyzed per year. The annual number of general anesthesia or sedation cases was also analyzed, and changes in the method of behavior management with increasing age were examined. Results: The study involved 7,654 patients with ADHD (6,270 males; 1,384 females). The total number of dental treatments was 137,778, while the number of sedation cases was 16,109, among which 13,052 involved male patients and 3,057 female patients. The number of general anesthesia cases was 631, among which 538 involved male patients and 93 female patients. The most frequently used sedation method in the dental treatment of patients with ADHD was N2O inhalation. The percentage of sedation cases was highest in patients aged 4 years, and it decreased with increasing age. Conclusion: In South Korea, both sedation and dental treatments were slightly more common in patients with ADHD than in the general population. With increasing age, the frequency of dental treatments and the percentage of sedation cases decreased.

• Journal of Preventive Medicine and Public Health
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• v.55 no.1
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• pp.19-27
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• 2022

This study estimated the direct and indirect socioeconomic costs of 238 diseases and 22 injuries from a social perspective in Korea from 2007 to 2015. The socioeconomic cost of each disease group was calculated based on the Korean Standard Disease Classification System. Direct costs were estimated using health insurance claims data provided by the National Health Insurance Service. The numbers of outpatients and inpatients with the main diagnostic codes for each disease were selected as a proxy indicator for estimating patients' medical use behavior by disease. The economic burden of disease from 2007 to 2015 showed an approximately 20% increase in total costs. From 2007 to 2015, communicable diseases (including infectious, maternal, pediatric, and nutritional diseases) accounted for 8.9-12.2% of the socioeconomic burden, while non-infectious diseases accounted for 65.7-70.7% and injuries accounted for 19.1-22.8%. The top 5 diseases in terms of the socioeconomic burden were self-harm (which took the top spot for 8 years), followed by cirrhosis of the liver, liver cancer, ischemic heart disease, and upper respiratory infections in 2007. Since 2010, the economic burden of conditions such as low back pain, falls, and acute bronchitis has been included in this ranking. This study expanded the scope of calculating the burden of disease at the national level by calculating the burden of disease in Koreans by gender and disease. These findings can be used as indicators of health equality and as useful data for establishing community-centered (or customized) health promotion policies, projects, and national health policy goals.

• Physical Therapy Rehabilitation Science
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• v.11 no.3
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• pp.285-295
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• 2022

Objective: The purpose of this study is to use logistic regression and decision tree analysis to identify the factors that affect the success or failurein the national physical therapy examination; and to build and compare predictive models. Design: Secondary data analysis study Methods: We analyzed 76,727 subjects from the physical therapy national examination data provided by the Korea Health Personnel Licensing Examination Institute. The target variable was pass or fail, and the input variables were gender, age, graduation status, and examination area. Frequency analysis, chi-square test, binary logistic regression, and decision tree analysis were performed on the data. Results: In the logistic regression analysis, subjects in their 20s (Odds ratio, OR=1, reference), expected to graduate (OR=13.616, p<0.001) and from the examination area of Jeju-do (OR=3.135, p<0.001), had a high probability of passing. In the decision tree, the predictive factors for passing result had the greatest influence in the order of graduation status (x²=12366.843, p<0.001) and examination area (x²=312.446, p<0.001). Logistic regression analysis showed a specificity of 39.6% and sensitivity of 95.5%; while decision tree analysis showed a specificity of 45.8% and sensitivity of 94.7%. In classification accuracy, logistic regression and decision tree analysis showed 87.6% and 88.0% prediction, respectively. Conclusions: Both logistic regression and decision tree analysis were adequate to explain the predictive model. Additionally, whether actual test takers passed the national physical therapy examination could be determined, by applying the constructed prediction model and prediction rate.

• Journal of The Korean Society of Clinical Toxicology
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• v.20 no.2
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• pp.45-50
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• 2022

Purpose: This study utilizes the NEDIS (National Emergency Department Information System) database to suggest a predictive model for snakebite and envenomation in Korea by analyzing the geographical distribution and seasonal variation of snakebite patients visiting the ER. Methods: This was a retrospective study on snakebite patients visiting the ER using the NEDIS database from January 2014 to December 2019. The subjects include patients with the KCD (Korea Standard Classification of Disease) disease code T63.0 (Toxic effect of contact with snake venom). Geographical location, patient gender, patient age, date of ER visit, treatment during the ER stay, and disposition were recorded to analyze the geographical distribution and seasonal variation of snakebite patients in Korea. Results: A total of 12,521 patients were evaluated in this study (7,170 males, 54.9%; 5,351 females, 40.9%). The average age was 58.5±17.5 years. In all, 7,644 patients were admitted with an average admission time of 5.04±4.7 days, and 2 patients expired while admitted. The geographical distribution was Gyeongsang 3,370 (26.9%), Cheonra 2,692 (21.5%), Chungcheong 2,667 (21.3%), Seoul Capital area 1,999 (16.0%), Kangwon 1,457 (11.6%), and Jeju 336 (2.7%). The seasonal variation showed insignificant incidences in winter and higher severity in spring and summer than in fall: winter 27 (0.2%), spring 2,268 (18.1%), summer 6,847 (54.7%), and fall 3,380 (27.0%). Conclusion: Patients presenting with snakebites and envenomation in the emergency room were most common in the Gyeongsang area and during summer. The simple seasonal model predicted that 436 snakebites and 438 envenomation cases occurred in July and August. The results of this study can be applied to suitably distribute and stock antivenom. Appropriate policies can be formed to care for snakebite patients in Korea.

• Journal of Sasang Constitutional Medicine
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• v.34 no.1
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• pp.37-45
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• 2022

Objectives The purpose of this study was to reveal that Sasang constitution(SC) was associated with hypertension and pre-hypertension and could be a risk factor. Methods We introduced this study to educational personnel in D university in Daejeon, and 275 subjects joined this study. The SC classification was conducted with KS 15 questionnaire. The subjected measured the blood pressure with Jawon medical device automatically after 10 minute rest. The hypertension and pre-hypertension was classified by the guide of the Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure. The frequency analysis and T-test was used in general characteristics, and chi-square test was also used between SC and pre-hypertension and hypertension. Logistic regression was used to calculate the odds ratios (ORs) and 95% confidence interval (95% CI) for pre-hypertension and hypertension. Results The number of Taeeumin(TE), Soeumin(SE), and Soyangin(SY) was 142, 71, and 61 respectively. There was significantly different in systolic and diastolic blood pressure among SC types(p<.001). The distribution of the normal group, pre-hypertension and hypertension group by SC types was significantly different (p<.001). The ORs of TE was significantly increased (ORs 4.039, 95% CI=2.019-8.082 in pre-hypertension and ORs 4.235, 95% CI=1.581-11.348 in hypertension) compared with SE(p<.001), and after adjusting gender and smoking habit, it was still significantly different(p<.001). Conclusions It is possible that SC, especially TE could be a risk factor both pre-hypertension and hypertension.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1431-1445
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• 2022

We construct a deep neural network model named ECGResNet. This model can diagnosis diseases based on 12-lead ECG data of eight common cardiovascular diseases with a high accuracy. We chose the 16 Blocks of ResNet50 as the main body of the model and added the Squeeze-and-Excitation module to learn the data information between channels adaptively. We modified the first convolutional layer of ResNet50 which has a convolutional kernel of 7 to a superposition of convolutional kernels of 8 and 16 as our feature extraction method. This way allows the model to focus on the overall trend of the ECG signal while also noticing subtle changes. The model further improves the accuracy of cardiovascular and cerebrovascular disease classification by using a fully connected layer that integrates factors such as gender and age. The ECGResNet model adds Dropout layers to both the residual block and SE module of ResNet50, further avoiding the phenomenon of model overfitting. The model was eventually trained using a five-fold cross-validation and Flooding training method, with an accuracy of 95% on the test set and an F1-score of 0.841.We design a new deep neural network, innovate a multi-scale feature extraction method, and apply the SE module to extract features of ECG data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.329-331
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• 2021

Recently, as various cases of using deep learning in the health-care field are increasing, functions such as electrocardiogram examination and body composition analysis through wearable device can be provided to provide rational decision-making and a process tailored to the individual. In order to utilize deep learning, it it most important to secure refined data, and this data is being made through human intervention or unsupervised learning. In this paper, we propose a model that conducts unsupervised learning by clusters according to gender and age using human body data such as chest and waist circumferences, which are easy to measure, and classifies them with CNN. For data, the 7th human body data provided by Korean Agency for Technology and Standards was used. Through this, it it thought that it can be applied to various application cases such as personalized body shape management service and obesity analysis.

• Journal of Practical Engineering Education
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• v.16 no.2
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• pp.227-239
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• 2024

This study aims to analyze the impact of vocational training received by learning workers through the degree-linked work-study program on their learning outcomes. Specifically, we explore the causal relationship between various factors considered during university degree program admission and selection, and the average GPA (Grade Point Average) after admission. To achieve this, we conducted regression analysis and variance analysis using historical admission data and GPA records of 976 students from three undergraduate programs at a domestic K university that implements the degree-linked work-study model. Additionally, we included company information from publicly available databases that could potentially influence the academic performance of learning workers. Our analysis revealed significant causal relationships across various factors, including the classification of the high school attended, gender, family background, subject-specific grades in high school, duration of employment at the company, and age at the time of admission. Based on these findings, we anticipate that universities operating similar degree programs can enhance their selection procedures for learning workers. Furthermore, the results of this study can serve as foundational data for future policy recommendations related to degree-linked work-study programs.

• Journal of Digital Convergence
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• v.22 no.1
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• pp.23-32
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• 2024

This study selected in-depth discharge damage survey data and analyzed 92,364 patients whose main diagnosis was S00-T98 (damage, addiction, and specific other results due to external factors) based on the Korean Standard Classification of Diseases and Deaths (KCD-7th) among patients discharged from the hospital after inpatient treatment from January 2016 to December 2018. As a result of analyzing the general characteristics of injured and traumatic patients, the incidence rate of men was higher in gender, and the incidence rate of women increased as the year increased. As a result of analyzing the characteristics of injury and trauma patients other than injury, the injury intention had a high rate of unintentional damage, the damage place was the highest on the road/road, and it showed a decreasing trend as the year increased, and it showed an increasing trend in the residential area. It can be used as basic data for the establishment of a related system to prevent damage as a result of subsang.

• Korean Journal of Clinical Pharmacy
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• v.34 no.3
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• pp.194-201
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• 2024

Background: Asthma is a chronic inflammatory airway disease associated with systemic inflammation and increased prevalence of various comorbid conditions. This study investigates the prevalence of non-respiratory comorbidities among adult asthma patients in South Korea, aiming to elucidate potential correlations and impacts of asthma on overall health, thereby affecting patients' quality of life and healthcare systems. Methods: This retrospective cohort study utilized the National Health Insurance Service data (HIRA-NPS-2020) and included adults diagnosed with asthma. Non-respiratory diseases were identified using the Korean Standard Disease Classification (KCD-8) codes, with exclusions applied for other respiratory conditions. The prevalence of comorbidities was analyzed and compared between asthma and non-asthma patients, adjusting for confounders such as age, gender, and insurance status through inverse probability treatment weighting (IPTW). Results: The analysis revealed that asthma patients exhibit significantly higher rates of cardiovascular diseases, metabolic disorders, gastrointestinal conditions, and mental health issues compared to the control group. Notably, conditions such as heart failure, gastroesophageal reflux disease, and anxiety were more prevalent, with odds ratios (OR) ranging from 1.18 to 3.90. These results demonstrate a substantial burden of comorbidities associated with asthma, indicating a broad impact on health beyond the respiratory system. Conclusion: The findings highlight the systemic nature of asthma and the interconnectedness of inflammatory processes across different organ systems. This comprehensive analysis confirms previous research linking asthma with an increased risk of various non-respiratory diseases, providing insights into the multifaceted impact of asthma on patient health.