• 대한간호학회지
• /
• 제50권6호
• /
• pp.787-798
• /
• 2020

Purpose: This study aimed to assign weights for subscales and items of the Post-Intensive Care Syndrome questionnaire and suggest optimal cut-off values for screening unplanned hospital readmissions of critical care survivors. Methods: Seventeen experts participated in an analytic hierarchy process for weight assignment. Participants for cut-off analysis were 240 survivors who had been admitted to intensive care units for more than 48 hours in three cities in Korea. We assessed participants using the 18-item Post-Intensive Care Syndrome questionnaire, generated receiver operating characteristic curves, and analysed cut-off values for unplanned readmission based on sensitivity, specificity, and positive likelihood ratios. Results: Cognitive, physical, and mental subscale weights were 1.13, 0.95, and 0.92, respectively. Incidence of unplanned readmission was 25.4%. Optimal cut-off values were 23.00 for raw scores and 23.73 for weighted scores (total score 54.00), with an area of under the curve (AUC) of .933 and .929, respectively. There was no significant difference in accuracy for original and weighted scores. Conclusion: The optimal cut-off value accuracy is excellent for screening of unplanned readmissions. We recommend that nurses use the Post-Intensive Care Syndrome Questionnaire to screen for readmission risk or evaluating relevant interventions for critical care survivors.

• 한국수자원학회:학술대회논문집
• /
• 한국수자원학회 2021년도 학술발표회
• /
• pp.77-77
• /
• 2021

가뭄은 사회·경제적으로 매우 큰 피해를 주는 자연재해이며, 그 시작과 발생 지역을 정확하게 예측하는 데 어려운 문제가 있다. 이에 수문 분야에서는 가뭄에 영향을 미치는 수문·기상인자들을 이용하여 다양한 가뭄지수를 개발하였고 이를 활용하여 가뭄 현상을 모니터링하고 예측 및 전망하는데 다양한 노력을 기울이고 있다. 하지만 가뭄지수들은 실제 가뭄이 어떠한 형태로 발생하는지 파악하기에 많은 한계점을 가지고 있다. 이에 최근 들어 미국과 유럽에서는 실제 농업, 환경, 에너지 등과 같은 다양한 분야에 걸쳐 가뭄 피해로 인해 생기는 가뭄 영향을 보다 체계적이고 상세한 데이터 인벤토리로 구축하고 가뭄지수와의 상관관계, 회귀분석과 같은 연구를 통해 가뭄 영향 예측을 시도하고 있다. 따라서 본 연구에서는 보고서, 데이터베이스, 웹 크롤링(Web-Crawling)을 통한 뉴스 기사 등과 같은 자료를 수집하여 국내 가뭄 영향 인벤토리를 구축하였다. 또한 수문 분야에 널리 사용되고 있는 가뭄지수인 표준 강수 증발산량지수 SPEI(Standardized Precipitation-Evapotranspiration Index)를 기반으로 지역에 따른 가뭄 영향을 예측하기 위해 최근 로지스틱 회귀모형, Random forest, Support vector machine, XGBoost 등의 다양한 머신러닝 기법을 적용하였다. 각 모형의 성능을 Receiver Operating Characteristic(ROC) 곡선을 통해 평가하여 가뭄 영향 예측에 적절한 머신러닝 기법을 제시하였다. 본 연구 결과를 통해 텍스트 기반의 가뭄 영향 자료와 머신러닝 기법을 통한 가뭄 영향 예측 방법론은 가뭄 재난 관리에 유용한 정보를 제공할 수 있다.

• Geomechanics and Engineering
• /
• 제36권5호
• /
• pp.441-453
• /
• 2024

Sinkhole subsidence and collapse is a common geohazard often formed in karst areas such as the state of Florida, United States of America. To predict the sinkhole occurrence, we need to understand the formation mechanism of sinkhole and its karst hydrogeology. For this purpose, investigating the factors affecting sinkholes is an essential and important step. The main objectives of the presenting study are (1) the development of a machine learning (ML)-based model, namely C5.0 decision tree (C5.0 DT), for the prediction of sinkhole susceptibility, which accounts for sinkhole/subsidence inventory and sinkhole contributing factors (e.g., geological/hydrogeological) and (2) the construction of a regional-scale sinkhole susceptibility map. The study area is east central Florida (ECF) where a cover-collapse type is commonly reported. The C5.0 DT algorithm was used to account for twelve (12) identified hydrogeological factors. In this study, a total of 1,113 sinkholes in ECF were identified and the dataset was then randomly divided into 70% and 30% subsets for training and testing, respectively. The performance of the sinkhole susceptibility model was evaluated using a receiver operating characteristic (ROC) curve, particularly the area under the curve (AUC). The C5.0 model showed a high prediction accuracy of 83.52%. It is concluded that a decision tree is a promising tool and classifier for spatial prediction of karst sinkholes and subsidence in the ECF area.

• 한국수자원학회논문집
• /
• 제47권2호
• /
• pp.171-182
• /
• 2014

본 연구에서는 가뭄해석을 위한 이변량 결합가뭄지수를 산정하고 국내 활용성을 평가하였다. 이변량 결합가뭄지수 산정을 위해 결합분포함수는 Clayton copula, 매개변수 추정은 교정방법을 이용하였으며, 입력변수로는 1977~2012년 동안의 강수량 및 토양수분량 자료를 선정하였다. 우리나라에 대한 이변량 결합가뭄지수를 산정한 후, 기존 가뭄지수인 SPI 및 SSI와 같이 시계열 분석, 지역별 분석 및 ROC 분석을 수행하여 활용성을 평가하였다. 분석결과 SPI는 가뭄의 시작, SSI는 가뭄의 해갈을 적절히 고려하였으며, 이변량 결합가뭄지수는 SPI 및 SSI의 거동 특성을 적절히 반영하는 것으로 나타났다. 또한 이변량 결합가뭄지수가 SPI 및 SSI에 비해 ROC score가 높게 산정되었으며, 지역별 분석에서도 지역의 가뭄 상황을 적절히 재현하여 활용성이 우수하게 나타났다. 이변량 결합가뭄지수는 기존 가뭄지수의 해석적 한계를 보완하였다는 측면에서 국내 가뭄해석의 활용성이 높다고 판단된다.

• Korean Journal of Radiology
• /
• 제22권7호
• /
• pp.1213-1224
• /
• 2021

Objective: To develop a machine learning (ML) pipeline based on radiomics to predict Coronavirus Disease 2019 (COVID-19) severity and the future deterioration to critical illness using CT and clinical variables. Materials and Methods: Clinical data were collected from 981 patients from a multi-institutional international cohort with real-time polymerase chain reaction-confirmed COVID-19. Radiomics features were extracted from chest CT of the patients. The data of the cohort were randomly divided into training, validation, and test sets using a 7:1:2 ratio. A ML pipeline consisting of a model to predict severity and time-to-event model to predict progression to critical illness were trained on radiomics features and clinical variables. The receiver operating characteristic area under the curve (ROC-AUC), concordance index (C-index), and time-dependent ROC-AUC were calculated to determine model performance, which was compared with consensus CT severity scores obtained by visual interpretation by radiologists. Results: Among 981 patients with confirmed COVID-19, 274 patients developed critical illness. Radiomics features and clinical variables resulted in the best performance for the prediction of disease severity with a highest test ROC-AUC of 0.76 compared with 0.70 (0.76 vs. 0.70, p = 0.023) for visual CT severity score and clinical variables. The progression prediction model achieved a test C-index of 0.868 when it was based on the combination of CT radiomics and clinical variables compared with 0.767 when based on CT radiomics features alone (p < 0.001), 0.847 when based on clinical variables alone (p = 0.110), and 0.860 when based on the combination of visual CT severity scores and clinical variables (p = 0.549). Furthermore, the model based on the combination of CT radiomics and clinical variables achieved time-dependent ROC-AUCs of 0.897, 0.933, and 0.927 for the prediction of progression risks at 3, 5 and 7 days, respectively. Conclusion: CT radiomics features combined with clinical variables were predictive of COVID-19 severity and progression to critical illness with fairly high accuracy.

• Journal of Preventive Medicine and Public Health
• /
• 제38권2호
• /
• pp.203-207
• /
• 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
• /
• 제34권1호
• /
• pp.3-12
• /
• 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 Yeungnam Medical Science
• /
• 제23권2호
• /
• pp.205-212
• /
• 2006

연구 배경: 고립성 폐결절의 30%~40%는 악성결절의 가능성이 높다. 따라서 고립성 폐결절의 악성감별이 무엇보다 중요하다. 최근 PET/CT가 악성 감별에 널리 사용되며, 또한 그 중요성이 커지고 있다. 이 연구의 목적은 integrated PET/CT의 여러 인자들을 비교하여 고립성 폐결절의 악성 여부를 구별하는데 유용한 지표를 찾기 위한 것이다. 재료 및 방법: 2005년 12월부터 2006년 4월까지 3 cm 미만의 고립성 폐결절로 내원한 환자 19명을 대상으로 하였다. 환자는 integrated PET/CT의 최대 SUV는 FDG 주입 후 1 시간, 2 시간에 측정하였다. 또한 대상 환자 모두 경피세침술로 조직검사를 하였다. Levene's test를 이용하여 integrated PET/CT에서, 조직검사로 확인된 양성결절과 악성결절의 SUV1, SUV2, 보존지수(retention index)의 차이를 비교하였다. 성적: 조직검사 결과 12명이 악성결절로 확인되었고, 7명은 양성결절로 진단되었다. SUV1(p=0.006)과 SUV2(p=0.022)는 양성결절보다 악성결절에서 높았으며 이들 값은 통계적으로 유의하였으나 보존지수는 유의한 차이가 없었다(p=0.526). ROC 곡선을 이용한 양성결절과 악성결절을 구분하는 기준값은 SUV1은 5.40, SUV2는 7.45였다. 이때 SUV1의 민감도는 66.7%, 특이도는 71.4%였으며, SUV2의 민감도는 75%, 특이도는 71.4%였다. 결론: 이상의 결과로 integrated PET/CT에서 일반적으로 널리 사용하고 있는 SUV1은 양성결절과 악성결절을 구별하는데 있어 유용하다는 것을 확인할 수 있었고, 아직 많이 연구되지 않은 SUV2 또한 통계학적으로 의미 있는 차이를 보임을 알 수 있었다. 양성결절과 악성결절을 구분하는 기준값은 각각 5.40, 7.45였다. 연구결과 고립성 폐결절의 악성여부를 구별하는데 SUV1, SUV2 모두 유용하게 사용될 수 있으나 SUV2가 SUV1에 비교하여 특이도는 같으나 더 높은 민감도를 나타내었다.

• Journal of Trauma and Injury
• /
• 제19권1호
• /
• pp.67-73
• /
• 2006

Purpose: The arterial base deficit (BD) has proven to be useful in the evaluation and management of trauma patients. Indicators such as the Triage-Revised Trauma Score (t-RTS) and the systemic inflammatory response syndrome (SIRS) score have been used as triage tools for emergency trauma patients in Korea. The purpose of this study was to assess the usefulness of the initial BD in predicting injury severity and outcome in the trauma population. Methods: The medical records of 308 consecutive trauma patients admitted to the Emergency Center of Masan Samsung Hospital from January 2004 to December 2004 were carefully examined prospectively and retrospectively, and 291 patients were selected as subjects for this research. The SIRS score and the t-RTS were calculated based on the records from the emergency department, and the BD was calculated based on the arterial blood gas analysis obtained within 30 minutes of admission. The efficiency of the three indicators as triage tools was evaluated by using cross tabulations in two - by - two matrices and by using a receiver operating characteristic (ROC) curve analysis. Results: When the mortality was used as the outcome parameter, the sensitivity and the accuracy of the initial BD were higher than those of the SIRS score (p<0.05) and were same as those of the t-RTS. The areas under the ROC curves of the initial BD, the SIRS score, and the t-RTS were $0.740{\pm}0.087$, $0.696{\pm}0.082$, and $0.871{\pm}0.072$, respectively (95% confidence interval). When emergency operation and blood transfusion requirements were used as outcome parameters, the comparisons of the sensitivities and the accuracies of the initial BD and the other two indicators showed the same pattern as mentioned above. The areas under the ROC curves of the initial BD were 0.7~0.8 and were larger than those of the SIRS score (p<0.05). Conclusion: The ability of the initial BD to predict injury severity and outcome was similar to those of the t-RTS and the SIRS score. Therefore, the authors suggest that the initial BD may be used as an alternative to previous triage tools for trauma patients.

• Journal of Trauma and Injury
• /
• 제30권4호
• /
• pp.140-144
• /
• 2017

Purpose: The optic nerve sheath diameter (ONSD) measured by ultrasonography is among the indicators of intracranial pressure (ICP) elevation. However, whether ONSD measurement is useful for initial treatment remains controversial. Thus, this study aimed to investigate the relationship between ONSD measured by computed tomography (CT) and ICP in patients with traumatic brain injury (TBI). Methods: A total of 246 patients with severe trauma from January 1, 2015 until December 31, 2015 were included in the study. A total of 179 patients with brain damage with potential for ICP elevation were included in the TBI group. The remaining 67 patients comprised the non-TBI group. A comparison was made between the two groups. Receiver operating characteristic (ROC) curve analysis was performed to determine the accuracy of ONSD when used as a screening test for the TBI group including those with TBI with midline shift (with elevated ICP). Results: The mean injury severity score (ISS) and glasgow coma scale (GCS) of all patients were $24.2{\pm}6.1$ and $5.4{\pm}0.8$, respectively. The mean ONSD of the TBI group ($5.5{\pm}1.0mm$) was higher than that of the non-TBI group ($4.7{\pm}0.6mm$). Some significant differences in age ($55.3{\pm}18.1$ vs. $49.0{\pm}14.8$, p<0.001), GCS ($11.7{\pm}4.1$ versus $13.3{\pm}3.0$, p<0.001), and ONSD ($5.5{\pm}1.0$ vs. $4.7{\pm}0.6$, p<0.001) were observed between the TBI and the non-TBI group. An ROC analysis was used to assess the correlation between TBI and ONSD. Results showed an area under the ROC curve (AUC) value of 0.752. The same analysis was used in the TBI with midline shift group, which showed an AUC of 0.912. Conclusions: An ONSD of >5.5 mm, measured on CT, is a good indicator of ICP elevation. However, since an ONSD is not sensitive enough to detect an increased ICP, it should only be used as one of the parameters in detecting ICP along with other screening tests.