• Journal of Chest Surgery
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• v.56 no.2
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• pp.99-107
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• 2023

Background: The neutrophil-to-lymphocyte ratio (NLR) has been suggested as a novel predictive marker of cardiovascular disease. However, its prognostic role in patients under-going coronary artery bypass grafting (CABG) is unclear. This study aimed to determine the association between the preoperative NLR and early mortality in patients undergoing CABG. Methods: Cardiac surgery was performed in 2,504 patients at Seoul St. Mary's Hospital from January 2010 to December 2021. This study retrospectively reviewed 920 patients who underwent isolated CABG, excluding those for whom the preoperative NLR was unavailable. The primary endpoints were the 30- and 90-day mortality after isolated CABG. Risk factor analysis was performed using logistic regression analysis. Based on the optimal cut-off value of preoperative NLR on the receiver operating characteristic curve, high and low NLR groups were compared. Results: The 30- and 90-day mortality rates were 3.8% (n=35) and 7.0% (n=64), respectively. In the multivariable analysis, preoperative NLR was significantly associated with 30-day mortality (odds ratio [OR], 1.28; 95% confidence interval [CI], 1.17-1.39; p<0.001) and 90-day mortality (OR, 1.17; 95% CI, 1.07-1.28; p<0.001). The optimal cut-off value of the preoperative NLR was 3.4. Compared to the low NLR group (<3.4), the high NLR group (≥3.4) showed higher 30- and 90-day mortality rates (1.4% vs. 12.1%, p<0.001; 2.8% vs. 21.3%, p<0.001, respectively). Conclusion: Preoperative NLR was strongly associated with early mortality after isolated CABG, especially in patients with a high preoperative NLR (≥3.4). Further studies with larger cohorts are necessary to validate these results.

• Geomechanics and Engineering
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• v.34 no.3
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• pp.267-284
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• 2023

Landslides are one of the most dangerous phenomena and natural disasters. Landslides cause many human and financial losses in most parts of the world, especially in mountainous areas. Due to the climatic conditions and topography, people in the northern and western regions of Iran live with the risk of landslides. One of the measures that can effectively reduce the possible risks of landslides and their crisis management is to identify potential areas prone to landslides through multi-criteria modeling approach. This research aims to model landslide potential area in the Oshvand watershed using a support vector machine algorithm. For this purpose, evidence maps of seven effective factors in the occurrence of landslides namely slope, slope direction, height, distance from the fault, the density of waterways, rainfall, and geology, were prepared. The maps were generated and weighted using the continuous fuzzification method and logistic functions, resulting values in zero and one range as weights. The weighted maps were then combined using the support vector machine algorithm. For the training and testing of the machine, 81 slippery ground points and 81 non-sliding points were used. Modeling procedure was done using four linear, polynomial, Gaussian, and sigmoid kernels. The efficiency of each model was compared using the area under the receiver operating characteristic curve; the root means square error, and the correlation coefficient . Finally, the landslide potential model that was obtained using Gaussian's kernel was selected as the best one for susceptibility of landslides in the Oshvand watershed.

• Journal of The Geomorphological Association of Korea
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• v.27 no.3
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• pp.87-103
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• 2020

The purpose of this study is to evaluate the risk of cropland and man-made infrastructures in a landslide-prone area using a GIS-based method. To achieve this goal, a landslide inventory map was prepared based on aerial photograph analysis as well as field observations. A total of 550 landslides have been counted in the entire study area. For model analysis and validation, extracted landslides were randomly selected and divided into two groups. The landslide causative factors such as slope, aspect, curvature, topographic wetness index, elevation, forest type, forest crown density, geology, land-use, soil drainage, and soil texture were used in the analysis. Moreover, to identify the correlation between landslides and causative factors, pixels were divided into several classes and frequency ratio was also extracted. A landslide susceptibility map was constructed using a bayesian predictive model (BPM) based on the entire events. In the cross validation process, the landslide susceptibility map as well as observation data were plotted with a receiver operating characteristic (ROC) curve then the area under the curve (AUC) was calculated and tried to extract a success rate curve. The results showed that, the BPM produced 85.8% accuracy. We believed that the model was acceptable for the landslide susceptibility analysis of the study area. In addition, for risk assessment, monetary value (local) and vulnerability scale were added for each social thematic data layers, which were then converted into US dollar considering landslide occurrence time. Moreover, the total number of the study area pixels and predictive landslide affected pixels were considered for making a probability table. Matching with the affected number, 5,000 landslide pixels were assumed to run for final calculation. Based on the result, cropland showed the estimated total risk as US $ 35.4 million and man-made infrastructure risk amounted to US $ 39.3 million.

• Journal of The Geomorphological Association of Korea
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• v.26 no.3
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• pp.53-67
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• 2019

The purpose of this study is to identify the quality of landslide susceptibility in a landslide-prone area (Jinbu-myeon, Gangwon-do, South Korea) by spatial prediction modeling approach and compare the results obtained. For this goal, a landslide inventory map was prepared mainly based on past historical information and aerial photographs analysis (Daum Map, 2008), as well as some field observation. Altogether, 550 landslides were counted at the whole study area. Among them, 182 landslides are debris flow and each group of landslides was constructed in the inventory map separately. Then, the landslide inventory was randomly selected through Excel; 50% landslide was used for model analysis and the remaining 50% was used for validation purpose. Total 12 contributing factors, such as slope, aspect, curvature, topographic wetness index (TWI), elevation, forest type, forest timber diameter, forest crown density, geology, landuse, soil depth, and soil drainage were used in the analysis. Moreover, to find out the co-relation between landslide causative factors and incidents landslide, pixels were divided into several classes and frequency ratio for individual class was extracted. Eventually, six landslide susceptibility maps were constructed using the Bayesian Predictive Discriminant (BPD), Empirical Likelihood Ratio (ELR), and Linear Regression Method (LRM) models based on different category dada. Finally, in the cross validation process, landslide susceptibility map was plotted with a receiver operating characteristic (ROC) curve and calculated the area under the curve (AUC) and tried to extract success rate curve. The result showed that Bayesian, likelihood and linear models were of 85.52%, 85.23%, and 83.49% accuracy respectively for total data. Subsequently, in the category of debris flow landslide, results are little better compare with total data and its contained 86.33%, 85.53% and 84.17% accuracy. It means all three models were reasonable methods for landslide susceptibility analysis. The models have proved to produce reliable predictions for regional spatial planning or land-use planning.

• Journal of The Geomorphological Association of Korea
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• v.27 no.2
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• pp.65-80
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• 2020

This paper deals with risk assessment of life in a landslide-prone area by a GIS-based modeling method. Landslide susceptibility maps can provide a probability of landslide prone areas to mitigate or proper control this problems and to take any development plan and disaster management. A landslide inventory map of the study area was prepared based on past historical information and aerial photography analysis. A total of 550 landslides have been counted at the whole study area. The extracted landslides were randomly selected and divided into two different groups, 50% of the landslides were used for model calibration and the other were used for validation purpose. Eleven causative factors (continuous and thematic) such as slope, aspect, curvature, topographic wetness index, elevation, forest type, forest crown density, geology, land-use, soil drainage, and soil texture were used in hazard analysis. The correlation between landslides and these factors, pixels were divided into several classes and frequency ratio was also extracted. Eventually, a landslide susceptibility map was constructed using a logistic regression model based on entire events. Moreover, the landslide susceptibility map was plotted with a receiver operating characteristic (ROC) curve and calculated the area under the curve (AUC) and tried to extract a success rate curve. Based on the results, logistic regression produced an 85.18% accuracy, so we believed that the model was reliable and acceptable for the landslide susceptibility analysis on the study area. In addition, for risk assessment, vulnerability scale were added for social thematic data layer. The study area predictive landslide affected pixels 2,000 and 5,000 were also calculated for making a probability table. In final calculation, the 2,000 predictive landslide affected pixels were assumed to run. The total population causalities were estimated as 7.75 person that was relatively close to the actual number published in Korean Annual Disaster Report, 2006.

• Journal of Medicine and Life Science
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• v.20 no.3
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• pp.115-125
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• 2023

Arteriovenous fistula flow dysfunction is the leading cause of vascular access thrombosis and loss in patients undergoing hemodialysis. However, data regarding the influence of access flow rate measurements on the long-term outcomes of access are limited. This study aims to identify accesses at a high risk of thrombosis and loss among patients undergoing hemodialysis by measuring the access flow rate and exploring an optimal threshold value for predicting future access thrombosis. We enrolled 220 patients with arteriovenous fistula undergoing hemodialysis. The primary outcome was the occurrence of access thrombosis. Access flow rates were measured monthly using the ultrasound dilution method and were averaged using all measurements from patients with patent access. In patients experienced access thrombosis, those immediately before the thrombosis were selected. Using these data, we calculated the access flow rate threshold for thrombosis occurrence by analyzing the receiver operating characteristic curve, and the patients were divided into two groups according to whether access flow rates were higher or lower than 400 mL/min. During a median follow-up period of 3.1 years, 4,510 access flows were measured (median measurements per patient, 33 times; interquartile range, 11-54). A total of 65 access thromboses and 19 abandonments were observed. Access thrombosis and loss were higher in the lowflow group than in the high-flow group. This study revealed that low access flow rates are strongly associated with access thrombosis occurrence and subsequent loss of arteriovenous fistulas in patients undergoing hemodialysis.

• Biomolecules & Therapeutics
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• v.31 no.6
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• pp.674-681
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• 2023

Bile pigment, bilirubin, and biliverdin concentrations may change as a results of biliary tract cancer (BTC) altering the mechanisms of radical oxidation and heme breakdown. We explored whether changes in bile pigment components could help distinguish BTC from benign biliary illness by evaluating alterations in patients with BTC. We collected bile fluid from 15 patients with a common bile duct stone (CBD group) and 63 individuals with BTC (BTC group). We examined the bile fluid's bilirubin, biliverdin reductase (BVR), heme oxygenase (HO-1), and bacterial taxonomic abundance. Serum bilirubin levels had no impact on the amounts of bile HO-1, BVR, or bilirubin. In comparison to the control group, the BTC group had considerably higher amounts of HO-1, BVR, and bilirubin in the bile. The areas under the curve for the receiver operating characteristic curve analyses of the BVR and HO-1 were 0.832 (p<0.001) and 0.891 (p<0.001), respectively. Firmicutes was the most prevalent phylum in both CBD and BTC, according to a taxonomic abundance analysis, however the Firmicutes/Bacteroidetes ratio was substantially greater in the BTC group than in the CBD group. The findings of this study showed that, regardless of the existence of obstructive jaundice, biliary carcinogenesis impacts heme degradation and bile pigmentation, and that the bile pigment components HO-1, BVR, and bilirubin in bile fluid have a diagnostic significance in BTC. In tissue biopsies for the diagnosis of BTC, particularly for distinguishing BTC from benign biliary strictures, bile pigment components can be used as additional biomarkers.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.4 no.4
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• pp.159-176
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• 2023

The conservation of the raccoon dog (Nyctereutes procyonoides) in South Korea requires the protection and preservation of natural habitats while additionally ensuring coexistence with human activities. Applying habitat map modeling techniques provides information regarding the distributional patterns of raccoon dogs and assists in the development of future conservation strategies. The purpose of this study is to generate potential habitat distribution maps for the raccoon dog in South Korea using geospatial technology-based models. These models include the frequency ratio (FR) as a bivariate statistical approach, the group method of data handling (GMDH) as a machine learning algorithm, and convolutional neural network (CNN) and long short-term memory (LSTM) as deep learning algorithms. Moreover, the imperialist competitive algorithm (ICA) is used to fine-tune the hyperparameters of the machine learning and deep learning models. Moreover, there are 14 habitat characteristics used for developing the models: elevation, slope, valley depth, topographic wetness index, terrain roughness index, slope height, surface area, slope length and steepness factor (LS factor), normalized difference vegetation index, normalized difference water index, distance to drainage, distance to roads, drainage density, and morphometric features. The accuracy of prediction is evaluated using the area under the receiver operating characteristic curve. The results indicate comparable performances of all models. However, the CNN demonstrates superior capacity for prediction, achieving accuracies of 76.3% and 75.7% for the training and validation processes, respectively. The maps of potential habitat distribution are generated for five different levels of potentiality: very low, low, moderate, high, and very high.

• Journal of Korean Neurosurgical Society
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• v.66 no.6
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• pp.664-671
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• 2023

Objective : The optic nerve sheath diameter (ONSD)/eyeball transverse diameter (ETD) ratio is a more reliable marker of intracranial pressure than the ONSD alone. We aimed to investigate the predictive value of the ONSD/ETD ratio (OER) for neurological outcomes in patients with aneurysmal subarachnoid hemorrhage (aSAH). Methods : Adult patients with aSAH who visited the emergency department of a tertiary hospital connected to a South Korean university between January 2015 and December 2021 were included. Data on patient characteristics and brain computed tomography scan findings, including the ONSD and ETD, were collected using a predefined protocol. According to the neurological outcome at hospital discharge, the patients were divided into the unfavorable neurological outcome (UNO; cerebral performance category [CPC] score 3-5) and the favorable neurological outcome (FNO; CPC score 1-2) groups. The primary outcome was the association between the OER and neurological outcomes in patients with aSAH. Results : A total of 171 patients were included in the study, of whom 118 patients (69%) had UNO. Neither the ONSD (p=0.075) nor ETD (p=0.403) showed significant differences between the two groups. However, the OER was significantly higher in the UNO group in the univariate analysis (p=0.045). The area under the receiver operating characteristic curve of the OER for predicting UNO was 0.603 (p=0.031). There was no independent relationship between the OER and UNO in the multivariate logistic regression analysis (adjusted odds ratio, 0.010; p=0.576). Conclusion : The OER was significantly higher in patients with UNO than in those with FNO, and the OER was more reliable than the ONSD alone. However, the OER had limited utility in predicting UNO in patients with aSAH.

• Imaging Science in Dentistry
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• v.53 no.4
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• pp.375-381
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• 2023

Purpose: This study assessed the diagnostic performance of stitched and non-stitched cross-sectional cone-beam computed tomography (CBCT) images of non-displaced ovine mandibular fractures. Materials and Methods: In this ex vivo study, non-displaced fractures were artificially created in 10 ovine mandibles (20 hemi-mandibles) using a hammer. The control group comprised 8 hemi-mandibles. The non-displaced fracture lines were oblique or vertical, <0.5 mm wide, 10-20 mm long, and only in the buccal or lingual cortex. Fracture lines in the ramus and posterior mandible were created to be at the interface or borders of the 2 stitched images. CBCT images were obtained from the specimens with an 80 mm×80 mm field of view before and after fracture induction. OnDemand software (Cybermed, Seoul, Korea) was used for stitching the CBCT images. Four observers evaluated 56 (28 stitched and 28 non-stitched) images to detect fracture lines. The diagnostic performance of stitched and non-stitched images was assessed by calculating the area under the receiver operating characteristic curve (AUC). Sensitivity and specificity values were also calculated (alpha=0.05). Results: The AUC was calculated to be 0.862 and 0.825 for the stitched and non-stitched images, respectively (P=0.747). The sensitivity and specificity were 90% and 75% for the non-stitched images and 85% and 87% for the stitched images, respectively. The inter-observer reliability was shown by a Fleiss kappa coefficient of 0.79, indicating good agreement. Conclusion: No significant difference was found in the diagnostic performance of stitched and non-stitched cross-sectional CBCT images of non-displaced fractures of the ovine mandible.