• 대한족부족관절학회지
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• 제19권2호
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• pp.51-57
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• 2015

Purpose: Minimal incision distal metatarsal osteotomy (MIDMO) is known to be an effective surgical procedure for mild to moderate hallux valgus. However, the result of MIDMO on moderate to severe hallux valgus is controversial; therefore, we investigated the radiological and clinical results of MIDMO on moderate to severe hallux valgus. Materials and Methods: We reviewed 51 feet (48 patients) with moderate to severe hallux valgus. The mean age was 67.0 years and the mean follow-up period was 32.2 months. Radiological data of hallux valgus angle, first intermetatarsal angle, and distal metatarsal articular angle on plain radiographs were analyzed. Recurrence, union, lateral translation of distal fragment and angulation were also analyzed. The clinical data were obtained using American Orthopaedic Foot and Ankle Society (AOFAS) score of preoperation and last follow-up. Receiver operating characteristic (ROC) curve was used to determine a cut-off value. Results: The mean hallux valgus angle measured at preoperation was $37.7^{\circ}$ and $15.9^{\circ}$ at last follow-up. The mean first intermetatarsal angle of preoperation and last follow-up were $15.2^{\circ}$ and $8.3^{\circ}$. The mean distal metatarsal articular angle changed from $12.6^{\circ}$ at preoperation to $7.8^{\circ}$ at last follow-up. Preoperative hallux valgus angle (p=0.0051) and distal metatarsal articular angle (p=0.0078) were statistically significant factors affecting postoperative AOFAS score. Cut-off value of each was $37^{\circ}$ and 13o, respectively. Lateral translation of distal fragment in 5 recurrent cases was 23.0% compared to 45.3% of 46 non-recurrent cases. The result was statistically significant and the cut-off value was 38%. Conclusion: Sufficient lateral translation over 38% in MIDMO on moderate to severe hallux valgus patients with preoperative hallux valgus angle under $37^{\circ}$ and distal metatarsal articular angle under $13^{\circ}$ can lead to good clinical results without recurrence.

• Imaging Science in Dentistry
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• 제39권1호
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• pp.13-18
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• 2009

Purpose: This study was designed to determine a proper threshold value and opacity in three-dimensional CT volume rendering of oral and maxillofacial area. Materials and Methods: Three-dimensional CT data obtained from 50 persons who were done orthognatic surgery in department of oral and maxillofacial radiology of Seoul National University retrospectively. 12 volume rendering post-processing protocols of combination of threshold(100HU, 150HU, 221HU, 270HU) and opacity (58%, 80%, 90%) were applied. Five observers independently evaluated image quality using a five-point range scale. The results were analyzed by receiver operating characteristic curves, ANOVA and Kappa value. And three oromaxillofacial surgeons chose the all images that they thought proper clinically in the all of images. Results: Analysis using ROC curves revealed the area under each curve which indicated a diagnostic accuracy. The highest diagnostic accuracy appear with 100HU and 58% opacity. and the lowest diagnostic accuracy appear with 221HU and 58% opacity that are being used protocol in department of oral and maxillofacial radiology of Seoul National University. But, no statistically significant difference was noted between any of the protocols. And the number of proper images clinically that chosen by three oromaxillofacial surgeons is the largest in the cases of protocol 8 (221HU, opacity 80%) and protocol 11 (270HU, opacity 80%) in one after the other. Conclusion: Threshold and opacity in volume rendering can be controled easily and these can be causes of making an diagnostic accuracy. So we need to select proper values of these factors.

• 한국환경보건학회지
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• 제40권6호
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• pp.492-501
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• 2014

Objectives: The purpose of this study was to assess the validity of self-reported cigarette smoking status and investigate factors associated with the accuracy self-reported and measured urinary cotinine in Korean adults. Methods: We used data from the $1^{st}$ Korean National Environmental Health Survey (2009-2011) among adults aged ${\geq}19$ years (N=6,246). The survey examined self-reported smoking status, and urinary cotinine was regarded as the biomarker of exposure to tobacco smoke. Urinary cotinine was analyzed using a gas chromatography-mass spectrometry (GC/MS) and data analysis was conducted using IBM SPSS version 20.0, which uses the sample weight and calculates variance estimates to adjust for the unequal probability of selection into the survey. Results: We calculated a cut-off point (53.3 ug/L) by using a ROC (Receiver Operating Characteristic) curve. The smoking prevalence was 24.6% based on self-reported data and 28.2% based on urinary cotinine concentrations. When we assessed the agreement between self-reported and urinary cotinine, we found an average agreement of 97.7% among self-reported smokers and 94.5% among self-reported non-smokers. Among self-reported smokers, factors affected the discrepancy were age, household economic status and average number of cigarettes smoked per day. On the other hand, gender, former smoking experience, and exposure to SHS (second hand smoke) were associated with discrepancies among self-reported non-smokers. Conclusion: These results suggest that self-reported data on smoking status provide a valid estimate of actual smoking status. In future research, we will conduct a continuous monitoring study for reliability verification of the data to reduce potential interpretation errors.

• Asian Pacific Journal of Cancer Prevention
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• 제16권12호
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• pp.5095-5099
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• 2015

Background: The statistical methods to analyze and predict the related dangerous factors of deep fungal infection in lung cancer patients were several, such as logic regression analysis, meta-analysis, multivariate Cox proportional hazards model analysis, retrospective analysis, and so on, but the results are inconsistent. Materials and Methods: A total of 696 patients with lung cancer were enrolled. The factors were compared employing Student's t-test or the Mann-Whitney test or the Chi-square test and variables that were significantly related to the presence of deep fungal infection selected as candidates for input into the final artificial neural network analysis (ANN) model. The receiver operating characteristic (ROC) and area under curve (AUC) were used to evaluate the performance of the artificial neural network (ANN) model and logistic regression (LR) model. Results: The prevalence of deep fungal infection from lung cancer in this entire study population was 32.04%(223/696), deep fungal infections occur in sputum specimens 44.05%(200/454). The ratio of candida albicans was 86.99% (194/223) in the total fungi. It was demonstrated that older (${\geq}65$ years), use of antibiotics, low serum albumin concentrations (${\leq}37.18g/L$), radiotherapy, surgery, low hemoglobin hyperlipidemia (${\leq}93.67g/L$), long time of hospitalization (${\geq}14$days) were apt to deep fungal infection and the ANN model consisted of the seven factors. The AUC of ANN model($0.829{\pm}0.019$)was higher than that of LR model ($0.756{\pm}0.021$). Conclusions: The artificial neural network model with variables consisting of age, use of antibiotics, serum albumin concentrations, received radiotherapy, received surgery, hemoglobin, time of hospitalization should be useful for predicting the deep fungal infection in lung cancer.

• IMMUNE NETWORK
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• 제6권1호
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• pp.43-51
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• 2006

Background: The DR-$70^{TM}$ immunoassay is a newly developed cancer diagnostic test which quantifies the serum fibrin degradation products (FDP), produced during fibrinolysis, by antibody reaction. The purpose of this study was to evaluate the potential of DR-$70^{TM}$ Immunoassay in screening malignant tumor. Methods: Sample subjects were 4,169 adults, both male and female, who visited the health promotion center of a general hospital from March 2004 to April 2005 and underwent the DR-$70^{TM}$ immunoassay test and other tests for cancer diagnosis. The patient group was defined as 42 adults out of the sample subjects who were newly diagnosed with cancer during the same time period when the DR-$70^{TM}$ immunoassay test was performed. Final confirmation of a malignant tumor was made by pathological analysis. Results: The mean DR-$70^{TM}$ level was $0.83{\pm}0.65{\mu}g/ml$ (range: 0.00 (0.0001)${\sim}7.42{\mu}g/ml)$ in the control group (n=4,127) as opposed to $2.70{\pm}2.33{\mu}g/ml$ (range: $0.12{\sim}9.30{\mu}g/ml)$ in the cancer group (n=42), and statistical significance was established (p<0.0001, Student t-test). When categorized by the type of malignant tumor, all cancer patients with the exception of the subgroups of colon and rectal cancer showed significantly higher mean DR-$70^{TM}$ levels compared with the control group (p<0.0001, Kruscal-Wallis test). The receiver operating characteristic (ROC) curve analysis revealed ${\geq}1.091{\mu}g/ml$ as the best cut-off value. Using this cut-off value, the DR-$70^{TM}$ immunoassay produced a sensitivity of 71.4%, a specificity of 70.1%, a positive predictability of 69.4%, and a negative predictability of 69.2% (1). Conclusion: A significant increase in the mean DR-$70^{TM}$ value was observed in the cancer group (thyroidal, gastric, breast, hepatic and ovarian) com pared with the control group. In particular, the specificity and sensitivity of the DR-$70^{TM}$ immunoassay was relatively high in the subgroups of breast, gastric, and thyroidal cancer patients. There is need for further studies on a large number of malignant tumor patients to see how the DR-$70^{TM}$ level might be changed according to the differentiation grade and postoperative prognosis of the malignant tumor.

• Tuberculosis and Respiratory Diseases
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• 제71권1호
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• pp.8-14
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• 2011

Background: MicroRNAs (miRNAs) have demonstrated their potential as biomarkers for lung cancer diagnosis. In recent years, miRNAs have been found in body fluids such as serum, plasma, urine and saliva. Circulating miRNAs are highly stable and resistant to RNase activity along with, extreme pH and temperatures in serum and plasma. In this study, we investigated serum miRNA profiles that can be used as a diagnostic biomarker of non-small cell lung cancer (NSCLC). Methods: We compared the expression profile of miRNAs in the plasma of patients diagnosed with lung cancer using an miRNA microarray. The data from this assay were validated by quantitative real-time PCR (qRT-PCR). Results: Six miRNAs were overexpressed and three miRNAs were underexpressed in both tissue and serum from squamous cell carcinoma (SCC) patients. Sixteen miRNAs were overexpressed and twenty two miRNAs were underexpressed in both tissue and serum from adenocarcinoma (AC) patients. Of the four miRNAs chosen for qRT-PCR analysis, the expression of miR-23a was consistent with microarray results from AC patients. Receiver operating characteristic (ROC) curve analyses were done and revealed that the level of serum miR-23a was a potential marker for discriminating AC patients from chronic obstructive pulmonary disease (COPD) patients. Conclusion: Although a small number of patients were examined, the results from our study suggest that serum miR-23a can be used in the diagnosis of AC.

• 전자공학회논문지SC
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• 제48권4호
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• pp.1-9
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• 2011

쇼크(shock)란 조직에 필요한 산소 요구량과 공급 간의 불균형에 의해 유발되는 임상증후군을 말한다. 환자의 치료효과와 생존율 향상을 위해서 쇼크의 조기 진단은 매우 중요하다. 그러나 현재 쇼크 진단에 사용되는 맥박, 혈압 등 생체 징후의 경우 출혈 정도를 제대로 반영하지 못하여 환자에 대한 처치가 늦어질 수 있다. 따라서 쇼크의 조기 진단을 위한 많은 연구들이 진행되어 왔으며, 조직의 저산소증, 대사성 산증을 반영해주는 지표인 젖산 농도와 관류 측정의 유용성이 입증된 바 있다. 본 연구에서는 흰쥐를 대상으로 정량적 출혈을 유도한 후, 젖산 농도 측정과 laser Doppler flowmeter를 통해 관류를 측정하였으며, 지혈 후 젖산 농도/관류의 비(ratio)를 생존 예측을 위한 새로운 지표로써 제안하였다. 새로 제안된 지표를 통한 생존예측을 ROC 커브 방법에 적용한 결과, 민감도 90.0%, 특이도 96.7%, 정확도 94.0%를 보였으며, 생존군과 사망군 간 새로운 지표의 유의한 차이도 가장 조기에 보여주었다. 향후 임상 적용 연구를 통해 새롭게 제안한 지표의 임상 적용이 가능하다면, 쇼크 환자를 조기 진단하고 치료효과를 높일 수 있을 것으로 생각된다.

• Journal of Dental Anesthesia and Pain Medicine
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• 제20권5호
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• pp.293-301
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• 2020

Background: The success rate of intubation under direct laryngoscopy is greatly influenced by laryngoscopic grade using the Cormack-Lehane classification. However, it is not known whether grade under direct laryngoscopy can also affects the success rate of nasotracheal intubation using a fiberoptic bronchoscpe, so this study investigated the same. In addition, we investigated other factors that influence the success rate of fiberoptic nasotracheal intubation (FNI). Methods: FNI was performed by 18 anesthesiology residents under general anesthesia in patients over 15 years of age who underwent elective oral and maxillofacial operations. In all patients, the Mallampati grade was measured. Laryngeal view grade under direct laryngoscopy, and the degree of secretion and bleeding in the oral cavity was measured and divided into 3 grades. The time required for successful FNI was measured. If the intubation time was > 5 minutes, it was evaluated as a failure and the airway was managed by another method. The failure rate was evaluated using appropriate statistical method. Receiver operating characteristic (ROC) curves and area under the curve (AUC) were also measured. Results: A total of 650 patients were included in the study, and the failure rate of FNI was 4.5%. The patient's sex, age, height, weight, Mallampati, and laryngoscopic view grade did not affect the success rate of FNI (P > 0.05). BMI, the number of FNI performed by residents (P = 0.03), secretion (P < 0.001), and bleeding (P < 0.001) grades influenced the success rate. The AUCs of bleeding and secretion were 0.864 and 0.798, respectively, but the AUC of BMI, the number of FNI performed by residents, Mallampati, and laryngoscopic view grade were 0.527, 0.616, 0.614, and 0.544, respectively. Conclusion: Unlike in intubation under direct laryngoscopy, in the case of FNI, oral secretion and nasal bleeding had a significant effect on FNI difficulty than Mallampati grade or Laryngeal view grade.

• Journal of Gastric Cancer
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• 제21권3호
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• pp.268-278
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• 2021

Purpose: While several prognostic models for the stratification of death risk have been developed for patients with advanced gastric cancer receiving first-line chemotherapy, they have seldom been tested in the Chinese population. This study investigated the performance of these models and identified the optimal tools for Chinese patients. Materials and Methods: Patients diagnosed with metastatic or recurrent gastric adenocarcinoma who received first-line chemotherapy were eligible for inclusion in the validation cohort. Their clinical data and survival outcomes were retrieved and documented. Time-dependent receiver operating characteristic (ROC) and calibration curves were used to evaluate the predictive ability of the models. Kaplan-Meier curves were plotted for patients in different risk groups divided by 7 published stratification tools. Log-rank tests with pairwise comparisons were used to compare survival differences. Results: The analysis included a total of 346 patients with metastatic or recurrent disease. The median overall survival time was 11.9 months. The patients were different into different risk groups according to the prognostic stratification models, which showed variability in distinguishing mortality risk in these patients. The model proposed by Kim et al. showed relative higher predicting abilities compared to the other models, with the highest χ² (25.8) value in log-rank tests across subgroups, and areas under the curve values at 6, 12, and 24 months of 0.65 (95% confidence interval [CI]: 0.59-0.72), 0.60 (0.54-0.65), and 0.63 (0.56-0.69), respectively. Conclusions: Among existing prognostic tools, the models constructed by Kim et al., which incorporated performance status score, neutrophil-to-lymphocyte ratio, alkaline phosphatase, albumin, and tumor differentiation, were more effective in stratifying Chinese patients with gastric cancer receiving first-line chemotherapy.

• 한국시뮬레이션학회논문지
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• 제32권4호
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• pp.19-26
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• 2023

전국 대학생의 중도 탈락 비율의 증가는 학생 개인 뿐만 아니라 대학과 사회에 심각한 부정적 영향을 끼친다. 본 연구에서는 중도 탈락이 예상되는 학생을 사전에 식별하기 위하여, 각 대학의 학사관리 시스템에서 손쉽게 얻을 수 있는 학적 데이터를 기반으로 머신러닝 분야의 결정트리, 랜덤 포레스트, 로지스틱 회귀 및 딥러닝 기반의 중도 탈락 예측 모델을 구축하고, 그 성능을 비교·분석하였다. 분석 결과 로지스틱 회귀 기반 예측 모델의 재현율이 가장 높았으나 f-1 및 auc 값이 낮은 한계를 보였고, 랜덤 포레스트 기반의 예측 모델의 경우 재현율을 제외한 다른 모든 지표에서 가장 우수한 성능을 보였다. 또한 예측 기간에 따른 예측 모델의 성능을 확인하기 위하여 예측 기간을 단기(1개 학기 이내), 중기(2개 학기 이내) 및 장기(3개 학기 이내)로 나누어 분석해 본 결과, 장기 예측 시 가장 높은 예측력을 보였다. 본 연구를 통해 각 대학은 중도 탈락이 예상되는 학생들을 조기에 식별하고, 이들에 대한 집중 관리를 통해 중도 탈락 비율을 줄이며 나아가 대학 재정 안정화에 기여할 수 있을 것으로 기대된다.