• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.126-136
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• 2018

The purpose of this study was to develop a severity-adjustment model for predicting mortality in acute stroke patients using machine learning. Using the Korean National Hospital Discharge In-depth Injury Survey from 2006 to 2015, the study population with disease code I60-I63 (KCD 7) were extracted for further analysis. Three tools were used for the severity-adjustment of comorbidity: the Charlson Comorbidity Index (CCI), the Elixhauser comorbidity index (ECI), and the Clinical Classification Software (CCS). The severity-adjustment models for mortality prediction in patients with acute stroke were developed using logistic regression, decision tree, neural network, and support vector machine methods. The most common comorbid disease in stroke patients were hypertension, uncomplicated (43.8%) in the ECI, and essential hypertension (43.9%) in the CCS. Among the CCI, ECI, and CCS, CCS had the highest AUC value. CCS was confirmed as the best severity correction tool. In addition, the AUC values for variables of CCS including main diagnosis, gender, age, hospitalization route, and existence of surgery were 0.808 for the logistic regression analysis, 0.785 for the decision tree, 0.809 for the neural network and 0.830 for the support vector machine. Therefore, the best predictive power was achieved by the support vector machine technique. The results of this study can be used in the establishment of health policy in the future.

• Perspectives in Nursing Science
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• v.10 no.1
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• pp.52-64
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• 2013

Purpose: The purpose of this study was to explore the utilization of health care of patients with lung cancer in Korea and identify determinants of these patients' health care utilization. Methods: This was a descriptive analytical study. The national medical fees claims data of patients with lung cancer were used. Using SPSS Statistics 20, the ${\chi}^2$-test and logistic regression were performed to determine the factors influencing health care utilization. Results: There were significant differences by sex, age, disease type, stage, comorbidity index, region of institutions, and type of institutions in the utilization of surgical procedures; by age, disease type, stage, comorbidity index, region of institutions, and type of institutions in the utilization of chemotherapy; and by age, stage, comorbidity index, region of institutions, and type of institutions in the utilization of radiotherapy. Conclusion: The findings of this study suggest that democratic and clinical characteristics of patients as well as institutional characteristics affect health care utilization of patients with lung cancer. Additional research is needed to determine the factors influencing health care utilization of patients with lung cancer.

• Journal of Digital Convergence
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• v.17 no.2
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• pp.217-230
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• 2019

This study was conducted to develop a customized severity-adjustment method and to evaluate their validity for acute myocardial infarction(AMI) patients to complement the limitations of the existing severity-adjustment method for comorbidities. For this purpose, the subjects of KCD-7 code I20.0 ~ I20.9, which is the main diagnosis of acute myocardial infarction were extracted using the Korean National Hospital Discharge In-depth Injury survey data from 2006 to 2015. Three tools were used for severity-adjustment method of comorbidities : CCI (charlson comorbidity index), ECI (Elixhauser comorbidity index) and the newly proposed CCS (Clinical Classification Software). The results showed that CCS was the best tool for the severity correction, and that support vector machine model was the most predictable. Therefore, we propose the use of the customized method of severity correction and machine learning techniques from this study for the future research on severity adjustment such as assessment of results of medical service.

• Korean Journal of Psychosomatic Medicine
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• v.24 no.1
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• pp.74-82
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• 2016

Objectives : Suicide attempters have impaired decision making and are at high risk of reattempt. Therefore it is important to refer them to psychiatric treatment. Especially, People with medical comorbidity are at higher risk of suicidal attempt and mortality. The aim of this study was to investigate the characteristics of suicidal attempters and to analyze the influence of the medical comorbidity on decision to receive psychiatric treatment after visit to an emergency department. Methods : One hundred and thirty two patients, who visited the emergency room of a general hospital in Gyeonggi-do between January, 2012 and December, 2012 were enrolled as the subjects of this study. After reviewing each subject's medical records retrospectively, demographic and clinical factors were analyzed. Results : Regardless of the engagement type, either via admission or outpatient clinic, the determinant factors of psychiatric treatment engagement were psychiatric diagnosis, employment status, previous psychiatric treatment history, and previous attempt history. Comparison of severity of medical comorbidity(Charlson Comorbidity Index) showed that suicide attempters who received psychiatric treatment via admission or refused the treatment tended to have higher level of medical comorbidity than who received psychiatric treatment via outpatient department. Conclusions : Our findings showed that medical comorbidity of suicide attempters affected the decision to accept psychiatric treatment. All psychiatrists should evaluate the presence and the severity of medical comorbidity of the suicide attempters and consider implementing more intervention for the medically ill attempters who are willing to discharge against advice.

• Korean Journal of Biological Psychiatry
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• v.16 no.1
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• pp.37-45
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• 2009

Objectives : It is reported that panic disorder is frequently comorbid with other psychiatric illnesses. The aim of this study was to investigate differences of psychiatric comorbidity according to age of onset of panic disorder. Methods : Three hundred-two patients participated in the study. All the patients were evaluated by clinical instruments for the assessment the presence of other comorbid psychiatric disorders and various clinical features; Korean version of Mini International Neuropsychiatric Interview, Self-report questionnaires(Beck Anxiety Inventory, Beck Depression Inventory, Anxiety Sensitivity Index and State-Trait Anxiety Inventory) and clinical rating scale (Hamilton Anxiety Scale, Hamilton Depression Scale and Global Assessment of Functional score). Chi-square test was used to determine the difference between early onset and late onset panic disorder. Results : Forty percent of panic patients were found to have at least one comorbid psychiatric diagnosis. There were no differences among the groups divided by number of comorbidity in sex, agoraphobia comorbidity, duration of panic disorder, except onset age of panic disorder. Early onset group had more comorbidy with social phobia, agoraphobia, PTSD. We also found that Early onset panic disorder patients were more likely to experience derealization, nausea, parethesia than late onset panic disorder patients. Conclusion : The results of our study are in keeping with previous data from other parts of the world. Our finding suggest that earier onset of panic disorder related to more psychiatric comorbidity.

• Journal of Periodontal and Implant Science
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• v.48 no.2
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• pp.92-102
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• 2018

Purpose: This study investigated the validity of the Charlson comorbidity index (CCI) as a predictor of periodontal disease (PD) over a 12-year period. Methods: Nationwide representative samples of 149,785 adults aged ${\geq}60$ years with PD (International Classification of Disease, 10th revision [ICD-10], K052-K056) were derived from the National Health Insurance Service-Elderly Cohort during 2002-2013. The degree of comorbidity was measured using the CCI (grade 0-6), including 17 diseases weighted on the basis of their association with mortality, and data were analyzed using multivariate Cox proportional-hazards regression in order to investigate the associations of comorbid diseases (CDs) with PD. Results: The multivariate Cox regression analysis with adjustment for sociodemographic factors (sex, age, household income, insurance status, residence area, and health status) and CDs (acute myocardial infarction, congestive heart failure, peripheral vascular disease, cerebral vascular accident, dementia, pulmonary disease, connective tissue disorders, peptic ulcer, liver disease, diabetes, diabetes complications, paraplegia, renal disease, cancer, metastatic cancer, severe liver disease, and human immunodeficiency virus [HIV]) showed that the CCI in elderly comorbid participants was significantly and positively correlated with the presence of PD (grade 1: hazard ratio [HR], 1.11; P<0.001; grade ${\geq}2$: HR, 1.12, P<0.001). Conclusions: We demonstrated that a higher CCI was a significant predictor of greater risk for PD in the South Korean elderly population.

• Journal of Korean Neurosurgical Society
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• v.64 no.6
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• pp.995-1003
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• 2021

Objective : People are living longer and the elderly population continues to increase. The incidence of degenerative spinal diseases (DSDs) in the elderly population is quite high. Therefore, we are facing more cases of DSD and offering more surgical solutions in geriatric patients. Understanding the significance and association of frailty and central sarcopenia as risk factors for spinal surgery in elderly patients will be helpful in improving surgical outcomes. We conducted a retrospective cohort analysis of prospectively collected data to assess the impact of preoperative central sarcopenia, frailty, and comorbidity on surgical outcome in elderly patients with DSD. Methods : We conducted a retrospective analysis of patients who underwent elective spinal surgery performed from January 1, 2019 to September 30, 2020 at our hospital. We included patients aged 65 and over who underwent surgery on the thoracic or lumbar spine and were diagnosed as DSD. Central sarcopenia was measured by the 50th percentile of psoas : L4 vertebral index (PLVI) using the cross-sectional area of the psoas muscle. We used the Korean version of the fatigue, resistance, ambulation, illnesses, and loss of weight (K-FRAIL) scale to measure frailty. Comorbidity was confirmed and scored using the Charlson Comorbidity Index (CCI). As a tool for measuring surgical outcome, we used the Clavien-Dindo (CD) classification for postoperative complications and the length of stay (LOS). Results : This study included 85 patients (35 males and 50 females). The mean age was 74.05±6.47 years. Using the K-FRAIL scale, four patients were scored as robust, 44 patients were pre-frail and 37 patients were frail. The mean PLVI was 0.61±0.19. According to the CD classification, 50 patients were classified as grade 1, 19 as grade 2, and four as grade 4. The mean LOS was 12.35±8.17 days. Multivariate stepwise regression analysis showed that postoperative complication was significantly associated with surgical invasiveness and K-FRAIL scale. LOS was significantly associated with surgical invasiveness and CCI. K-FRAIL scale showed a significant correlation with CCI and PLVI. Conclusion : The present study demonstrates that frailty, comorbidity, and surgical invasiveness are important risk factors for postoperative complications and LOS in elderly patients with DSD. Preoperative recognition of these factors may be useful for perioperative optimization, risk stratification, and patient counseling.

• Journal of Preventive Medicine and Public Health
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• v.43 no.1
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• pp.42-49
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• 2010

Objectives: To compare the performance of three International Statistical Classification of Diseases, 10th Revision translations of the Charlson comorbidities when predicting in-hospital among patients with myocardial infarction (MI). Methods: MI patients ${\geq}20$ years of age with the first admission during 2006 were identified(n=20,280). Charlson comorbidities were drawn from Heath Insurance Claims Data managed by Health Insurance Review and Assessment Service in Korea. Comparisions for various conditions included (a) three algorithms (Halfon, Sundararajan, and Quan algorithms), (b) lookback periods (1-, 3- and 5-years), (c) data range (admission data, admission and ambulatory data), and (d) diagnosis range (primary diagnosis and first secondary diagnoses, all diagnoses). The performance of each procedure was measured with the c-statistic derived from multiple logistic regression adjusted for age, sex, admission type and Charlson comorbidity index. A bootstrapping procedure was done to determine the approximate 95% confidence interval. Results: Among the 20,280 patients, the mean age was 63.3 years, 67.8% were men and 7.1% died while hospitalized. The Quan and Sundararajan algorithms produced higher prevalences than the Halfon algorithm. The c-statistic of the Quan algorithm was slightly higher, but not significantly different, than that of other two algorithms under all conditions. There was no evidence that on longer lookback periods, additional data, and diagnoses improved the predictive ability. Conclusions: In health services study of MI patients using Health Insurance Claims Data, the present results suggest that the Quan Algorithm using a 1-year lookback involving primary diagnosis and the first secondary diagnosis is adequate in predicting in-hospital mortality.

• Journal of Preventive Medicine and Public Health
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• v.42 no.2
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• pp.117-122
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• 2009

Objectives : We tried to evaluate the agreement of the Charlson comorbidity index values(CCI) obtained from different sources(medical records and National Health Insurance claims data) for gastric cancer patients. We also attempted to assess the prognostic value of these data for predicting 1-year mortality and length of the hospital stay(length of stay). Methods : Medical records of 284 gastric cancer patients were reviewed, and their National Health Insurance claims data and death certificates were also investigated. To evaluate agreement, the kappa coefficient was tested. Multiple logistic regression analysis and multiple linear regression analysis were performed to evaluate and compare the prognostic power for predicting 1 year mortality and length of stay. Results : The CCI values for each comorbid condition obtained from 2 different data sources appeared to poorly agree(kappa: 0.00-0.59). It was appeared that the CCI values based on both sources were not valid prognostic indicators of 1-year mortality. Only medical record-based CCI was a valid prognostic indicator of length of stay, even after adjustment of covariables($\beta$ = 0.112, 95% CI = [0.017-1.267]). Conclusions : There was a discrepancy between the data sources with regard to the value of CCI both for the prognostic power and its direction. Therefore, assuming that medical records are the gold standard for the source for CCI measurement, claims data is not an appropriate source for determining the CCI, at least for gastric cancer.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.34 no.4
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• pp.275-282
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• 2023

Objectives: This study aimed to identify the psychiatric comorbidity status of adult patients diagnosed with attention-deficit hyperactivity disorder (ADHD) and determine the impact of comorbidities on neuropsychological outcomes in ADHD. Methods: The study participants were 124 adult patients with ADHD. Clinical psychiatric assessments were performed by two board-certified psychiatrists in accordance with the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. All participants were assessed using the Mini-International Neuropsychiatric Interview Plus version 5.0.0 to evaluate comorbidities. After screening, neuropsychological outcomes were assessed using the Comprehensive Attention Test (CAT) and the Korean version of the Wechsler Adult Intelligence Scale, Fourth Edition (K-WAIS-IV). Results: Mood disorders (38.7%) were the most common comorbidity of ADHD, followed by anxiety (18.5%) and substance use disorders (13.7%). The ADHD with comorbidities group showed worse results on the Perceptual Organization Index and Working Memory Index sections of the K-WAIS than the ADHD-alone group (p=0.015 and p=0.024, respectively). In addition, the presence of comorbidities was associated with worse performance on simple visual commission errors in the CAT tests (p=0.024). Conclusion: These findings suggest that psychiatric comorbidities are associated with poor neuropsychological outcomes in adult patients with ADHD, highlighting the need to identify comorbidities in these patients.