• Journal of Preventive Medicine and Public Health
• /
• v.30 no.4 s.59
• /
• pp.764-778
• /
• 1997

To find the medical insurance utilization of workers when suffering from low back pain, an analysis was made toward the data of medical insurance benefits matched with the general characteristics of 10,183 workers, who were registered continuously from 1993 to 1995 at a medical insurance cooperation for industrial workers. The results were as follows; 1. The period prevalence of the medical insurance utilization for low back pain for 3 years from 1993 to 1995 was calculated as 17.1% for male workers and 19.4% for female workers. Most common cause of utilization was other dorsopathies including the herniation of lumbar discs. 2. The utilization rate increased significantly as the present age and the age joining the company got older(p<0.001). As the duration of employment got longer, the utilization rate of the male showed the tendency to increase and that of the female increased significantly(p<0.05). Among male workers employed at cement and concrete manufacturing companies showed higher utilization rate and among female laborers showed significantly higher utilization rate than clerical workers(p<0.01). 3. Annual utilization rate for low back pain didn't show any difference, but the portion of other dorsopathies among cause of utilization showed the tendency to increase from 1993 to 1995. 4. The mean number of claims for outpatient medical care for low back pain differed significantly by age, working duration, type of industries, income level(p<0.05), and the mean of total visiting days for care of low back pain differed significantly by working duration. In conclusion, considering the fact that the medical insurance utilization for low back pain increased annually and other dorsopathies including the herniation of dorsopathies were increasing, an effective preventive or management program for low back pain toward worker employed at industries were required.

• Pediatric Infection and Vaccine
• /
• v.13 no.2
• /
• pp.147-155
• /
• 2006

Purpose : The purpose of this study is to evaluate epidemiological data of pathogens obtained from stool exams and compare them with the clinical course in pediatric patients with symptoms of acute gastroenteritis. Methods : Subjects were selected from patients presenting with symptoms of acute gastroenteritis who visited the outpatient clinic or who were admitted to the Dankook University Hospital from December of 2004 to December of 2005. Stool exams for 17 pathogens was performed. RT-PCR was used to detect norovirus and enzyme-linked immunoabsorbant assay (ELISA) was used to detect rotavirus, adenovirus and astrovirus in the subjects stool samples. Ten different species of bacteria(Salmonella spp., Shigella spp., Clostridium perfrigens, Campylobacter spp., Escherichia coli, Vibrio spp., Staphylococcus aureus, Bacillus cereus, Yersinia spp., and L. monocytogenes) were each selectively cultivated and enzyme immunoassays(EIA) was used to test for antigens for C. parvum, E. histolytica and G. lamblia. Retrospective chart review was performed for comparisons of clinical manifestations. Results : A total of 215 subjects was selected and of these 89 cases(41.4%) showed positive results for at least one pathogen. Male to female ratio was 1.3:1. Age distribution showed 4 cases less than one month(4.5%), 4 cases from 1~2 months(4.5%), 24 cases from 3~12 months(26.7%), 47 cases form 13~48 months(52.8%), 10 cases greater than 48 months (21.2%). Viruses showed the greatest proportion of cases with 68 subjects(77.5%), of these rotavirus being the most commonly reported in 50 cases. Bacteria was identified in 26 cases (29.2%), of these nontyphoidal salmonella was noted in 10 cases. Protozoa followed with 21 cases(23.6%), of these C. parvum was noted in 11 cases and G. lamblia was noted in 10 cases. Mixed infections with more than two pathogens were seen in 22 cases(24.7%), of these viral infection with accompanying parasitic infection was seen in 12(54.5%) cases. Conclusion : In this study we examined various pathogens known to cause acute gastroenteritis in children. Further studies for various pathogens can provide useful information for management of the acute gastroenteritis.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
• /
• v.10 no.2
• /
• pp.212-219
• /
• 1999

Objective：This study is designed to get clinical guidelines for management of children with TBI by examining neuropsychiatric sequelae of TBI, determining whether the severity of TBI, type of treatment, and enviornmental factors are related to those sequelae, and defining the adequacy of public psychological tests as evaluating tools for them. Method：This is chart review of 47 children, aged 5 to 14 years, referred to a psychiatric outpatient clinic for neuropsychiatric evaluation at least 6 months after TBI. Data on the initial GCS score, associated injury, treatment type, and duration of hospital stay are obtained from medical records. EEG, MRI, intelligent test, and several psychological tests are administrated at the point of assessment. Results：1) Cognitive symptoms outnumber externalizing behavioral, emotional, and somatic symptoms, with no significant differences of frequencies of those 4 categorical symptoms between mild injury group and moderate to severe group. 2) Children treated with non-surgical method(p<0.01) complain more cognitive symptoms than the others. 3) Behavioral symptoms are related to younger age(p<0.05), and to anticonvulsant medication(p<0.05). 4) Children with associated injury complain emotional symptoms more frequently(p<0.05). 5) More somatic symptoms are presented by children with no medication(p<0.05), and with higher I.Q(p<0.05). 6) Low I.Q is correlated to low GCS score (p<0.05). Cognitive impairment is confirmed in 25 in 42 children complaining cognitive symptoms though I.Q test and BGT, whose hospital stay is longer than the others(p<0.05). 7) emotional disturbance is confirmed in 22 in 25 children showing emotional problems through psychological tests, who complain cognitive symptoms more frequently(p<0.05). Conclusion：This findings suggest that even mild TBI children need to be followed-up and treated as complaining neuropsychiatric symptoms over 6 months after injury, and shorter hospital stay is recommended for cognitive and emotional status of children, and for better evaluation of neuropsychiatric sequelae of TBI, more specific tests should be included in neuropsychological test tools.

• Journal of the korean academy of Pediatric Dentistry
• /
• v.37 no.1
• /
• pp.65-72
• /
• 2010

General anesthesia has been researched and developed in dentistry as on type of management technique to sedate patients who may be uncontrollable or require medical consideration. There has been continuous research into this area, but analysis of large set of patients over a sustained period of time is lacking. Thus, this study analyzes the records of patients who received general anesthesia at the Yonsei University Dental Hospital Department of Pediatric and Clinic for the Disabled. 1. Patient's age ranged from 1 to 66, with under 5 being the largest group with 410 members(38.5%). The study included more men than women, with 695 male members(65.3%). 2. Type of dental procedure performed were as follows(per person) : 5.6 Dental restoration; 2.3 Endodontic treatment of deciduous and primary teeth; 2.5 preformed crowning; and 1.6 extractions. Procedures took an average of 100 minutes. 3. 1022 patients(95.9%) received dental care under general anesthesia once and 43 patients(4.1%) received dental care under general anesthesia two or more times. Dentistry under general anesthesia has the many benefit. However, without appropriate post-treatment care, it is difficult to maintain good oral health. Therefore, it is important to improve the efficiency and safety of general anesthesia through future research.

• Journal of Food Hygiene and Safety
• /
• v.36 no.1
• /
• pp.68-76
• /
• 2021

Foodborne outbreaks frequently occur worldwide and result in huge economic losses. It is the therefore important to estimate the costs associated with foodborne diseases to minimize the economic damage. At the same time, it is difficult to accurately estimate the economic loss from foodborne disease due to a wide variety of cost components. In Korea, there are a limited number of analytical studies attempting to estimate such costs. In this study we investigated the components of economic cost used in foreign countries to better estimate the cost of foodborne disease in Korea. Seven recent studies investigated the cost components used to estimate the cost of foodborne disease in humans. This study categorized the economic loss into four types of cost: direct costs, indirect costs, food business costs, and government administration costs. The healthcare costs most often included were medical (outpatient) and hospital costs (inpatient). However, these cost components should be selected according to the systems and budgets of medical services by country. For non-healthcare costs, several other studies considered transportation costs to the hospital as an exception to the cost of inpatient care. So, further discussion is needed on whether to consider inpatient care costs. Among the indirect costs, premature mortality, lost productivity, lost leisure time, and lost quality of life/pain, grief and suffering costs were considered, but the opportunity costs for hospital visits were not considered in any of the above studies. As with healthcare costs, government administration costs should also be considered appropriate cost components due to the difference in government budget systems, for example. Our findings will provide fundamental information for economic analysis associated with foodborne diseases to improve food safety policy in Korea.

• The Journal of the Society of Stroke on Korean Medicine
• /
• v.11 no.1
• /
• pp.9-17
• /
• 2010

Objectives : This study was aimed to evaluate the current status of East-West integrated treatment in stroke and brain disease and to discuss further plans. Methods : The medical records of patients who visited the stroke and brain disease center at Kyung Hee University, East-West Neo Medical Center from May 2006 to August 2010 were evaluated. The general characteristics of patients who underwent integrated treatment, trend in the number of cross referrals were initially evaluated. Later major disorders, the reasons of referrals and the number of visits in outpatients were analyzed. Results : 1. 3496 patients were referred from the eastern medical hospital to the western medical hospital and 2440 patients from the western medical hospital to the eastern medical hospital. The number of patients reached a peak alter the opening of the hospital and has decreased from then on. Referrals of female patients were more than those of male patients and patients over 50 years old were the most. 2. Admitted patients with stroke of chronic stage were most commonly referred from the eastern medical hospital to the western medical hospital and cerebral infarction was most common from the western medical hospital to the eastern medical hospital. Among the outpatients cerebral infarction topped from east to west, and stroke of chronic stage from west to east. 3. 36.6% of the patients from east to west received integrated treatment more than 3 times and 28.6% from west to east. Headache was the second most common reason to be referred from west to east and 36.7% of patients didn't continue to have either of the treatment and 30.3% received eastern treatment only, Conclusions: According to this study, chronic stroke management was successfully performed in the outpatient clinic in the form of East-West integration treatment. Further research on other diseases such as headache is recommended.

• Journal of Intelligence and Information Systems
• /
• v.24 no.2
• /
• pp.111-124
• /
• 2018

This study aims to develop a classification model for predicting the occurrence of hyperlipidemia, one of the chronic diseases. Prior studies applying data mining techniques for predicting disease can be classified into a model design study for predicting cardiovascular disease and a study comparing disease prediction research results. In the case of foreign literatures, studies predicting cardiovascular disease were predominant in predicting disease using data mining techniques. Although domestic studies were not much different from those of foreign countries, studies focusing on hypertension and diabetes were mainly conducted. Since hypertension and diabetes as well as chronic diseases, hyperlipidemia, are also of high importance, this study selected hyperlipidemia as the disease to be analyzed. We also developed a model for predicting hyperlipidemia using SVM and meta learning algorithms, which are already known to have excellent predictive power. In order to achieve the purpose of this study, we used data set from Korea Health Panel 2012. The Korean Health Panel produces basic data on the level of health expenditure, health level and health behavior, and has conducted an annual survey since 2008. In this study, 1,088 patients with hyperlipidemia were randomly selected from the hospitalized, outpatient, emergency, and chronic disease data of the Korean Health Panel in 2012, and 1,088 nonpatients were also randomly extracted. A total of 2,176 people were selected for the study. Three methods were used to select input variables for predicting hyperlipidemia. First, stepwise method was performed using logistic regression. Among the 17 variables, the categorical variables(except for length of smoking) are expressed as dummy variables, which are assumed to be separate variables on the basis of the reference group, and these variables were analyzed. Six variables (age, BMI, education level, marital status, smoking status, gender) excluding income level and smoking period were selected based on significance level 0.1. Second, C4.5 as a decision tree algorithm is used. The significant input variables were age, smoking status, and education level. Finally, C4.5 as a decision tree algorithm is used. In SVM, the input variables selected by genetic algorithms consisted of 6 variables such as age, marital status, education level, economic activity, smoking period, and physical activity status, and the input variables selected by genetic algorithms in artificial neural network consist of 3 variables such as age, marital status, and education level. Based on the selected parameters, we compared SVM, meta learning algorithm and other prediction models for hyperlipidemia patients, and compared the classification performances using TP rate and precision. The main results of the analysis are as follows. First, the accuracy of the SVM was 88.4% and the accuracy of the artificial neural network was 86.7%. Second, the accuracy of classification models using the selected input variables through stepwise method was slightly higher than that of classification models using the whole variables. Third, the precision of artificial neural network was higher than that of SVM when only three variables as input variables were selected by decision trees. As a result of classification models based on the input variables selected through the genetic algorithm, classification accuracy of SVM was 88.5% and that of artificial neural network was 87.9%. Finally, this study indicated that stacking as the meta learning algorithm proposed in this study, has the best performance when it uses the predicted outputs of SVM and MLP as input variables of SVM, which is a meta classifier. The purpose of this study was to predict hyperlipidemia, one of the representative chronic diseases. To do this, we used SVM and meta-learning algorithms, which is known to have high accuracy. As a result, the accuracy of classification of hyperlipidemia in the stacking as a meta learner was higher than other meta-learning algorithms. However, the predictive performance of the meta-learning algorithm proposed in this study is the same as that of SVM with the best performance (88.6%) among the single models. The limitations of this study are as follows. First, various variable selection methods were tried, but most variables used in the study were categorical dummy variables. In the case with a large number of categorical variables, the results may be different if continuous variables are used because the model can be better suited to categorical variables such as decision trees than general models such as neural networks. Despite these limitations, this study has significance in predicting hyperlipidemia with hybrid models such as met learning algorithms which have not been studied previously. It can be said that the result of improving the model accuracy by applying various variable selection techniques is meaningful. In addition, it is expected that our proposed model will be effective for the prevention and management of hyperlipidemia.