• Asian Pacific Journal of Cancer Prevention
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• v.17 no.4
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• pp.1861-1864
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• 2016

Although early diagnosis of thyroid nodule type is very important, the diagnostic accuracy of standard tests is a challenging issue. We here aimed to find an optimal combination of factors to improve diagnostic accuracy for distinguishing malignant from benign thyroid nodules before surgery. In a prospective study from 2008 to 2012, 345 patients referred for thyroidectomy were enrolled. The sample size was split into a training set and testing set as a ratio of 7:3. The former was used for estimation and variable selection and obtaining a linear combination of factors. We utilized smoothly clipped absolute deviation (SCAD) logistic regression to achieve the sparse optimal combination of factors. To evaluate the performance of the estimated model in the testing set, a receiver operating characteristic (ROC) curve was utilized. The mean age of the examined patients (66 male and 279 female) was $40.9{\pm}13.4years$ (range 15- 90 years). Some 54.8% of the patients (24.3% male and 75.7% female) had benign and 45.2% (14% male and 86% female) malignant thyroid nodules. In addition to maximum diameters of nodules and lobes, their volumes were considered as related factors for malignancy prediction (a total of 16 factors). However, the SCAD method estimated the coefficients of 8 factors to be zero and eliminated them from the model. Hence a sparse model which combined the effects of 8 factors to distinguish malignant from benign thyroid nodules was generated. An optimal cut off point of the ROC curve for our estimated model was obtained (p=0.44) and the area under the curve (AUC) was equal to 77% (95% CI: 68%-85%). Sensitivity, specificity, positive predictive value and negative predictive values for this model were 70%, 72%, 71% and 76%, respectively. An increase of 10 percent and a greater accuracy rate in early diagnosis of thyroid nodule type by statistical methods (SCAD and ANN methods) compared with the results of FNA testing revealed that the statistical modeling methods are helpful in disease diagnosis. In addition, the factor ranking offered by these methods is valuable in the clinical context.

• Journal of Trauma and Injury
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• v.25 no.4
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• pp.139-144
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• 2012

Purpose: Hypovolemic shock is the leading cause of death in multiple trauma patients with pelvic bone fracures. The purpose of this study was to develop a simple prediction method for injury severity and amount of hemorrhage via an analysis of the correlation between the site of pelvic bone fracture and the amount of transfusion and to verify the usefulness of the such a simple scoring system. Methods: We analyzed retrospectively the medical records and radiologic examination of 102 patients who had been diagnosed as having a pelvic bone fracture and who had visited the Emergency Department between January 2007 and December 2011. Fracture sites in the pelvis were confirmed and re-classified anatomically as pubis, ilium or sacrum. A multiple linear regression analysis was performed on the amount of transfusion, and a simplified scoring system was developed. The predictive value of the amount of transfusion for the scoring system as verified by using the receiver operating characteristics (ROC). The area under the curve of the ROC was compared with the injury severity score (ISS). Results: From among the 102 patients, 97 patients (M:F=68:29, mean $age=46.7{\pm}16.6years$) were enrolled for analysis. The average ISS of the patients was $16.2{\pm}7.9$, and the average amount of packed RBC transfusion for 24 hr was $3.9{\pm}4.6units$. The regression equation resulting from the multiple linear regression analysis was 'packed RBC units=1.40${\times}$(sacrum fracture)+1.72${\times}$(pubis fracture)+1.67${\times}$(ilium fracture)+0.36' and was found to be suitable (p=0.005). We simplified the regression equation to 'Pelvic Bleeding Score=sacrum+pubis+ilium.' Each fractured site was scored as 0(no fracture) point, 1(right or left) point, or 2(both) points. Sacrum had only 0 or 1 point. The score ranged from 0 to 5. The area under the curve (AUC) of the ROC was 0.718 (95% CI: 0.588-0.848, p=0.009). For an upper Pelvis Bleeding Score of 3 points, the sensitivity of the prediction for a massive transfusion was 71.4%, and the specificity was 69.9%. Conclusion: We developed a simplified scoring system for the anatomical fracture sites in the pelvis to predict the requirement for a transfusion (Pelvis Bleeding Score (PBS)). The PBS, compared with the ISS, is considered a useful predictor of the need for a transfusion during initial management.

• Pediatric Infection and Vaccine
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• v.24 no.1
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• pp.1-6
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• 2017

Purpose: We investigated the effectiveness of the delta neutrophil index (DNI) for the prediction of neonatal bacteremia and compared it to other indices. Methods: A total of 146 pediatric patients, aged less than 31 days, admitted to the neonatal intensive care unit of Wonju Severance Christian Hospital with fever before or during hospitalization were enrolled in this study. We divided the patients into two groups based on the existence of neonatal bacteremia and performed blood culture tests on both groups. We examined white blood cell count, absolute neutrophil count, DNI, platelet count, and C-reactive protein (CRP) test. We used a receiver operating characteristic (ROC) curve to evaluate their diagnostic significance. Results: Seventy-seven patients were diagnosed with neonatal bacteremia. The mean gestational age was 38.74 weeks and the mean birth weight was 3.20 kg. The mean gestational age of the control group was 33.34 weeks and the mean birth weight was 2.20 kg. Causative organisms of bacteremia included Staphylococcus aureus (n=22), Staphylococcus epidermidis (n=18), and Streptococcus agalactiae (n=8). Both DNI and CRP were significantly associated with neonatal bacteremia after adjusting for gestational age and birth weight. The area under the ROC curve (AUC) for DNI (0.70) was higher than that for CRP (0.68). Conclusions: The DNI can be used to effectively predict neonatal bacteremia. The prediction will be more accurate if DNI is used in conjunction with other indices. In future, it will be useful to compare DNI with other indices and investigate its relationship with prognosis.

• Korean Journal of Community Nutrition
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• v.19 no.5
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• pp.490-498
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• 2014

Objectives: This study was conducted to propose the need of re-establishing the criteria of the body weight classification in the elderly. We compared the Asia-Pacific Region Criteria (APR-C) with Entropy Model Criteria (ENT-C) using Morbidity rate of chronic diseases which correlates significantly with Body Mass Index (BMI). Methods: Subjects were 886 elderly female participating in the 2007-2009 Korea National Health and Nutrition Examination Survey (KNHANES). We compared APR-C with those of ENT-C using Receiver Operating Characteristics (ROC) curve and logistic regression analysis. Results: In the case of the morbidity of hypertension, the results were as follows: Where it was in the T-off point of APR-C, sensitivity was 67.5%, specificity was 43.1%, and Youden's index was 10.6. While in the cut-off point of ENT-C, it was 56.7%, 56.6%, and 13.3 respectively. In the case of the morbidity of diabetes, the results were as follows: In the cut-off point of APR-C, Youden's index was 14.2. While in the cut-off point of ENT-C, it was 17.2 respectively. The Area Under the ROC Curve (AUC) of the subjects who had more than 2 diseases among hypertension, diabetes, and dyslipidemia was 0.615 (95% CI: 0.578-0.652). Compared to the normal group, the odds ratio of the hypertension group which will belong to the overweight or obesity was 1.79 (95% CI: 1.30-2.47) in the APR-C, and 2.04 (95% CI: 1.49-2.80) in the ENT-C (p < 0.001). Conclusions: We conclude that the optimal cut-off point of BMI to distinguish between normal weight and overweight was $24kg/m^2$ (ENT-C) rather than $23kg/m^2$ (APR-C).

• Journal of the Korean Society of Radiology
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• v.13 no.2
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• pp.209-216
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• 2019

The purpose of this study was to suggest the optimum ambient illumination level for proper visualization in image inspection and reading on CRT and LCD monitors used for ultrasound and reading. The evaluators were divided into 4 groups: 20 (Ultra-sonographer: 20 groups (4 groups: ultra-sonographer, 1-5 years, 5 ultra-sonographers, 6 to 10 years, 5 ultra-sonographers, 11 to 15 years, The subjects were 32 questions. The evaluation method was image evaluation of ultrasonic soft copy images for 30 seconds per 10, 25, 100Lux ambient illumination. The evaluation results were evaluated as 6 points (Normal = Definitely no lesion), 2 points = possibly not a lesion, 3 points = probably not a lesion, 4 points = possibly a lesion, 5 points = probably a lesion, 6 points = Definitely a lesion). In this study, the results of ROC analysis according to ambient light illumination reading softcopy images used for lesion detection of all ultrasound images showed the highest sensitivity, specificity, and AUC results at 10Lux. It was found that optimal use of 10Lux for ambient light illumination would provide optimal detection of lesions in ultrasound soft copy images. Based on the future research data, it will be presented as basic data for designing ambient light brightness of ultrasound imaging laboratory and reading room.

• Animal Bioscience
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• v.36 no.9
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• pp.1336-1349
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• 2023

Objective: The study was conducted to screen differentially expressed miRNAs in sows at early pregnancy by high-throughput sequencing and explore its mechanism of action on embryo implantation. Methods: The blood serum of pregnant and non-pregnant Landrace×Yorkshire sows were collected 14 days after artificial insemination, and exosomal miRNAs were purified for high throughput miRNA sequencing. The expression patterns of 10 differentially expressed (DE) miRNAs were validated by quantitative reverse transcription-polymerase chain reaction (qRT-PCR). The qRT-PCR quantified the abundance of serum exosomal miR-192 in pregnant and control sows, and the diagnostic power was assessed by receiver operating characteristic (ROC) analysis. The target genes of DE miRNAs were predicted with bioinformatics software, and the functional and pathway enrichment analysis was performed on gene ontology and the Kyoto encyclopedia of genes and genomes terms. Furthermore, a luciferase reporter system was used to identify the target relation between miR-192 and integrin alpha 4 (ITGA4), a gene influencing embryo implantation in pigs. Finally, the expression levels of miRNAs and the target gene ITGA4 were analyzed by qRT-PCR, and western blot, with the proliferation of BeWo cells detected by cell counting kit-8 (CCK-8). Results: A total of 221 known miRNAs were detected in the libraries of the pregnant and non-pregnant sows, of which 55 were up-regulated and 67 were down-regulated in the pregnant individuals compared with the non-pregnant controls. From these, the expression patterns of 10 DE miRNAs were validated. The qRT-PCR analysis further confirmed a significantly higher expression of miR-192 in the serum exosomes extracted from pregnant sows, when compared to controls. The ROC analysis revealed that miR-192 provided excellent diagnostic accuracy for pregnancy (area under the ROC curve [AUC]=0.843; p>0.001). The dual-luciferase reporter assay indicated that miR-192 directly targeted ITGA4. The protein expression of ITGA4 was reduced in cells that overexpressed miR-192. Overexpression of miR-192 resulted in the decreased proliferation of BeWo cells and regulated the expression of cell cycle-related genes. Conclusion: Serum exosomal miR-192 could serve as a potential biomarker for early pregnancy in pigs. miR-192 targeted ITGA4 gene directly, and miR-192 can regulate cellular proliferation.

• Biomedical Science Letters
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• v.19 no.2
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• pp.90-97
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• 2013

The tuberculin skin test (TST) and interferon gamma (IFN-${\gamma}$) release assay (IGRA) have been widely used for diagnosis of latent tuberculosis infection (LTBI). In order to overcome limitations of current LTBI diagnostic methods, the development of a novel molecular assay which is able to measure the IFN-${\gamma}$ messenger RNA (mRNA) expression level after stimulation with Mycobacterium tuberculosis (MTB) specific antigen was recently developed. The ability of a molecular assay to detect MTB infection was similar to commercial IGRA however, the optimal incubation time for stimulating IFN-${\gamma}$ was not yet established. Therefore, in this study the direct comparisons of MTB Ag stimulation times (4 and 24 hrs) were performed for diagnosis of MTB infection. Data showed that the coincident rate between QFT-GIT IFN-${\gamma}$ ELISA and IFN-${\gamma}$ RT-PCR (4 hrs) was 88.35% and that of QFT-GIT and IFN-${\gamma}$ RT-PCR (24 hrs) was 70.85%. Based on a receiver operating characteristic (ROC) curve, the 4 hrs-MTB specific Ag stimulation time for IFN-${\gamma}$ RT-PCR had the significant P value, 95% CI value, and AUC (P < 0.0001, 95% CI=0.82 to 1.02, and AUC=0.9214) in comparison with 24 hrs-MTB specific Ag stimulation time (P = 0.009, 95% CI=0.06 to 0.94, and AUC=0.7711). These results show that 4-hr was the most optimal MTB Ag stimulation time for performing IFN-${\gamma}$ RT-PCR. Although semi-quantitative RT-PCR had a few analytical limitations, it might be useful as an alternative molecular diagnostic method for detecting MTB infection.

• Advances in nano research
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• v.17 no.3
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• pp.213-219
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• 2024

Nanotechnology is one of the critical factors involved in enhancing the sensitivity of serum biomarker detection. To explore the relationship between serum APN, Cystatin C and MMP-9 levels in patients with hypertension during pregnancy and the severity and prognosis of the disease. A total of 75 cases of hypertensive disorder complicating pregnancy (HDCP) patients who were admitted to the hospital from February 5, 2023 to May 9, 2024, were selected as the study group, and 70 healthy pregnant women who were in the same gestational week were selected as the control group. The serum APN, MMP-9 and Cys C levels of pregnant women and HDCP patients with different disease severity were compared between the two groups, and the receiver characteristic curve (ROC) was used to analyze its diagnostic value. The serum APN, MMP-9 and Cys C levels of HDCP patients with different prognosis were compared, and the factors affecting the prognosis of patients were analyzed by Logistic regression. Nanoparticles could aslo enable the sensitive detection and quantification of APN, Cystatin C, and MMP-9 in serum samples, thus increasing the accuracy of the study. The serum MMP-9 and Cys C levels of pregnant women in the study group were significantly increased, and the APN level was significantly decreased (P<0.05). Serum MMP-9 and Cys C levels in patients with pregnancy-induced hypertension, mild preeclampsia, and severe preeclampsia gradually increased (r=0.768, 0.766; P<0.001), and APN levels gradually decreased (r=-0.748, P< 0.001). In the diagnosis of patients with HDCP, the sensitivity, specificity and AUC of APN single diagnosis were 70.00%, 82.67% and 9.848 respectively. The sensitivity, specificity and AUC of MMP-9 single diagnosis were 82.86%, 74.67% and 298.300 respectively. The sensitivity, specificity and AUC of Cys C single diagnosis were 80.00%, 74.67% and 1.301 respectively. There were significant differences in age, BMI, parity, dysthymia, disease severity, APN, MMP-9 and Cys between patients with poor prognosis of HDCP and patients with good prognosis of HDCP (P<0.001). The patient's age, BMI, disease severity, APN, MMP-9 and Cys Cwere all related to HDCP. They were related risk factors of HDCP (P<0.05).

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.969-980
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• 2017

Galloping is one of the most serious vibration problems in transmission lines. Power lines can be extensively damaged owing to aerodynamic instabilities caused by ice accretion. In this study, the accident probability induced by galloping phenomenon was analyzed using logistic regression analysis. As former studies have generally concluded, main factors considered were local weather factors and physical factors of power delivery systems. Since the number of transmission towers outnumbers the number of weather observatories, interpolation of weather factors, Kriging to be more specific, has been conducted in prior to forming galloping accident estimation model. Physical factors have been provided by Korea Electric Power Corporation, however because of the large number of explanatory variables, variable selection has been conducted, leaving total 11 variables. Before forming estimation model, with 84 provided galloping cases, 840 non-galloped cases were chosen out of 13 billion cases. Prediction model for accidents by galloping has been formed with logistic regression model and validated with 4-fold validation method, corresponding AUC value of ROC curve has been used to assess the discrimination level of estimation models. As the result, logistic regression analysis effectively discriminated the power lines that experienced galloping accidents from those that did not.

• Biomedical Science Letters
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• v.23 no.4
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• pp.348-354
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• 2017

TyG (triglyceride and glucose) index using triglyceride and fasting blood glucose is recommended as a useful marker for insulin resistance. The present study evaluated the usefulness of TyG index in diagnosing metabolic syndrome and suggested an optimal cut-off value. The subjects of this study were adult 4,415 adults aged 20 to 80 years who underwent health screening at J General Hospital from January 2016 to January 2017. Metabolic syndrome was based on AHA/NHLBI (American Heart Association/National Heart, Lung, and Blood Institute) criteria. TyG index correlated with metabolic syndrome risk factors including HOMA-IR. Compared with the participants in the lowest quartile of TyG index, odds ratios and 95% confidence intervals for metabolic syndrome were 8.5 (3.005~23.903), 20.0 (17.190~23.407) for those in the third, and the fourth quartile of TyG index. The optimal cut-off value of the metabolic syndrome was 8.81 for TyG index (sensitivity 86.7%, specificity 80.1%) and area under the ROC curve (AUC) was 0.894. In conclusion, TyG index is effective to identify individuals at risk for metabolic syndrome.