• Journal of Preventive Medicine and Public Health
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• v.38 no.2
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• pp.203-207
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• 2005

Objectives: Recently, the American Diabetes Association (ADA) redefined the criteria of prediabetes, which has lowered the diagnostic level of fasting plasma glucose (FPG) from 110 to 125 mg/dl, down to levels between 100 to 125mg/dl. The purpose of this study was to determine the predictive cutoff level of FPG as a risk for the development of diabetes mellitus in Korean men. Methods: A retrospective cohort study was conducted on 11,423 (64.5%) out of 17,696 males $\leq$30 years of age, and who met the FPG of $\leq$125 mg/dl and hemoglobin A1c of $\leq$ 6.4% criteria, without a history of diabetes, and who were enrolled at the screening center of a certain university hospital between January and December 1999. The subjects were followed from January 1999 to December 2002 (mean follow-up duration; 2.3(${\pm}0.7$) years). They were classified as normal (FPG <100mg/dl), high glucose (FPG $\geq$100mg/dl and <110mg/dl) and impaired fasting glucose (FPG $\geq$110mg/dl and $\leq$125mg/dl) on the basis of their fasting plasma glucose level measured in 1999. We compared the incidence of diabetes between the 3 groups by performing Cox proportional hazards model and used receiver operating characteristic analyses of the FPG level, in order to estimate the optimal cut-off values as predictors of incident diabetes. Results: At the baseline, most of the study subjects were in age in their 30s to 40s (mean age, 41.8(${\pm}7.1$) year). The incidence of diabetes mellitus in this study was 1.19 per 1,000 person-years (95% CI=0.68-1.79), which was much lower than the results of a community-based study that was 5.01 per 1,000 person-years. The relative risks of incident diabetes in the high glucose and impaired fasting glucose groups, compared with the normal glucose group, were 10.3 (95% CI=2.58-41.2) and 95.2 (95% CI= 29.3-309.1), respectively. After adjustment for age, body mass index, and log triglyceride, a FPG greater than 100mg/dl remained significant predictors of incident diabetes. Using the receiver operating characteristic (ROC) curve, the optimal cutoff level of FPG as a predictor of incident diabetes was 97.5 mg/dl, with a sensitivity and a specificity of 81.0% and 86.0%, respectively. Conclusion: These results suggest that lowering the criteria of impaired fasting glucose is needed in Korean male adults. Future studies on community-based populations, including women, will be required to determine the optimal cutoff level of FPG as a predictor of incident diabetes.

• Journal of Trauma and Injury
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• v.34 no.1
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• pp.3-12
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• 2021

Purpose: To evaluate the severity of trauma, many scoring systems and predictive models have been presented. The quick Sequential Organ Failure Assessment (qSOFA) is a simple scoring system based on vital signs, and we expect it to be easier to apply to trauma patients than other trauma assessment tools. Methods: This study was a cross-sectional study of trauma patients who visited the emergency department of Jeju National University Hospital. We excluded patients under the age of 18 years and unknown outcomes. We calculated the qSOFA, the Modified Early Warning Score (mEWS), Revised Trauma Score (RTS), and Injury Severity Score (ISS) based on patients' initial vital signs and assessments performed in the emergency department (ED). The primary outcome was mortality within 14 days of trauma. We analyzed qSOFA scores using multivariate logistic regression analysis and compared the predictive accuracy of these scoring systems using the area under the receiver operating characteristic curve (AUROC). Results: In total, 27,764 patients were analyzed. In the multivariate logistic regression analysis of the qSOFA, the adjusted odds ratios with 95% confidence interval (CI) for mortality relative to a qSOFA score of 0 were 27.82 (13.63-56.79) for a qSOFA score of 1, 373.31 (183.47-759.57) for a qSOFA score of 2, and 494.07 (143.75-1698.15) for a qSOFA score of 3. In the receiver operating characteristic (ROC) curve analysis for the qSOFA, mEWS, ISS, and RTS in predicting the outcomes, for mortality, the AUROC for the qSOFA (AUROC [95% CI]; 0.912 [0.871-0.952]) was significantly greater than those for the ISS (0.700 [0.608-0.793]) and RTS (0.160 [0.108-0.211]). Conclusions: The qSOFA was useful for predicting the prognosis of trauma patients evaluated in the ED.

• Journal of Preventive Medicine and Public Health
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• v.53 no.4
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• pp.256-265
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• 2020

Objectives: We compared the associations of 3 computed tomography (CT)-based abdominal adiposity indexes with non-alcoholic fatty liver disease (NAFLD) among middle-aged Korean men and women. Methods: The participants were 1366 men and 2480 women community-dwellers aged 30-64 years. Three abdominal adiposity indexes-visceral fat area (VFA), subcutaneous fat area (SFA), and visceral-to-subcutaneous fat ratio (VSR)-were calculated from abdominal CT scans. NAFLD was determined by calculating the Liver Fat Score from comorbidities and blood tests. An NAFLD prediction model that included waist circumference (WC) as a measure of abdominal adiposity was designated as the base model, to which VFA, SFA, and VSR were added in turn. The area under the receiver operating characteristic curve (AUC), integrated discrimination improvement (IDI), and net reclassification improvement (NRI) were calculated to quantify the additional predictive value of VFA, SFA, and VSR relative to WC. Results: VFA and VSR were positively associated with NAFLD in both genders. SFA was not significantly associated with NAFLD in men, but it was negatively associated in women. When VFA, SFA, and VSR were added to the WC-based NAFLD prediction model, the AUC improved by 0.013 (p<0.001), 0.001 (p=0.434), and 0.009 (p=0.007) in men and by 0.044 (p<0.001), 0.017 (p<0.001), and 0.046 (p<0.001) in women, respectively. The IDI and NRI were increased the most by VFA in men and VSR in women. Conclusions: Using CT-based abdominal adiposity indexes in addition to WC may improve the detection of NAFLD. The best predictive indicators were VFA in men and VSR in women.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.3
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• pp.1339-1344
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• 2014

Aims: Alterations in mitochondrial DNA (mtDNA) have been implicated in carcinogenesis and tumor progression. We here evaluated the diagnostic and prognostic potential of mtDNA as a biomarker for breast cancer. Methods: Using multiplex real-time polymerase chain reaction, nuclear DNA (nDNA) and mtDNA levels in serum, buffy coat, tumor, and tumor-adjacent tissue samples from 50 breast cancer patients were determined and assessed for associations with clinicopathological features. To evaluate mtDNA as a biomarker for distinguishing between the four sample types, we created receiver operating characteristic (ROC) curves. Results: The mtDNA levels in buffy coat were significantly lower than in other sample types. Relative to tumor-adjacent tissue, reduced levels of mtDNA were identified in buffy coat and tumor tissue but not in serum. According to ROC curve analysis, mtDNA levels could be used to distinguish between buffy coat and tumor-adjacent tissue samples with good sensitivity (77%) and specificity (83%). Moreover, mtDNA levels in serum and tumor tissue were positively associated with cancer TMN stage. Conclusions: The mtDNA levels in blood samples may represent a promising, non-invasive biomarker in breast cancer patients. Additional, large-scale validation studies are required to establish the potential use of mtDNA levels in the early diagnosis and monitoring of breast cancer.

• Clinical and Experimental Pediatrics
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• v.60 no.11
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• pp.353-358
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• 2017

Purpose: To develop and evaluate a simple screening tool to assess hearing loss in newborns. A derived score was compared with the standard clinical practice tool. Methods: This cohort study was designed to screen the hearing of newborns using transiently evoked otoacoustic emission and auditory brain stem response, and to determine the risk factors associated with hearing loss of newborns in 3 tertiary hospitals in Northern Thailand. Data were prospectively collected from November 1, 2010 to May 31, 2012. To develop the risk score, clinical-risk indicators were measured by Poisson risk regression. The regression coefficients were transformed into item scores dividing each regression-coefficient with the smallest coefficient in the model, rounding the number to its nearest integer, and adding up to a total score. Results: Five clinical risk factors (Craniofacial anomaly, Ototoxicity, Birth weight, family history [Relative] of congenital sensorineural hearing loss, and Apgar score) were included in our COBRA score. The screening tool detected, by area under the receiver operating characteristic curve, more than 80% of existing hearing loss. The positive-likelihood ratio of hearing loss in patients with scores of 4, 6, and 8 were 25.21 (95% confidence interval [CI], 14.69-43.26), 58.52 (95% CI, 36.26-94.44), and 51.56 (95% CI, 33.74-78.82), respectively. This result was similar to the standard tool (The Joint Committee on Infant Hearing) of 26.72 (95% CI, 20.59-34.66). Conclusion: A simple screening tool of five predictors provides good prediction indices for newborn hearing loss, which may motivate parents to bring children for further appropriate testing and investigations.

• Korean Journal of Remote Sensing
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• v.36 no.1
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• pp.67-81
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• 2020

The rapid climatic changes being caused by global warming are resulting in abnormal weather conditions worldwide, which in some regions have increased the frequency of landslides. This study was aimed to analyze and compare the landslide susceptibility using the Frequency Ratio (FR), Statistical Index, Weight of Evidence, Certainty Factor, and Index of Entropy (IoE) at Woomyeon Mountain in South Korea. Through the construction of a landslide inventory map, 164 landslide locations in total were found, of which 50 (30%) were reserved to validate the model after 114 (70%) had been chosen at random for model training. The sixteen landslide conditioning factors related to topography, hydrology, pedology, and forestry factors were considered. The results were evaluated and compared using relative operating characteristic curve and the statistical indexes. From the analysis, it was shown that the FR and IoE models were better than the other models. The FR model, with a prediction rate of 0.805, performed slightly better than the IoE model with a prediction rate of 0.798. These models had the same sensitivity values of 0.940. The IoE model gave a specific value of 0.329 and an accuracy value of 0.710, which outperforms the FR model which gave 0.276 and 0.680, respectively, to predict the spatial landslide in the study area. The generated landslide susceptibility maps can be useful for disaster and land use planning.

• Korean Journal of Biological Psychiatry
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• v.13 no.4
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• pp.273-278
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• 2006

Objectives : Biochemical markers can provide an objective evidence of heavy alcohol drinking. The purpose of this study was to compare and evaluate the usefulness of biological markers detecting alcohol dependence, such as mean corpuscular volume(MCV), gamma-glutamyl transferase(GGT), and carbohydrate-deficient transferrin(CDT) in the patients of an alcohol counseling center. Methods : This study was done with 64 patients with alcohol dependence and 36 healthy subjects. Relative values(%) of CDT were determined in their sera with turbidimetric immunoassay(Bio-Rad %CDT assay, Axis-Shield ASA, Oslo, Norway), and were compared with conventional markers of alcohol consumption, GGT and MCV. Results : Among the patients with alcohol dependence, 78.1% showed abnormal %CDT levels compared with GGT(61.9%) and MCV(20.7%). The areas under the receiver operating characteristic(ROC) curves(95% confidence interval) for %CDT, GGT, and MCV were 0.934(0.866-0.973), 0.871(0.789-0.930), and 0.575 (0.472-0.673), respectively. Conclusion : %CDT seems to be the most reliable biological marker for the detection and monitoring of alcohol consumption in the patients with alcohol dependence of the alcohol counseling center.

• Journal of Information Technology and Architecture
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• v.10 no.4
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• pp.467-478
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• 2013

The necessity of research for EA service and performance is surfacing while nation-level and individual agency level performances utilizing Government-wide EA information. In this study, performance model for EA service has been developed categorizing characteristic elements of EA as service. And weight differences between quality items that constitute performance model have been calculated using AHP analysis method. To achieve the stated, SERVQUAL applied performance model for EA service has been developed working through logical reasoning and a broad range of theoretical studies concerning EA service. Moreover, relative weight differences between quality items that constitute the model have been calculated. The results of weight analysis find that importance differences between quality items in order of significance are as follows: EA administrator > EA information > EA education > EA policy > EA operating system. This study, as the nation's first research to graft the public-sector EA service onto SERVQUAL Model that is capturing remarkable attention, has considerable practical and theoretical implications.

• Journal of Trauma and Injury
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• v.21 no.2
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• pp.71-77
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• 2008

Purpose: The Glasgow Coma Scale (GCS), though it is widely used for triage, has been criticized as being unnecessarily complex. Recently, a 3-point Simplified Motor Score (SMS, defined as obeys commands=2; localizes pain=1; withdrawals to pain or worse=0) was developed from the motor component of the GCS and was found to have a similar test performance for triage after traumatic brain injury when compared with the GCS as the criterion standard. The purpose of this study was to validate the SMS. Methods: We analyzed the patients who visited Kyungpook National University Hospital emergency center after traumatic brain injury from 2006 January to 2006 June. The test performance of the GCS, its motor component, and SMS relative to three clinically relevant traumatic brain injury outcomes (abnormal brain CT scans, Abbreviated Injury Scale $(AIS){\geq}4$, and mortality) were evaluated with areas under the receiver operating characteristic curves (AUCs). Results: Of 504 patients included in the analysis, 25.6% had an abnormal brain CT scans, 13.1% had $AIS{\geq}4$, and 5.0% died. The AUCs for the GCS, its motor component, and SMS with respect to the abnormal CT scans were 0.776, 0.715, and 0.716, and respectively, those for $AIS{\geq}4$ and mortality, were 0.969, 0.973, and 0.968, and 0.931, 0.909, and 0.909, respectively. Conclusion: The 3-point SMS demonstrated similar test performance when compared with the 15-point GCS score and its motor component for triage after traumatic brain injury in our populations.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.197-197
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• 2016

Forecasting future drought events in a region plays a major role in water management and risk assessment of drought occurrences. The creeping characteristics of drought make it possible to mitigate drought's effects with accurate forecasting models. Drought forecasts are inevitably plagued by uncertainties, making it necessary to derive forecasts in a probabilistic framework. In this study, a new probabilistic scheme is proposed to forecast droughts, in which a discrete-time finite state-space hidden Markov model (HMM) is used aggregated with the Representative Concentration Pathway 8.5 (RCP) precipitation projection (HMM-RCP). The 3-month standardized precipitation index (SPI) is employed to assess the drought severity over the selected five stations in South Kore. A reversible jump Markov chain Monte Carlo algorithm is used for inference on the model parameters which includes several hidden states and the state specific parameters. We perform an RCP precipitation projection transformed SPI (RCP-SPI) weight-corrected post-processing for the HMM-based drought forecasting to derive a probabilistic forecast that considers uncertainties. Results showed that the HMM-RCP forecast mean values, as measured by forecasting skill scores, are much more accurate than those from conventional models and a climatology reference model at various lead times over the study sites. In addition, the probabilistic forecast verification technique, which includes the ranked probability skill score and the relative operating characteristic, is performed on the proposed model to check the performance. It is found that the HMM-RCP provides a probabilistic forecast with satisfactory evaluation for different drought severity categories, even with a long lead time. The overall results indicate that the proposed HMM-RCP shows a powerful skill for probabilistic drought forecasting.