• Korean Journal of Community Nutrition
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• v.15 no.2
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• pp.275-283
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• 2010

There are few studies reporting optimal waist circumference that can be utilized to prevent the incidence of cardiovascular disease (CVD). We evaluated the association of waist circumference and waist and hip circumference ratio (WHR) with incident cases of CVD developed over 6 years in a population-based prospective study including Korean adults. Analyses for receiver-operating characteristic (ROC) curve were performed with data for 1,733 men and 1,579 women who were aged 40 to 69 years and were free of a physician-diagnosis of CVD at baseline. Information on the diagnosis of CVD was periodically reported using interviewer-administered questionnaires and anthropometric measures were obtained by biennial health examinations. We newly identified 77 cases of CVD during a follow-up period between 2003 and 2008. On the basis of measures of diagnostic accuracy including minimum distance to ROC curve and Youden index, waist circumference of 85 cm for men, in particular for male nonsmokers, and of 80 cm for women and WHR of 0.88 to 0.90 for men and of 0.83 for women were found to be optimal cutoff points to identify individuals at CVD risks. The study also found that the use of the suggested optimal values for waist circumference show higher sensitivity and lower specificity compared with 90 cm for men and 85 cm for women, which are waist cutoff points given by the Korean Society for the Study of Obesity to define abdominal obesity for Korean adults. Although lower cutoff points of waist circumference (83 cm) and WHR (0.87) were observed to be optimal for male smokers compared with male nonsmokers, whether suggesting waist cutoff points specific to smokers is needed warrants further studies. After taking into account other cardiovascular risk factors including smoking, men with waist circumference of 85 cm or greater and women with 80 cm or greater were at an increased risk of CVD. Thus, these cutoff points of waist circumference may be able to capture more individuals at CVD risks contributing to the prevention of future development of CVD.

• Proceedings of the KAIS Fall Conference
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• 2012.05a
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• pp.22-24
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• 2012

The tools that classify the severity of patients based on the prediction of mortality include APACHE, SAPS, and MPM. Theses tools rely crucially on the evaluation of patients' general clinical status on the first date of their admission to ICU. Nursing activities are one of the most crucial factors influencing on the quality of treatment that patients receive and one of the contributing factors for their prognosis and safety. The purpose of this study was to identify the goodness-of-fit of CPSCS of critical patient severity classification system(CPSCS) and Glasgow coma scale(GCS) and the clinical usefulness of its death rate prediction. Data were collected from the medical records of 187 neurological patients who were admitted to the ICU of C University Hospital. The data were analyzed through $x^2$ test, t-test, Mann-Whitney, Kruskal-Wallis, goodness-of-fit test, and ROC curve. In accordance with patients' general and clinical characteristics, patient mortality turned out to be statistically different depending on ICU stay, endotracheal intubation, central venous catheter, and severity by CPSCS. Homer-Lemeshow goodness-of-fit tests were CPSCS and GCS and the results of the discrimination test using the ROC curve were $CPSCS_0$, .734, $GCS_0$,.583, $CPSCS_{24}$,.734, $GCS_{24}$, .612, $CPSCS_{48}$,.591, $GCS_{48}$,.646, $CPSCS_{72}$,.622, and $GCS_{72}$,.623. Logistic regression analysis showed that each point on the CPSCS score signifies1.034 higher likelihood of dying. Applied to neurologically ill patients, early CPSCS scores can be regarded as a useful tool.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.2
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• pp.513-517
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• 2015

Background: Growing evidence suggests that the members of the ubiquitin-proteasome system (UPS) are important for tumorigenesis. HERC4, one component, is a recently identified ubiqutin ligase. However, the expression level and function role of HERC4 in lung cancer remain unknown. Our objective was to investigate any correlation between HERC4 and development of lung cancer and its clinical significance. Materials and Methods: To determine HERC4 expression in lung cancer, an immunohistochemistry analysis of a tissue microarray containing samples of 10 lung normal tissues, 15 pulmonary neuroendocrine carcinomas, 45 squamous epithelial cancers and 50 adenocarcinomas was conducted. Receiver operating characteristic (ROC) curve analysis was applied to obtain a cut-off point of 52.5%, above which the expression of HERC4 was regarded as "positive". Results: On the basis of ROC curve analysis, positive expression of HERC4 was detected in 0/10 (0.0%) of lung normal tissues, in 4/15 (26.7%) of pulmonary neuroendocrine carcinomas, in 13/45 (28.9%) of squamous epithelial cancers and in 19/50 (38.0%) of adenocarcinomas. It showed that lung tumors expressed more HERC4 protein than adjacent normal tissues (${\chi}^2$=4.675, p=0.031). Furthermore, HERC4 positive expression had positive correlation with pT status (${\chi}^2$=44.894, p=0.000), pN status (${\chi}^2$=43.628, p=0.000), histological grade (${\chi}^2$=7.083, p=0.029) and clinical stage (${\chi}^2$=72.484, p=0.000), but not age (${\chi}^2$=0.910, p=0.340). Conclusions: Our analysis suggested that HERC4 is likely to be a diagnostic biomarker for lung cancer.

• Journal of Periodontal and Implant Science
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• v.48 no.2
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• pp.114-123
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• 2018

Purpose: The aim of the current study was to develop a computer-assisted detection system based on a deep convolutional neural network (CNN) algorithm and to evaluate the potential usefulness and accuracy of this system for the diagnosis and prediction of periodontally compromised teeth (PCT). Methods: Combining pretrained deep CNN architecture and a self-trained network, periapical radiographic images were used to determine the optimal CNN algorithm and weights. The diagnostic and predictive accuracy, sensitivity, specificity, positive predictive value, negative predictive value, receiver operating characteristic (ROC) curve, area under the ROC curve, confusion matrix, and 95% confidence intervals (CIs) were calculated using our deep CNN algorithm, based on a Keras framework in Python. Results: The periapical radiographic dataset was split into training (n=1,044), validation (n=348), and test (n=348) datasets. With the deep learning algorithm, the diagnostic accuracy for PCT was 81.0% for premolars and 76.7% for molars. Using 64 premolars and 64 molars that were clinically diagnosed as severe PCT, the accuracy of predicting extraction was 82.8% (95% CI, 70.1%-91.2%) for premolars and 73.4% (95% CI, 59.9%-84.0%) for molars. Conclusions: We demonstrated that the deep CNN algorithm was useful for assessing the diagnosis and predictability of PCT. Therefore, with further optimization of the PCT dataset and improvements in the algorithm, a computer-aided detection system can be expected to become an effective and efficient method of diagnosing and predicting PCT.

• Tuberculosis and Respiratory Diseases
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• v.73 no.3
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• pp.143-150
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• 2012

Background: The release of interferon-gamma (IFN-${\gamma}$) by T lymphocytes increases after rechallenge with Mycobacterium tuberculosis antigen, especially, at a localized site of tuberculosis (TB) infection. We aimed to compare the clincial efficacy of two commercial IFN-${\gamma}$ release assays from pleural fluid for the diagnosis in tuberculous pleurisy. Methods: We performed T-SPOT.TB and QuantiFERON-TB Gold tests simultaneously on pleural fluid and peripheral blood samples from patients with pleural effusion, in South Korea, an area with intermediate TB burden. Results: Thirty-six patients were enrolled prospectively, and tuberculous pleurisy was found in 21 patients. Both the numbers of IFN-${\gamma}$ secreting T cells and the concentration of IFN-${\gamma}$ were greater in the pleural tuberculous group, comparing with the non-tuberculous group. Moreover, in the tuberculous group, there was a significant difference in IFN-${\gamma}$ producing spot-forming cells using the T-SPOT.TB method between pleural fluid and peripheral blood. The receiver operating characteristic (ROC) curve, was the greatest for pleural fluid T-SPOT.TB test, followed by peripheral blood T-SPOT.TB test, peripheral blood QuantiFERON-TB Gold test, and pleural fluid QuantiFERON-TB Gold test (area under the ROC curve of 0.956, 0.890, 0.743, and 0.721, respectively). The T-SPOT.TB assay produced less indeterminate results than did QuantiFERON-TB Gold assay in both pleural fluid and peripheral blood. Conclusion: These findings suggest that the pleural fluid T-SPOT.TB test could be the most useful test among the IFN-${\gamma}$ release assays for diagnosing tuberculous pleurisy in an area with an intermediate prevalence of TB infection.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.11
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• pp.6327-6330
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• 2013

Haematuria is a common presentation of bladder cancer and requires a full urologic evaluation. This study aimed to develop a scoring system capable of stratifying patients with haematuria into high or low risk groups for having bladder cancer to help clinicians decide which patients need more urgent assessment. This cross-sectional study included all adult patients referred for haematuria and subsequently undergoing full urological evaluation in the years 2001 to 2011. Risk factors with strong association with bladder cancer in the study population were used to design the scoring system. Accuracy was determined by the area under the receiver operating characteristic (ROC) curve. A total of 325 patients with haematuria were included, out of which 70 (21.5%) were diagnosed to have bladder cancer. Significant risk factors associated with bladder cancer were male gender, a history of cigarette smoking and the presence of gross haematuria. A scoring system using 4 clinical parameters as variables was created. The scores ranged between 6 to 14, and a score of 10 and above indicated high risk for having bladder cancer. It was found to have good accuracy with an area under the ROC curve of 80.4%, while the sensitivity and specificity were 90.0% and 55.7%, respectively. The scoring system designed in this study has the potential to help clinicians stratify patients who present with haematuria into high or low r isk for having bladder cancer. This will enable high-risk patients to undergo urologic assessment earlier.

• Journal of Korean Academy of Nursing
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• v.41 no.1
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• pp.92-100
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• 2011

Purpose: Mortality Provability Model (MPM) II is a model for predicting mortality probability of patients admitted to ICU. This study was done to test the validity of MPM II for critically ill neurological patients and to determine applicability of MPM II in predicting mortality of neurological ICU patients. Methods: Data were collected from medical records of 187 neurological patients over 18 yr of age who were admitted to the ICU of C University Hospital during the period from January 2008 to May 2009. Collected data were analyzed through $X^2$ test, t-test, Mann-Whiteny test, goodness of fit test, and ROC curve. Results: As to mortality according to patients' general and clinically related characteristics, mortality was statistically significantly different for ICU stay, hospital stay, APACHE III score, APACHE predicted death rate, GCS, endotracheal intubation, and central venous catheter. Results of Hosmer-Lemeshow goodness-of-fit test were MPM $II_0$ ($X^2$=0.02, p=.989), MPM $II_24$ ($X^2$=0.99 p=.805), MPM $II_48$ ($X^2$=0.91, p=.822), and MPM $II_72$ ($X^2$=1.57, p=.457), and results of the discrimination test using the ROC curve were MPM $II_0$, .726 (p<.001), MPM $II_24$, .764 (p<.001), MPM $II_48$, .762 (p<.001), and MPM $II_72$, .809 (p<.001). Conclusion: MPM II was found to be a valid mortality prediction model for neurological ICU patients.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2012.04a
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• pp.190-193
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• 2012

The tools that classify the severity of patients based on the prediction of mortality include APACHE, SAPS, and MPM. Theses tools rely crucially on the evaluation of patients' general clinical status on the first date of their admission to ICU. Nursing activities are one of the most crucial factors influencing on the quality of treatment that patients receive and one of the contributing factors for their prognosis and safety. The purpose of this study was to identify the goodness-of-fit of CPSCS of critical patient severity classification system(CPSCS) and Glasgow coma scale(GCS) and the clinical usefulness of its death rate prediction. Data were collected from the medical records of 187 neurological patients who were admitted to the ICU of C University Hospital. The data were analyzed through $x^2$ test, t-test, Mann-Whitney, Kruskal-Wallis, goodness-of-fit test, and ROC curve. In accordance with patients' general and clinical characteristics, patient mortality turned out to be statistically different depending on ICU stay, endotracheal intubation, central venous catheter, and severity by CPSCS. Homer-Lemeshow goodness-of-fit tests were CPSCS and GCS and the results of the discrimination test using the ROC curve were $CPSCS_0$,.734, $GCS_0$,.583, $CPSCS_{24}$,.734, $GCS_{24}$,.612, $CPSCS_{48}$,.591, $GCS_{48}$,.646, $CPSCS_{72}$,.622, and $GCS_{72}$,.623. Logistic regression analysis showed that each point on the CPSCS score signifies1.034 higher likelihood of dying. Applied to neurologically ill patients, early CPSCS scores can be regarded as a useful tool.

• Korean Journal of Community Nutrition
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• v.23 no.4
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• pp.277-288
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• 2018

Objectives: This study was performed to verify the validity and judgment criteria setting of a health status assessment tool based on dietary patterns for middle-aged women. Methods: A total of 474 middle-aged women who visited the Comprehensive Medical Examination Center at Hanmaeum Hospital in Changwon were enrolled (IRB 2013-0005). The validity was verified using clinical indicators for the diagnosis of metabolic syndrome (MS), and it was used to set the criteria for the tool. A logistic regression analysis was performed for validation. The area under-receiver operation (AUC), sensitivity, specificity, and Youden Index were calculated through ROC curve analysis. Statistical analysis was performed by SPSS 21, and p value <0.05 was considered to be statistically significant. Results: The mean score of the group with no MS (73.3 points) was significantly higher compared to the group with MS (65.7 points) (p<0.001). An analysis of the association between the tool scores and risk of MS showed a 0.15-fold reduction in the risk of MS every time the tool's score increased by one point. As the result of the ROC curve analysis, the assessment reference point was set to 71 points, indicating 77.0% sensitivity and 61.0% specificity. Risk of MS was significantly higher in the group with a score of less than 71.0 than a group with more than 71 points (OR=5.28, p<0.001). Conclusions: This study was the first attempt to develop a health status assessment tool based on the dietary patterns for middle-aged women, and this tool has proven its usefulness as an MS assessment tool through the application of middle-aged women in the field of health screening.

• The Korean Journal of Applied Statistics
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• v.30 no.4
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• pp.591-602
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• 2017

The concentration of fine dust has increased in Korea and people have become more concerned with respiratory diseases. This study selected risk factors for chronic obstructive pulmonary disease (COPD) through demographic and clinical features and constructed a nomogram. First, logistic regression analysis was performed using demographic and clinical feature and the pulmonary function test results of the Korean National Health and Nutrition Examination Survey (KNHANES) $6^{th}$ (2013-2015) and the nomogram was constructed to visualize the risk factors of chronic obstructive pulmonary disease in order to facilitate the interpretation of the analysis results. The ROC curve and calibration plot were also used to verify the nomogram of chronic obstructive pulmonary disease.