• Journal of Korean Neurosurgical Society
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• v.65 no.5
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• pp.751-757
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• 2022

Objective : Tumours of the brain are a rare occurrence accounting for approximately 2% of all neoplasms in adults. Few studies have been done in Nigeria on the profile of brain tumours. The aim of this study is to determine the profile of brain tumours in general and determine the change in Kanofsky Performance Score (KPS) after treatment. Methods : This is a prospective hospital-based study in Kaduna. All consecutive patients over 18 years of age with diagnosis of brain tumours from January 2016 to December 2019 were included in the study. Demographic and clinical data was collected using a proforma during the study. Patients who received treatment were followed up for 12 months. The primary outcome data was the difference in the quality of life as measured by KPS at the point of first contact and at 1-month after treatment and at 12-month follow up. Data obtained was analysed with SPSS version 25.0 for Windows. Descriptive statistics was done to determine the profile. Paired t-test at 95% confidence interval was done to check for significant correlation between the mean KPS. Results : A total of 39 consecutive patients were included in the study. There was a slight male preponderance with a M : F of 1.17 : 1. Meningioma and metastasis were more common in females while gliomas and pituitary tumours were more common in males. The mean age of patients was 49.8 years and standard deviation of 11.8 years. Pituitary tumours were the most common tumours. The most common location of the tumour was frontal lobe followed by the pituitary gland. The mean duration of symptoms before neurosurgical consultation was 38 weeks. The most common presenting symptoms of patient with brain tumour was headache. The quality of life improve compare to the baseline in 81% of patient at discharge and at 1 year follow up. The overall mortality rate was 25.6%. Conclusion : The most common brain tumour in our study is pituitary tumour. Most patients present late. The most common presenting symptoms is headache. There is significant improvement in the KPS of patients following treatment. The overall mortality rate at 1-year post treatment is 25.6%.

• The Korean Journal of Nuclear Medicine
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• v.23 no.2
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• pp.175-181
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• 1989

Visual assessment of regional wall motion abnormality (RWMA) by gated blood pol scan (GBPS) serves as an useful parameter in the diagnosis, functional evaluation, and follow up in various clinical settings, but are still subject to some inherent limitations. On important problem may be the interobserver as well as intraobsever variation that may well be present due to the subjective nature of the interpretations. This study was carried out to determine the reliability and reproducibility of visual assessments made in GBPSs, and to observe the degree to which the results would be influenced by observer variation. Fifty two patients with coronary heart disease had resting GBPS and contrast ventriculography within 4 days appall. Contrast ventriculography-showed normal wall motion in 6 patients and the remaining 46 had RWMA in one or more segments. The anterior and left anterolateral views of all 52 GBPSs were analyzed by three independent observers, who selected from 5 scales, their level of confidence that there was RWMA in that segment. Reciever operating characteristic (ROC) curves for each analysis was plotted and the area under the curve $(\theta)$ was used as a parameter representing each observer's performance in his interpretations. The findings of contrast ventriculographies were used as the standard for RWMA. The apical and inferoapical segments showed the best correlation with contrast ventriculography ($\theta=0.90-0.94$, 0.81-0.94, respectively), and the inferior wall showed the poorest correlation $(\theta=0.70-0.74)$. The interpretations of the inferior, septal, apical, and posteroinferior, segments showed no difference between the observers, but there was significantly better performance in assessment by observer A compared to that by B or C for the anterolateral segments ($\theta=0.87$, 0.78, 0.76, respectively. p<0.01 for A vs B, p<0.05 for A vs C), as well as when all segments were considered altogether ($\theta=0.88$, 0.83, 0.82, respectively. both p<0.05). This was also true for the infero-apical segment between A and C ($\theta=0.09$, 0.81, p<0.05). The intraobserver variation, however, did not appear significant, with only the inferior segment for observer B showing any significant difference when observer A and B repeated the analysis 10 days latter. There was no difference in assessing dyskinesia, with all observers showing a high performance ($\theta=0.98$, 0.87, 0.97, respectively). The visual assessment of left ventricular ejection fraction by all three observers correlated well with the calculated value from a semiautomated method (Spearman's r = 0.91, 0.83, 0.83. p<0.01, p<0.05, p < 0.05). The assessment of LV and RV size also correlated well between the three observers (Kendall's w = 0.80, 0.51, p<0.01 for both left and right ventricles). The above findings suggest that RWMA visually assessed by GBPS correlates well with that done by contrast ventriculography. And although the observer's experience or skill may influence the results in certain segments, visual analysis of GBPS may serve as a reliable and reproducible means for evaluating ventricular function.

• Korean Journal of Radiology
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• v.24 no.5
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• pp.395-405
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• 2023

Objective: This study aimed to develop and validate models using radiomics features on a native T1 map from cardiac magnetic resonance (CMR) to predict left ventricular reverse remodeling (LVRR) in patients with nonischemic dilated cardiomyopathy (NIDCM). Materials and Methods: Data from 274 patients with NIDCM who underwent CMR imaging with T1 mapping at Severance Hospital between April 2012 and December 2018 were retrospectively reviewed. Radiomic features were extracted from the native T1 maps. LVRR was determined using echocardiography performed ≥ 180 days after the CMR. The radiomics score was generated using the least absolute shrinkage and selection operator logistic regression models. Clinical, clinical + late gadolinium enhancement (LGE), clinical + radiomics, and clinical + LGE + radiomics models were built using a logistic regression method to predict LVRR. For internal validation of the result, bootstrap validation with 1000 resampling iterations was performed, and the optimism-corrected area under the receiver operating characteristic curve (AUC) with 95% confidence interval (CI) was computed. Model performance was compared using AUC with the DeLong test and bootstrap. Results: Among 274 patients, 123 (44.9%) were classified as LVRR-positive and 151 (55.1%) as LVRR-negative. The optimism-corrected AUC of the radiomics model in internal validation with bootstrapping was 0.753 (95% CI, 0.698-0.813). The clinical + radiomics model revealed a higher optimism-corrected AUC than that of the clinical + LGE model (0.794 vs. 0.716; difference, 0.078 [99% CI, 0.003-0.151]). The clinical + LGE + radiomics model significantly improved the prediction of LVRR compared with the clinical + LGE model (optimism-corrected AUC of 0.811 vs. 0.716; difference, 0.095 [99% CI, 0.022-0.139]). Conclusion: The radiomic characteristics extracted from a non-enhanced T1 map may improve the prediction of LVRR and offer added value over traditional LGE in patients with NIDCM. Additional external validation research is required.

• Journal of Korean Academy of Nursing
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• v.29 no.5
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• pp.1087-1102
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• 1999

Diabetes mellitus, a universal and prevalent chronic disease, is projected to be one of the most formidable worldwide health problems in the 21st century. For those living with diabetes, there is a need for self-care skills to manage a complex medical regimen. Self-efficacy which refers to one's belief in his/her capability to monitor and perform the daily activities required to manage diabetes has be found to be related to self-care. The concept of self-efficacy comes from social cognitive theory which maintains that cognitive mechanism mediate the performance of behavior. The literature cites several research studies which show a strong relationship between self-efficacy and self-care behavior. Meta-analysis is a technique that enables systematic review and quantitative integration of the results from multiple primary studies that are relevant to a particular research question. Therefore, this study was done using meta-analysis to quantitatively integrate the results of independent research studies to obtain numerical estimates of the overall effect of a self-efficacy with diabetic patient on self-care behaviors. The research proceeded in three stages : 1) literature search and retrieval of studies in which self-efficacy was related to self-care, 2) coding, and 3) calculation of mean effect size and data analysis. Seventeen studies which met the research criteria included study population of adults with diabetes, measures of self-care and measures of self-efficacy as a predictive variable. Computation of effect size was done on DSTAT which is a statistical computer program specifically designed for meta-analysis. To determine the effect of self-efficacy on self-care practice homogeneity tests were conducted. Pooled effect size estimates, to determine the best subvariable for composite variables, metabolic control variables and component of self-efficacy and self-care, indicated that the effect of self-efficacy composite on self-care composite was moderate to large. The weighted mean effect size of self-efficacy composite and self-care composite were ＋.76 and the confidence interval was from ＋.66 to ＋.86 with the number of subjects being 1,545. The total for this meta-analysis result showed that the weighted mean effect sizes ranged from ＋.70 to ＋1.81 which indicates a large effect. But since reliabilities of the instruments in the primary studies were low or not stated, caution must be applied in unconditionally accepting the results from these effect sizes. Meta-analysis is a useful took for clarifying the status of knowledge development and guiding decision making about future research and this study confirmed that there is a relationship between self-efficacy and self-care in patients with diabetes. It, thus, provides support for nurses to promote self-efficacy in their patients. While most of the studies included in this meta-analysis used social cognitive theory as a framework for the study, some studies use Fishbein & Ajzen's attitude model as a model for active self-care. Future research is needed to more fully define the concept of self-care and to determine what it is that makes patients feel competent in their self-care activities. The results of this study showed that self-efficacy can promote self-care. Future research is needed with experimental design to determine nursing interventions that will increase self-efficacy.

• Journal of Pharmaceutical Investigation
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• v.31 no.1
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• pp.49-55
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• 2001

Acetyl-L-carnitine (ALC), an endogenous component of the L-carnitine family, is naturally occurring molecule synthesized from L-carnitine (LC) by carnitine acetyl transferase. ALC has been shown to improve the cognitive performance of patients suffering from dementia of the Alzheimer's type and proposed for treating Alzheimer's disease in pharmacological doses. The purpose of the present study was to evaluate the bioequivalence of two ALC tablets, $Nicetile^{TM}$ (Dong-A pharmaceutical Co., Ltd.) and $Neurocetil^{TM}$ (Kyung-Dong Pharmaceutical Co., Ltd.), according to the guidelines of Korea Food and Drug Administration. Twenty six normal male volunteers, $22.80{\pm}2.76$ year in age and $63.07{\pm}7.98\;kg$ in body weight, were divided into two groups and a randomized $2{\times}2$ cross-over study was employed. After one tablet containing 500 mg of ALC was orally administered, blood was taken at predetermined time intervals and the concentrations of ALC in serum were determined using HPLC with fluorescence detector. Because of the presence of endogenous ALC, the calibration was performed using dialyzed serum. Pharmacokinetic parameters such as $AUC_t$, $C_{max}\;and\;T_{max}$ were calculated and ANOVA was utilized for the statistical analysis of the parameters. The results showed that the differences in $AUC_t$, $C_{max}\;and\;T_{max}$ between two tablets were 2.72%, -0.65% and -8.42%, respectively, when calculated against the $Nicetile^{TM}$ tablet. The powers $(1-{\beta})$ for $AUC_t\;and\;C_{max}$ were 94.87% and 87.17%, respectively. Minimum detectable differences $({\Delta})$ at ${\alpha}=0.05$ and $1-{\beta}=0.8$ were less than 20% (e.g., 15.58% and 19.16% $AUC_t\;C_{max}$, respectively). The 90% confidence intervals were within ${\pm}20%$ (e.g., $-11.84{\sim}6.41$ and $-10.57{\sim}11.88$for $AUC_t\;and\;C_{max}$, respectively). Two parameters met the criteria of KFDA for bioequivalence, indicating that $Neurocetil^{TM}$ tablet is bioequivalent to $Nicetile^{TM}$ tablet.

• Journal of Korean Home Economics Education Association
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• v.19 no.1 s.43
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• pp.15-33
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• 2007

The purpose of this study is to find the effect of improvement in student's learning attitude when applying portfolio, which is one of the ways for the performance's assessment suggested as an alternative of traditional assessment for the instruction of Home Economics subject. The results of this study were as follows; 1. We have developed the Portfolio materials; teaching and learning plans, the paper of activities of the class, materials of the instructions, and assessment materials from the instruction of total 13 times in the unit of 'making short pants'. 2. The instruction,'Making short pants' with applying portfolio, is very effective in terms of changing student's learning attitude positively - pride, self-confidence, interest, conscience of purpose, motivation for achievement, focus surroundings, self-study, friendship among classmate and etc. 3. The result of analyzing students 'thoughts shows that the majority over 90% of the students showed the positive attitude toward applied portfolio instruction. Here are the reasons that 'it's helpful to study', 'it can be focused better on the instruction', 'it give them satisfaction and couidence' and 'it can be increased abilities studying by oneself'. on the other hand, the negative side of the instruction applied portfolio is that it requires too much time to prepare portfolio materials. there is pressure because of a lot of assignments to do. Based on this result, we are expecting to increase student's interest in the middle school class of Technology and Home Economic and also to achieve development of the method of teaching and learning to enhance student's learning attitude.

• The Journal of Advanced Prosthodontics
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• v.5 no.4
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• pp.452-456
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• 2013

PURPOSE. The aim of this study was to evaluate the repeatability of the digitizing of silicon rubber impressions of abutment teeth by using a white light scanner and compare differences in repeatability between different abutment teeth types. MATERIALS AND METHODS. Silicon rubber impressions of a canine, premolar, and molar tooth were each digitized 8 times using a white light scanner, and 3D surface models were created using the point clouds. The size of any discrepancy between each model and the corresponding reference tooth were measured, and the distribution of these values was analyzed by an inspection software (PowerInspect 2012, Delcamplc., Birmingham, UK). Absolute values of discrepancies were analyzed by the Kruskal-Wallis test and multiple comparisons (${\alpha}$=.05). RESULTS. The discrepancy between the impressions for the canine, premolar, and molar teeth were $6.3{\mu}m$ (95% confidence interval [CI], 5.4-7.2), $6.4{\mu}m$ (95% CI, 5.3-7.6), and $8.9{\mu}m$ (95% CI, 8.2-9.5), respectively. The discrepancy of the molar tooth impression was significantly higher than that of other tooth types. The largest variation (as mean [SD]) in discrepancies was seen in the premolar tooth impression scans: $26.7{\mu}m$ (95% CI, 19.7-33.8); followed by canine and molar teeth impressions, $16.3{\mu}m$ (95% CI, 15.3- 17.3), and $14.0{\mu}m$ (95% CI, 12.3-15.7), respectively. CONCLUSION. The repeatability of the digitizing abutment teeth's silicon rubber impressions by using a white light scanner was improved compared to that with a laser scanner, showing only a low mean discrepancy between $6.3{\mu}m$ and $8.9{\mu}m$, which was in an clinically acceptable range. Premolar impression with a long and narrow shape showed a significantly larger discrepancy than canine and molar impressions. Further work is needed to increase the digitizing performance of the white light scanner for deep and slender impressions.

• Journal of The Korean Association For Science Education
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• v.42 no.2
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• pp.201-214
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• 2022

The purpose of this study is to examine the characteristics of model of the experiment in students' open inquiry. The research is a reinterpretation of the data collected from the performance of a three-year research project under the theme of 'school science inquiry' the perspective of model of the experiment. The inquiry activities of a focus group made up of four students have been recorded seven times. The recorded files and transcribed copies were analyzed according to interpretive methods. Students' activities were divided into three modeling of the experiment units, considering the modeling unit that includes the process of starting from the problem until it gets solved. The results of the study include illuminating the dynamic process and characteristics of modeling of the experiment and discussing its educational meaning as a distributed cognitive system at each modeling unit. First, students, instruments, and the primitive form of calculation represented by the interaction between them turned out to be important factors in the distributed cognitive system that constitutes model of the experiment. Second, in the early stages, non-verbal activities were carried out in which students became familiar with instruments, and verbal quantitative signs were created when the activities were sufficiently carried out. The generated quantitative signs became a source of data and confidence that can be referenced in subsequent activities. Third, the specialization of instrumentalization occurred, and factors that were important in inquiry, such as variable control, appeared. The results of the study provide new implications for science education research and education, which have been centered on explanatory models, by unfolding the characteristics of model of the experiment that have not been noticed in science education through students' inquiry.

• Korean Journal of Radiology
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• v.22 no.6
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• pp.994-1004
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• 2021

Objective: To extract pulmonary and cardiovascular metrics from chest CTs of patients with coronavirus disease 2019 (COVID-19) using a fully automated deep learning-based approach and assess their potential to predict patient management. Materials and Methods: All initial chest CTs of patients who tested positive for severe acute respiratory syndrome coronavirus 2 at our emergency department between March 25 and April 25, 2020, were identified (n = 120). Three patient management groups were defined: group 1 (outpatient), group 2 (general ward), and group 3 (intensive care unit [ICU]). Multiple pulmonary and cardiovascular metrics were extracted from the chest CT images using deep learning. Additionally, six laboratory findings indicating inflammation and cellular damage were considered. Differences in CT metrics, laboratory findings, and demographics between the patient management groups were assessed. The potential of these parameters to predict patients' needs for intensive care (yes/no) was analyzed using logistic regression and receiver operating characteristic curves. Internal and external validity were assessed using 109 independent chest CT scans. Results: While demographic parameters alone (sex and age) were not sufficient to predict ICU management status, both CT metrics alone (including both pulmonary and cardiovascular metrics; area under the curve [AUC] = 0.88; 95% confidence interval [CI] = 0.79-0.97) and laboratory findings alone (C-reactive protein, lactate dehydrogenase, white blood cell count, and albumin; AUC = 0.86; 95% CI = 0.77-0.94) were good classifiers. Excellent performance was achieved by a combination of demographic parameters, CT metrics, and laboratory findings (AUC = 0.91; 95% CI = 0.85-0.98). Application of a model that combined both pulmonary CT metrics and demographic parameters on a dataset from another hospital indicated its external validity (AUC = 0.77; 95% CI = 0.66-0.88). Conclusion: Chest CT of patients with COVID-19 contains valuable information that can be accessed using automated image analysis. These metrics are useful for the prediction of patient management.

• Korean Journal of Radiology
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• v.23 no.3
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• pp.343-354
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• 2022

Objective: To develop and evaluate a deep learning-based artificial intelligence (AI) model for detecting skull fractures on plain radiographs in children. Materials and Methods: This retrospective multi-center study consisted of a development dataset acquired from two hospitals (n = 149 and 264) and an external test set (n = 95) from a third hospital. Datasets included children with head trauma who underwent both skull radiography and cranial computed tomography (CT). The development dataset was split into training, tuning, and internal test sets in a ratio of 7:1:2. The reference standard for skull fracture was cranial CT. Two radiology residents, a pediatric radiologist, and two emergency physicians participated in a two-session observer study on an external test set with and without AI assistance. We obtained the area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity along with their 95% confidence intervals (CIs). Results: The AI model showed an AUROC of 0.922 (95% CI, 0.842-0.969) in the internal test set and 0.870 (95% CI, 0.785-0.930) in the external test set. The model had a sensitivity of 81.1% (95% CI, 64.8%-92.0%) and specificity of 91.3% (95% CI, 79.2%-97.6%) for the internal test set and 78.9% (95% CI, 54.4%-93.9%) and 88.2% (95% CI, 78.7%-94.4%), respectively, for the external test set. With the model's assistance, significant AUROC improvement was observed in radiology residents (pooled results) and emergency physicians (pooled results) with the difference from reading without AI assistance of 0.094 (95% CI, 0.020-0.168; p = 0.012) and 0.069 (95% CI, 0.002-0.136; p = 0.043), respectively, but not in the pediatric radiologist with the difference of 0.008 (95% CI, -0.074-0.090; p = 0.850). Conclusion: A deep learning-based AI model improved the performance of inexperienced radiologists and emergency physicians in diagnosing pediatric skull fractures on plain radiographs.