• Journal of Korean Academy of Nursing
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• v.42 no.3
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• pp.414-423
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• 2012

Purpose: The aims of this study were to develop and test the validity of the Korean Nursing Delirium Scale (Nu-DESC) for older patients in hospital. Methods: The Korean Nu-DESC was developed based on the Nu-DESC (Gaudreau, 2005), and revised according to nursing records related to signs and symptoms of older patients with delirium (n=361) and the results of a pilot study (n=42) in one general hospital. To test the validity of the Korean Nu-DESC, 75 older patients whom nurses suspected of delirium from 731 older patients from 12 nursing units were assessed by bedside nurses using the Korean Nu-DESC. A Receiver Operating Characteristic Curve of the Korean Nu-DESC was constructed with an accompanying Area Under the Curve (AUC). Results: Specific examples such as irritable, kidding, sleeping tendency, which were observed by bedside nurses in Korea, were identified in the five features of signs and symptoms of delirium in the instrument. The Korean Nu-DESC was psycho-metrically valid and had a sensitivity and specificity of .81-.76 and .97-.73, respectively. The AUC were .89, .74. Conclusion: Results of this study indicate that the Korean Nu-DESC is well-suited for widespread clinical use in busy inpatients settings and shows promise as a research instrument.

• Clinical and Experimental Pediatrics
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• v.59 no.3
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• pp.139-144
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• 2016

Purpose: Acute pyelonephritis (APN) is a serious bacterial infection that can cause renal scarring in children. Early identification of APN is critical to improve treatment outcomes. The neutrophil-lymphocyte ratio (NLR) is a prognostic marker of many diseases, but it has not yet been established in urinary tract infection (UTI). The aim of this study was to determine whether NLR is a useful marker to predict APN or vesicoureteral reflux (VUR). Methods: We retrospectively evaluated 298 pediatric patients ($age{\leq}36months$) with febrile UTI from January 2010 to December 2014. Conventional infection markers (white blood cell [WBC] count, erythrocyte sedimentation rate [ESR], C-reactive protein [CRP]), and NLR were measured. Results: WBC, CRP, ESR, and NLR were higher in APN than in lower UTI (P<0.001). Multiple logistic regression analyses showed that NLR was a predictive factor for positive dimercaptosuccinic acid (DMSA) defects (P<0.001). The area under the receiver operating characteristic (ROC) curve was high for NLR (P<0.001) as well as CRP (P<0.001) for prediction of DMSA defects. NLR showed the highest area under the ROC curve for diagnosis of VUR (P<0.001). Conclusion: NLR can be used as a diagnostic marker of APN with DMSA defect, showing better results than those of conventional markers for VUR prediction.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.21 no.2
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• pp.118-126
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• 2018

Purpose: Classical criteria for diagnosis of autoimmune hepatitis (AIH) are intended as research tool and are difficult to apply at patient's bedside. We aimed to study the accuracy of simplified criteria and the concordance with the expert diagnosis based on the original criteria. Methods: A cohort of children under study for liver disorder was selected through consecutive sampling to obtain the prevalence of AIH within the group of differential diagnoses. AIH was defined, based on classical criteria, through committee review of medical reports. Validity indicators of the simplified criteria were obtained in an intention to diagnose approach. Optimal cut-off and the area under the receiver operating characteristic (ROC) curve were calculated. Results: Out of 212 cases reviewed, 47.2% were AIH. For the optimal cut-off (6 points), the simplified criteria showed a sensitivity of 72.0% and a specificity of 96.4%, with a 94.7% positive and a 79.4% negative predictive value. The area under the ROC curve was 94.3%. There was a good agreement in the pre-treatment concordance between the classical and the simplified criteria (kappa index, 0.775). Conclusion: Simplified criteria provide a moderate sensitivity for the diagnosis of AIH, but may help in indicating treatment in cases under suspicion with 6 or more points.

• Journal of Society of Preventive Korean Medicine
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• v.20 no.2
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• pp.17-26
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• 2016

Objectives : We presented the results of reliability study in advance, and analyzed agreement between Korean medicine doctors(KMDs)' diagnosis and cold-heat pattern identification questionnaire(CHPI)'s diagnosis. Methods : This survey was conducted from May 16 to 17, 2015. The subjects were 93 adults living in rural society. Diagnosis of CHPI was performed by 2 KMDs who have clinical experience more than 5 years. The KMDs' diagnosis was set as a reference index, and then we compare 23 items(cold pattern 11 items and heat pattern 12 items) of CHPI questionnaire and 15 items(cold pattern 8 items and heat pattern 7 items) that were brief form of it. We had cut-off value by standard of KMDs' diagnosis using receiver operating characteristic-curve(ROC-curve), with which we calculated agreement including kappa value. Correlation analysis between CHPI evaluation score by KMDs and by the questionnaire was fulfilled as well. Results : Agreement about 11 and 8 cold pattern items showed 87.1% together, and the value of kappa each recorded 0.742 and 0.741. Agreement about 12 and 7 heat pattern items suggested 81.7% and 78.5%, and the value of kappa showed 0.634 and 0.570. Correlation coefficients were 0.803 of 11 items and 0.761 of 8 items about cold pattern. In addition, correlation coefficients were 0.789 of 12 items and 0.767 of 7 items about heat pattern. The significant probability (p-value) was under 0.001. Conclusions : We have developed CHPI questionnaire involving reliability and agreement based on usual symptoms, and hope additional complements so that Korean medicine diagnostics and Korean preventive medicine would be improved.

• 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.

• Journal of Biomedical Engineering Research
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• v.38 no.1
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• pp.25-31
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• 2017

Testing TB in chest X-ray images is a typical method to diagnose presence and magnitude of PTB lesion. However, the method has limitation due to inter-reader variability. Therefore, it is essential to overcome this drawback with automatic interpretation. In this study, we propose a novel method for detection of PTB using SegNet, which is a deep learning architecture for semantic pixel wise image labelling. SegNet is composed of a stack of encoders followed by a corresponding decoder stack which feeds into a soft-max classification layer. We modified parameters of SegNet to change the number of classes from 12 to 2 (TB or none-TB) and applied the architecture to automatically interpret chest radiographs. 552 chest X-ray images, provided by The Korean Institute of Tuberculosis, used for training and test and we constructed a receiver operating characteristic (ROC) curve. As a consequence, the area under the curve (AUC) was 90.4% (95% CI:[85.1, 95.7]) with a classification accuracy of 84.3%. A sensitivity was 85.7% and specificity was 82.8% on 431 training images (TB 172, none-TB 259) and 121 test images (TB 63, none-TB 58). This results show that detecting PTB using SegNet is comparable to other PTB detection methods.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.16
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• pp.6819-6822
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• 2014

Background: The aim of this study was to evaluate the accuracy of a new scoring system in Korean patients with hematuria at high risk of bladder cancer. Materials and Methods: A total of 319 consecutive patients presenting with painless hematuria without a history of bladder cancer were analyzed, from the period of August 2012 to February 2014. All patients underwent clinical examination, and 22 patients with incomplete data were excluded from the final validation data set. The scoring system included four clinical parameters: age (${\geq}50$ = 2 vs. <50 =1), gender (male = 2 vs. female = 1), history of smoking (smoker/ex-smoker = 4 vs. non-smoker = 2) and nature of the hematuria (gross = 6 vs. microscopic = 2). Results: The area under the receiver-operating characteristic curve (95% confidence interval) of the scoring system was 0.718 (0.655-0.777). The calibration plot demonstrated a slight underestimation of bladder cancer probability, but the model had reasonable calibration. Decision curve analysis revealed that the use of model was associated with net benefit gains over the treat-all strategy. The scoring system performed well across a wide range of threshold probabilities (15%-45%). Conclusions: The scoring system developed is a highly accurate predictive tool for patients with hematuria. Although further improvements are needed, utilization of this system may assist primary care physicians and other healthcare practitioners in determining a patient's risk of bladder cancer.

• 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.

• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.28 no.2
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• pp.415-433
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• 1998

Digora system is an intraoral indirect digital radiography system utilizing storage phosphor image plate. It has wide dynamic range which allows it to decrease the patient s exposure time and may increase diagnostic ability through image processing (such as edge enhancement, grey scale conversion, brightness change, and contrast enhancement). And also, it can transmit and storage image information. The purpose of this study was to evaluate the diagnostic ability of artificial proximal caries between Conventional radiograph and Digora images(unenhanced image, brightness & contrast controlled image, and edge enhanced image). ROC(Receiver Operating Characteristic) analysis, paired t-tests, and F-tests were done for the statistical evaluation of detectability. The following results were acquired: 1. In Grade I lesions, the mean ROC areas of Conventional radiograph, Digora unenhanced image, Digora controlled image, and Digora edge enhanced image were 0.953, 0.933, 0.965, 0.978 (p>0.05). 2. In Grade II lesions, the mean ROC areas of Conventional radiograph, Digora unenhanced image, Digora controlled image, and Digora edge enhanced image were 0.969, 0.964, 0.988, 0.994. Among theses areas, there was just statistical significance between Diagnostic abilities of Digora edge enhanced image and Conventional radiograph (p<0.05). 3. In the Interobserver variability, the ROC curve areas of Digora edge enhanced image was lowermost in these areas, regardless of the Carious lesion depths. In conclusion, intraoral indirect digital system, Digora system, has the potential possibility as an alternative of Conventional radiograph in the diagnosis of proximal caries.