• Journal of the Korean Wood Science and Technology
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• v.48 no.5
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• pp.591-607
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• 2020

This study was aimed to investigate the changes of chemical composition of the volatile organic compounds (VOCs) emitted from red pine needles in the process of needle abscission or senescence. The VOCs in intact, senescent, and litter red pine needle samples were analyzed by headspace-solid phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC/MS). And then, multivariate statistical interpretation of the processed data sets was conducted to investigate similarities and dissimilarities of the needle samples. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were used to investigate the dataset structure and discrimination between samples, respectively. From the data preview, the levels of major components of VOCs from needles were not significantly different between needle samples. By PCA investigation, the data reduction according to classification based on the chlorophyll a / chlorophyll b (Ca/Cb) ratio were found to be ideal for differentiating intact, senescent, and litter needles. The following OPLS-DA taking Ca/Cb ratio as y-variables showed that needle samples were well grouped on score plot and had the significant discriminant compounds, respectively. Several compounds had significantly correlated with Ca/Cb ratio in a bivariate correlation analysis. Notably, the litter needles had a higher content of oxidized compounds than the intact needles. In summary, we found that chemical compositions of VOCs between intact, senescent, and litter needles are different each other and several compounds reflect characteristic of needle.

• Journal of Korean Neurosurgical Society
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• v.59 no.1
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• pp.44-51
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• 2016

Objective : Malignant gliomas with neuronal marker expression (MGwNM) are rare and poorly characterized. Increasingly diverse types of MGwNM have been described and these reported cases underscore the dilemmas in the classification and diagnosis of those tumors. The aim of this study is to provide additional insights into MGwNM and present the clinicopathological features of 18 patients. Methods : We reviewed the medical records of 18 patients diagnosed as MGwNM at our institute between January 2006 and December 2012. Macroscopic total resection was performed in 11 patients (61%). We evaluated the methylation status of $O^6$-methylguanine-DNA methyltransferase (MGMT) and expression of isocitrate dehydrogenase 1 (IDH-1) in all cases, and deletions of 1p and 19q in available cases. Results : The estimated median overall survival was 21.2 months. The median progression-free survival was 6.3 months. Six patients (33%) had MGMT methylation but IDH1 mutation was found in only one patient (6%). Gene analysis for 1p19q performed in nine patients revealed no deletion in six, 19q deletion only in two, and 1p deletion only in one. The extent of resection was significantly correlated with progression free survival on both univariate analysis and multivariate analysis (p=0.002 and p=0.013, respectively). Conclusion : In this study, the overall survival of MGwNM was not superior to glioblastoma. The extent of resection has a significant prognostic impact on progression-free survival. Further studies of the prognostic factors related to chemo-radio therapy, similar to studies with glioblastoma, are mandatory to improve survival.

• Neurospine
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• v.15 no.4
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• pp.376-382
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• 2018

Objective: The purpose of this study was to evaluate factors associated with inpatient admission following 2-level cervical disc arthroplasty (CDA). A secondary aim was to compare outcomes between those treated on an inpatient versus outpatient basis. Methods: Using data from the American College of Surgeons National Surgical Quality Improvement Program database, multivariate logistic regression analysis was used to assess the independent effect of each variable on inpatient or outpatient selection for surgery. Statistical significance was defined by p-values <0.05. The factors considered were age, sex, body mass index (BMI), smoking status, American Society of Anesthesiologists physical status classification, and comorbidities including hypertension, diabetes, history of dyspnea or chronic obstructive pulmonary disease, previous cardiac intervention or surgery, steroid usage, and history of bleeding. In addition, whether the operation was performed by an orthopedic or neurosurgical specialist was analyzed. Results: The number of 2-level CDA procedures increased from 6 cases reported in 2014 to 142 in 2016, although a statistically significant increase in the number of outpatient cases performed was not seen (p=0.2). The factors found to be significantly associated with inpatient status following surgery were BMI (p=0.019) and diabetes mellitus requiring insulin (p=0.043). There were no significant differences in complication and readmission rates between the inpatient and outpatient groups. Conclusion: Patients undergoing inpatient 2-level CDA had significantly higher rates of obesity and diabetes requiring insulin than did patients undergoing the same procedure in the outpatient setting. With no difference in complication or readmission rates, 2-level CDA may be considered safe in the outpatient setting in appropriately selected patients.

• Journal of the Korean Medical Association
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• v.61 no.11
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• pp.687-698
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• 2018

Inappropriate antibiotic use significantly contributes to antibiotic resistance, resulting in reduced antibiotic efficacy and an increased burden of disease. The objective of this study was to investigate the characteristics of prescribers whose antibiotics use was high and to explore factors affecting the use of antibiotics by medical institutions. This study analyzed the National Health Insurance claims data from 2015. Antibiotic prescription data were analyzed in terms of the number of defined daily doses per 1,000 patients per day, according to the World Health Organization anatomical-therapeutic-chemical classification and methodologies for measuring the defined daily dose. We investigated the characteristics of prescribers and medical institutions with high antibiotic use. Multivariate regression analyses were performed on the basis of characteristics of the medical institution (number of patients, type of medical institution [hospital or clinic], age of the physician, etc.). The number of patients and number of beds were found to be significant factors affecting antibiotic use in hospitals, and the number of patients, region, and medical department were significant factors affecting antibiotic use at the level of medical institutions. These findings are expected to help policy-makers to better target future interventions to promote prudent antibiotic prescription.

• Journal of Chest Surgery
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• v.52 no.5
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• pp.342-352
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• 2019

Background: Smokers with lung adenocarcinoma have a worse prognosis than those who have never smoked; the reasons for this are unclear. We aimed to elucidate the impact of smoking on patients' prognosis and the association between smoking and clinicopathologic factors, particularly histologic subtypes. Methods: We reviewed the records of 233 patients with pathologic stage T1-4N0-2M0 lung adenocarcinomas who underwent surgery between January 2004 and July 2015. The histologic subtypes of tumors were reassessed according to the 2015 World Health Organization classification. Results: In total, 114 patients had a history of smoking. The overall survival probabilities differed between never-smokers and ever-smokers (80.8% and 65.1%, respectively; p=0.003). In multivariate analyses, the predominant histologic subtype was an independent poor prognostic factor. Smoking history and tumor size >3 cm were independent predictors of solid or micropapillary (SOL/MIP)-predominance in the logistic regression analysis. Smoking quantity (pack-years) in patients with SOL/MIP-predominant tumors was greater than in those with lepidic-predominant tumors (p=0.000). However, there was no significant difference in smoking quantity between patients with SOL/MIP-predominant tumors and those whose tumors had non-predominant SOL/MIP components (p=0.150). Conclusion: Smoking was found to be closely associated with SOL/MIP-predominance in lung adenocarcinoma. Greater smoking quantity was related to the presence of a SOL/MIP component.

• Korean Journal of Clinical Pharmacy
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• v.31 no.1
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• pp.27-34
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• 2021

Objective: To analyze osteoporosis treatment patterns and teriparatide prescription-associated factors in Korea by using a national health insurance claims database. Methods: We utilized the Health Insurance Review & Assessment Service National Patients Sample claims database to identify patients (aged ≥50 years) with at least one osteoporosis claim (International Classification of Disease 10th revision code: M80, M81, M82) and at least one prescription for osteoporosis medication (antiresorptive agents: bisphosphonates, selective estrogen receptor modulators, denosumab, and calcitonin; bone-forming agent: teriparatide) in 2018. Demographic characteristics and healthcare utilization patterns were analyzed. Factors associated with teriparatide prescriptions were assessed using a multivariate logistic regression model. Results: Records showed that 44,815 patients were prescribed osteoporosis medications in 2018; the percentage of patients prescribed each treatment was as follows: 86.6% bisphosphonates, 13.9% selective estrogen receptor modulators, 3.1% calcitonin, 2.1% denosumab, and 0.7% teriparatide. A greater proportion of patients prescribed teriparatide were ≥75 years (53.4% vs. 33.8%) and had fractures (63.9% vs. 12.8%) compared to the same for antiresorptives (p<0.001). Patients prescribed teriparatide had higher Charlson comorbidity index values (1.2±1.3 vs. 0.9±1.2) and were more frequently hospitalized (0.8±1.3 vs. 0.1±0.5) than those prescribed antiresorptives (p<0.001). Elderly patients (≥75 years old; adjusted OR=1.66; 95% CI 1.16-2.38) and those with fractures (adjusted OR=6.23; 95% CI 4.76-8.14) were more likely to be prescribed teriparatide than antiresorptives. Conclusion: Patients prescribed teriparatide were older and more likely to have severe osteoporosis than those prescribed antiresorptives.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.25 no.1
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• pp.61-69
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• 2022

Purpose: Studies in adults have shown an increasing incidence of Clostridioides difficile infection (CDI) in patients hospitalized with acute pancreatitis (AP). There is lack of epidemiological data on CDI and its impact on hospitalized pediatric patients with AP. Methods: We analyzed the National Inpatient Sample and Kids' Inpatient Database between the years 2003 and 2016 and included all patients (age <21 years) with a primary diagnosis of AP using specific International Classification of Diseases codes. We compared clinical outcomes between children with CDI and those without CDI. Our primary outcome was severe AP and secondary outcomes included length of stay and hospital charges. Results: A total of 123,240 hospitalizations related to AP were analyzed and CDI was noted in 0.6% of the hospital. The prevalence rate of CDI doubled from 0.4% (2003) to 0.8% (2016), p=0.03. AP patients with CDI had increased comorbidities, and also underwent more invasive surgical procedures, p<0.05. AP patients with CDI had a higher in-hospital mortality rate and increased prevalence of severe AP, p<0.001. Multivariate regression models showed that CDI was associated with 2.4 times (confidence interval [CI]: 1.91 to 3.01, p<0.001) increased odds of severe AP. CDI patients had 7.24 (CI: 6.81 to 7.67, p<0.001) additional hospital days while incurring $59,032 (CI: 54,050 to 64,014, p<0.001) additional hospitalization charges. Conclusion: CDI in pediatric patients with AP is associated with adverse clinical outcomes and increased healthcare resource utilization. Further studies are needed to elucidate this association to prevent the development of CDI and to improve outcomes.

• Journal of Gastric Cancer
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• v.22 no.3
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• pp.210-219
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• 2022

Purpose: Completion total gastrectomy (CTG) for remnant gastric cancer (RGC) is a technically demanding procedure and associated with increased morbidity. The present study aimed to evaluate postoperative complications and their risk factors following surgery for RGC after initial partial gastrectomy due to gastric cancer excluding peptic ulcer. Materials and Methods: We retrospectively reviewed the data of 107 patients who had previously undergone an initial gastric cancer surgery and subsequently underwent CTG for RGC between March 2002 and December 2020. The postoperative complications were graded using the Clavien-Dindo classification. Logistic regression analyses were used to determine the risk factors for complications. Results: Postoperative complications occurred in 34.6% (37/107) of the patients. Intra-abdominal abscess was the most common complication. The significant risk factors for overall complications were multi-visceral resections, longer operation time, and high estimated blood loss in the univariate analysis. The independent risk factors were multi-visceral resection (odds ratio [OR], 2.832; 95% confidence interval [CI], 1.094-7.333; P=0.032) and longer operation time (OR, 1.005; 95% CI, 1.001-1.011; P=0.036) in the multivariate analysis. Previous reconstruction type, minimally invasive approach, and current stage were not associated with the overall complications. Conclusions: Multi-visceral resection and long operation time were significant risk factors for the occurrence of complications following CTG rather than the RGC stage or surgical approach. When multi-visceral resection is required, a more meticulous surgical procedure is warranted to improve the postoperative complications during CTG for RGC after an initial gastric cancer surgery.

• Journal of Broadcast Engineering
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• v.27 no.6
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• pp.872-884
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• 2022

With the development of the IoT industry, different types of time series data are being generated in various industries, and it is evolving into research that reproduces and utilizes it through re-integration. In addition, due to data processing speed and issues of the utilization system in the actual industry, there is a growing tendency to compress the size of data when using time series data and integrate it. However, since the guidelines for integrating time series data are not clear and each characteristic such as data description time interval and time section is different, it is difficult to use it after batch integration. In this paper, two integration methods are proposed based on the integration criteria setting method and the problems that arise during integration of time series data. Based on this, integration framework of a heterogeneous time series data was constructed that is considered the characteristics of time series data, and it was confirmed that different heterogeneous time series data compressed can be used for integration and various machine learning.

• Smart Structures and Systems
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• v.29 no.1
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• pp.117-127
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• 2022

Data anomalies seriously threaten the reliability of the bridge structural health monitoring system and may trigger system misjudgment. To overcome the above problem, an efficient and accurate data anomaly detection method is desiderated. Traditional anomaly detection methods extract various abnormal features as the key indicators to identify data anomalies. Then set thresholds artificially for various features to identify specific anomalies, which is the artificial experience method. However, limited by the poor generalization ability among sensors, this method often leads to high labor costs. Another approach to anomaly detection is a data-driven approach based on machine learning methods. Among these, the bidirectional long-short memory neural network (BiLSTM), as an effective classification method, excels at finding complex relationships in multivariate time series data. However, training unprocessed original signals often leads to low computation efficiency and poor convergence, for lacking appropriate feature selection. Therefore, this article combines the advantages of the two methods by proposing a deep learning method with manual experience statistical features fed into it. Experimental comparative studies illustrate that the BiLSTM model with appropriate feature input has an accuracy rate of over 87-94%. Meanwhile, this paper provides basic principles of data cleaning and discusses the typical features of various anomalies. Furthermore, the optimization strategies of the feature space selection based on artificial experience are also highlighted.