• Journal of Yeungnam Medical Science
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• v.33 no.1
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• pp.8-12
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• 2016

Background: The decision to administer oral anticoagulation therapy depends on accurate assessment of stroke risk in patients with atrial fibrillation (AF). Various stroke risk stratification schemes have been developed to help inform clinical decision making. The CHADS2 and CHA2DS2-VASc scores have been used in estimating the risk of stroke in patients with AF. Recently R2CHA2DS2-VASc score was developed. The objective of the current study is to validate the usefulness of the R2CHA2DS2-VASc score and to compare the accuracy of the CHADS2, CHA2DS2-VASc, and R2CHA2DS2-VASc scores in predicting a patient's risk of stroke. Methods: Based on medical records, we conducted a retrospective study of patients hospitalized with AF from March 2011 to July 2013. A total of 448 AF patients were included in this study. The receiver operating characteristic (ROC) curve analysis in MedCalc was used for comparison with respective diagnostic values. Results: The patient characteristics showed male predominance (60.9%). Among the 448 AF patients, 131 (29.2%) patients had strokes during the study. A R2CHA2DS2-VASc score of more than 5 is the optimal cut-off value for prediction of stroke. A risk score of three, the area under the ROC curve (AUC) of R2CHA2DS2-VASc score (AUC 0.631; 95% confidence interval, 0.585-0.679) was the highest. A significant difference was observed between AUC for R2CHA2DS2-VASc, CHADS2, and CHA2DS2-VASc scores, but no meaningful difference between CHADS2 and CHA2DS2-VASc scores. Conclusion: We determined the usefulness of the R2CHA2DS2-VASc score, which showed better association with stroke than the CHADS2 and CHA2DS2-VASc scores.

• Journal of Korean Neurosurgical Society
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• v.64 no.1
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• pp.125-135
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• 2021

Objective : This study aimed to validate the Korean version of the Repeatable Battery for the Assessment of Neuropsychological Status Update (K-RBANS). Methods : We performed a retrospective analysis of 283 psychiatric and neurosurgery patients. To investigate the convergent validity of the K-RBANS, correlation analyses were performed for other intelligence and neuropsychological test results. Confirmatory factor analysis was used to test a series of alternative plausible models of the K-RBANS. To analyze the various capabilities of the K-RBANS, we compared the area under the receiver operating characteristic (ROC) curves (AUC). Results : Significant correlations were observed, confirming the convergent validity of the K-RBANS among the Total Scale Index (TSI) and indices of the K-RBANS and indices of intelligence (r=0.47-0.81; p<0.001) and other neuropsychological tests at moderate and above significance (r=0.41-0.63; p<0.001). Additionally, the results testing the construct validity of the K-RBANS showed that the second-order factor structure model (model 2, similar to an original factor structure of RBANS), which includes a first-order factor comprising five index scores (immediate memory, visuospatial capacity, language, attention, delayed memory) and one higher-order factor (TSI), was statistically acceptable. The comparative fit index (CFI) (CFI, 0.949) values and the goodness of fit index (GFI) (GFI, 0.942) values higher than 0.90 indicated an excellent fit. The root mean squared error of approximation (RMSEA) (RMSEA, 0.082) was considered an acceptable fit. Additionally, the factor structure of model 2 was found to be better and more valid than the other model in χ2 values (Δχ2=7.69, p<0.05). In the ROC analysis, the AUCs of the TSI and five indices were 0.716-0.837, and the AUC of TSI (AUC, 0.837; 95% confidence interval, 0.760-0.896) was higher than the AUCs of the other indices. The sensitivity and specificity of TSI were 77.66% and 78.12%, respectively. Conclusion : The overall results of this study suggest that the K-RBANS may be used as a valid tool for the brief screening of neuropsychological patients in Korea.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.21
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• pp.9077-9083
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• 2014

Background: This study aimed to summarize the potential diagnostic value of serum DKK1 levels in cancer detection. Materials and Methods: Serum DKK1 was measured using enzyme-linked immunosorbent assay in a case-control study. Then we performed a meta-analysis and the pooled sensitivity, specificity, diagnostic odds ratio, and summary receiver operating characteristic (sROC) curves were used to evaluate the overall test performance. Results: Serum DKK1 levels were found to be significantly upregulated in gastric cancer as compared to controls. ROC curve analysis revealed an AUC of 0.636, indicating the test has the potential to diagnose cancer with poor accuracy. The summary estimates of the pooled sensitivity, specificity and diagnostic odds ratio in meta-analysis were 0.55 with a 95% confidence interval (CI) (0.53-0.57), 0.86 (95%CI, 0.84-0.88) and 12.25 (95%CI, 5.31-28.28), respectively. The area under the sROC was 0.85. Subgroup analysis revealed that the diagnostic accuracy of serum DKK1 in lung cancer (sensitivity: 0.69 with 95%CI, 0.66-0.74; specificity: 0.95 with 95%CI, 0.92-0.97; diagnostic odds ratio: 44.93 with 95%CI, 26.19-77.08) was significantly higher than for any other cancer. Conclusions: Serum DKK1 might be useful as a noninvasive method for confirmation of cancer diagnosis, particularly in the case of lung cancer.

• The Journal of the Korea Contents Association
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• v.11 no.10
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• pp.342-348
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• 2011

The study aimed to compare the validity between the abdominal ultrasonographic(US) grading system of fatty liver and histologic grading system of fatty liver in living liver donor candidates. As the fatty liver is defined as pathologic total fat >10%, US validity was sensitivity 64.6%, specificity 68%, positive predictive value 76.8%, negative predictive value 54%. As the strict data handling on US grading normal, mild fatty liver are negative, moderate fatty liver is positive, US validity was sensitivity 26.8%, specificity 100%, positive predictive value 100%, negative predictive value 45.5%. ROC curve analysis according to different cut off value of liver-to-kidney brightness ratio was Area under ROC curve=0.859(95% CI=0.795~0.922, state variable= total fat 10%). There were statistically significant difference( p<0.001). Ultrasonography for the fatty diagnosis showed a high validity to predict the result of histology grade of fatty liver.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.11 no.3
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• pp.28-38
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• 2008

The purpose of this study are to compare existing presence-absence predictive models and to predict suitable habitat for Goral (Nemorhaedus caudatus raddeanus) that is an endangered and protected species in Seoraksan national park using the best model among existing predictive models. The methods of this study are as follows. First, 375 location data and 9 environmental data layers were implemented to build a model. Secondly, 4 existing presence-absence models : Generalized Linear Model (GLM), Generalized Addictive Model (GAM), Classification and Regression Tree (CART), and Artificial Neural Network (ANN) were tested to predict the Goal habitat. Thirdly, ROC (Receiver Operating Characteristic) and Kappa statistics were used to calculate a model performance. Lastly, we verified models and created habitat suitability maps. The ROC AUC (Area Under the Curve) and Kappa values were 0.697/0.266 (GLM), 0.729/0.313 (GAM), 0.776/0.453 (CART), and 0.858/0.559 (ANN). Therefore, ANN was selected as the best model among 4 models. The models showed that elevation, slope, and distance to stream were the significant factors for Goal habitat. The ratio of predicted area of ANN using a threshold was 31.29%, but the area decreased when human effect was considered. We need to investigate the difference of various models to build a suitable wildlife habitat model under a given condition.

• Journal of Korean Academy of Nursing
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• v.46 no.1
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• pp.149-158
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• 2016

Purpose: This study was done to develop of the Korean intensive care delirium screening tool (KICDST). Methods: The KICDST was developed in 5 steps: Configuration of conceptual frame, development of preliminary tool, pilot study, reliability and validity test, development of final KICDST. Reliability tests were done using degree of agreement between evaluators and internal consistency. For validity tests, CVI (Content Validity Index), ROC (Receiver Operating Characteristics) analysis, known group technique and factor analysis were used. Results: In the reliability test, the degree of agreement between evaluators showed .80~1.00 and the internal consistency was KR-20=.84. The CVI was .83~1.00. In ROC analysis, the AUC (Area Under the ROC Curve) was .98. Assessment score was 4 points. The values for sensitivity, specificity, correct classification rate, positive predictive value, and negative predictive value were found to be 95.0%, 93.7%, 94.4%, 95.0% and 93.7%, respectively. In the known group technique, the average delirium screening tool score of the non-delirium group was $1.25{\pm}0.99$ while that of delirium group was $5.07{\pm}1.89$ (t= - 16.33, p <.001). The factors were classified into 3 factors (cognitive change, symptom fluctuation, psychomotor retardation), which explained 67.4% of total variance. Conclusion: Findings show that the KICDST has high sensitivity and specificity. Therefore, this screening tool is recommended for early identification of delirium in intensive care patients.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.3
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• pp.1481-1488
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• 2014

Background: To avoid performing axillary lymph node dissection (ALND) for non-sentinel lymph node (SLN)-negative patients with-SLN positive axilla, nomograms for predicting the status have been developed in many centers. We created a new nomogram predicting non-SLN metastasis in SLN-positive patients with invasive breast cancer and evaluated 14 existing breast cancer models in our patient group. Materials and Methods: Two hundred and thirty seven invasive breast cancer patients with SLN metastases who underwent ALND were included in the study. Based on independent predictive factors for non-SLN metastasis identified by logistic regression analysis, we developed a new nomogram. Receiver operating characteristics (ROC) curves for the models were created and the areas under the curves (AUC) were computed. Results: In a multivariate analysis, tumor size, presence of lymphovascular invasion, extranodal extension of SLN, large size of metastatic SLN, the number of negative SLNs, and multifocality were found to be independent predictive factors for non-SLN metastasis. The AUC was found to be 0.87, and calibration was good for the present Ondokuz Mayis nomogram. Among the 14 validated models, the MSKCC, Stanford, Turkish, MD Anderson, MOU (Masaryk), Ljubljana, and DEU models yielded excellent AUC values of > 0.80. Conclusions: We present a new model to predict the likelihood of non-SLN metastasis. Each clinic should determine and use the most suitable nomogram or should create their own nomograms for the prediction of non- SLN metastasis.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.1
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• pp.323-333
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• 2016

Background: Ovarian cancer remains a major worldwide health care issue due to the lack of satisfactory diagnostic methods for early detection of the disease. Prior studies on the role of serum cancer antigen 125 (CA125) and human epididymis protein 4 (HE4) in detecting ovarian cancer presented conflicting results. New tools to improve the accuracy of identifying malignancy are urgently needed. We here aimed to evaluate the diagnostic utility of tissue CA125 and HE4 gene expression in comparison to serum CA125 and HE4 in discriminating benign from malignant pelvic masses. Materials and Methods: One-hundred Egyptian women were enrolled in this study, including 60 epithelial ovarian cancer (EOC) patients and 20 benign ovarian tumor patients, as well as 20 apparently healthy women. Preoperative serum levels of CA125 and HE4 were measured by immunoassays. Tissue expression levels of genes encoding CA125 and HE4 were determined by quantitative real time polymerase chain reaction (qRT-PCR). The diagnostic performance of CA125 and HE4, measured either as mRNA or protein levels, was evaluated by receiver operating characteristic (ROC) curves. Results: The serum CA125+HE4 combination and serum HE4, with area under the curve (AUC) values of 0.935 and 0.932, respectively, performed significantly better than serum CA125 (AUC=0.592; P<0.001). Tissue CA125 and HE4 (AUC=1) performed significantly better than serum CA125 (P<0.001), serum HE4 (P=0.016) and the serum CA125+HE4 combination (P=0.018). Conclusions: Measurement of tissue CA125 and HE4 gene expression not only improves discriminatory performance, but also broadens the range of differential diagnostic possibilities in distinguishing EOC from benign ovarian tumors.

• Atmosphere
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• v.33 no.5
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• pp.519-530
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• 2023

Deep convection can make adverse effects on safe and efficient aviation operations by causing various weather hazards such as convectively-induced turbulence, icing, lightning, and downburst. To prevent such damage, it is necessary to accurately predict spatiotemporal distribution of deep convective area near the airport and airspace. This study developed a new index, the Aviation Convective Index (ACI), for deep convection, using the operational global Unified Model of the Korea Meteorological Administration. The ACI was computed from combination of three different variables: 3-hour maximum of Convective Available Potential Energy, averaged Outgoing Longwave Radiation, and accumulative precipitation using the fuzzy logic algorithm. In this algorithm, the individual membership function was newly developed following the cumulative distribution function for each variable in Korean Peninsula. This index was validated and optimized by using the 1-yr period of radar mosaic data. According to the Receiver Operating Characteristics curve (AUC) and True Skill Score (TSS), the yearly optimized ACI (ACI_YrOpt) based on the optimal weighting coefficients for 1-yr period shows a better skill than the no optimized one (ACI_NoOpt) with the uniform weights. In all forecast time from 6-hour to 48-hour, the AUC and TSS value of ACI_YrOpt were higher than those of ACI_NoOpt, showing the improvement of averaged value of AUC and TSS by 1.67% and 4.20%, respectively.

• Korean Journal of Clinical Laboratory Science
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• v.49 no.2
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• pp.114-120
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• 2017

There have been many studies to develop methods for predicting diabetes and to prevent diabetes. The validity of glycated hemoglobin (HbA1c), one of the commonly known tools in predicting diabetes, has been verified by many previous studies. In this study, we examined the cutoff value of HbA1c for diabetes and impaired fasting glucose (IFG). Based on this study, we proposed a proper clinical guideline and evaluated the validation of the guideline. Excluding those without blood glucose and HbA1c data, we used the data of 5,161 subjects (2,281 men and 2,880 women) over the age of 20 years from the 2015 Korean National Health and Nutrition Examination Survey. The correlation efficient of fasting plasma glucose (FPG) and HbA1c was 0.79, indicating a strong relationship. Howeve, the correlation efficient of FPG and HbA1c was low, showing 0.27 in non-diabetes, 0.39 in IFG, and 0.66 in diabetes, showing a strong relationship. The cutoff value of HbA1c for predicting diabetes using ROC curve was 6.05% (sensitivity 84.6%, and specificity 92.0%), and AUC was 0.941 (0.937 in men, and 0.946 in women). The cutoff value of HbA1c for predicting IFG using ROC curve was 5.55% (sensitivity 64.5%, and specificity 70.0%), and AUC was 0.733 (0.708 in men, and 0.764 in women). Therefore, it may not be appropriate to apply the guidelines for diagnosing IFG since sensitivity and specificity were below 70%. For future studies retarding the cutoff value of HbA1c in predicting IFG, high sensitivity and specificity are expected if we segment the reference range of IFG.