• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.26 no.4
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• pp.213-223
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• 2023

Purpose: Pediatric patients in low-income countries are at a high risk of malnutrition. Numerous screening tools have been developed to detect the risk of malnutrition, including the Subjective Global Nutritional Assessment (SGNA), Pediatric Yorkhill Malnutrition Score (PYMS), Screening Tool for the Assessment of Malnutrition in Pediatrics (STAMP), and Screening Tool for Risk of Nutritional Status and Growth (STRONGkids). However, anthropometry remains the main tool for assessing malnutrition. We aimed to identify the value of four nutritional screening tools versus anthropometry for evaluating the nutritional status of children. Methods: We conducted a cross-sectional study of 1,000 children aged 1-12 years who visited the outpatient clinic of Cairo University Pediatric Hospital. Each participant was evaluated using anthropometric measurements (weight, length/height, and weight for length/height) as well as the PYMS, STAMP, STRONGkids, and SGNA screening tools. The sensitivities and specificities of these four tools were assessed using anthropometry as the gold standard. Results: Of the patients, 1.7% were underweight, 10.2% were wasted, and 35% were stunted. STRONGkids demonstrated the highest sensitivity (79.4%) and a high specificity (80.2%) for detecting malnutrition compared with weight for height, followed by STAMP, which demonstrated lower sensitivity (73.5%) but higher specificity (81.4%). PYMS demonstrated the lowest sensitivity (66.7%) and the highest specificity (93.5%), whereas SAGA demonstrated higher sensitivity (77.5%) and lower specificity (85.4%) than PYMS. Conclusion: The use of nutritional screening tools to evaluate the nutritional status of children is valuable and recommended as a simple and rapid method for identifying the risk of malnutrition in pediatric patients.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.13
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• pp.5245-5247
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• 2014

Background: Helicobacter pylori (H.pylori) is one of the most important causes of dyspepsia and gastric cancer and diagnosis can be made by invasive or non-invasive methods. The Atlas Helicobacter pylori antigen test is a new rapid non-invasive method which is simple to conduct. The aim of this study was to determine its sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy. Materials and Methods: This prospective study was conducted between July 2012 and December 2013. Stool samples of 59 dyspeptic patients who underwent upper endoscopy were evaluated for H. pylori stool antigen. Results: From the 59 patients who participated in this study, there were 36 (61%) males and 23 (39%) females. H. pylori was diagnosed in 24 (40.7%) gastric biopsies, 22 (91.7 %) of these being positive for the Atlas H. pylori antigen test. The sensitivity, specificity, PPV, NPV and accuracy were 91.7%, 100%, 100%, 94.6% and 96.6% respectively. Conclusions: The Atlas H. pylori antigen test is a new non-invasive method which is simple to perform and avails reliable results in a few minutes. Thus it can be the best option for the diagnosis of H. pylori infection due to its high sensitivity and specificity.

• Clinical and Experimental Emergency Medicine
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• v.5 no.4
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• pp.264-271
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• 2018

Objective For patients with acute myocardial infarction (AMI), symptoms assessed by emergency medical services (EMS) providers have a critical role in prehospital treatment decisions. The purpose of this study was to evaluate the diagnostic accuracy of EMS provider-assessed cardiac symptoms of AMI. Methods Patients transported by EMS to 4 study hospitals from 2008 to 2012 were included. Using EMS and administrative emergency department databases, patients were stratified according to the presence of EMS-assessed cardiac symptoms and emergency department diagnosis of AMI. Cardiac symptoms were defined as chest pain, dyspnea, palpitations, and syncope. Disproportionate stratified sampling was used, and medical records of sampled patients were reviewed to identify an actual diagnosis of AMI. Using inverse probability weighting, verification bias-corrected diagnostic performance was estimated. Results Overall, 92,353 patients were enrolled in the study. Of these, 13,971 (15.1%) complained of cardiac symptoms to EMS providers. A total of 775 patients were sampled for hospital record review. The sensitivity, specificity, positive predictive value, and negative predictive value of EMS provider-assessed cardiac symptoms for the final diagnosis of AMI was 73.3% (95% confidence interval [CI], 70.8 to 75.7), 85.3% (95% CI, 85.3 to 85.4), 3.9% (95% CI, 3.6 to 4.2), and 99.7% (95% CI, 99.7 to 99.8), respectively. Conclusion We found that EMS provider-assessed cardiac symptoms had moderate sensitivity and high specificity for diagnosis of AMI. EMS policymakers can use these data to evaluate the pertinence of specific prehospital treatment of AMI.

• Biomedical Science Letters
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• v.17 no.4
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• pp.355-361
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• 2011

We evaluated the performance of the NOW $Streptococcus$ $pneumoniae$ urinary antigen test, standard culture and polymerase chain reaction for detecting $S.$ $pneumoniae$. The urinary antigen test of pneumonia patients represented sensitivity at 72% and specificity at 79%. The results of PCR were targeting for autolysin ($lyt$A), pneumolysin ($ply$), and spn9828. The $lyt$A sensitivity and specificity stood at 56% and 87% respectively while $ply$ sensitivity reported 83% and specificity was 47%, sensitivity and specificity of spn9828 stood at 83% and 73% respectively. The results of urinary antigen test and three genes were all statistically meaningful within $P$ <0.05. When the urinary antigen test of $S.$ $pneumoniae$ was positive, the three kinds of genes were also likely to be positive. According to the result of urinary antigen test, the results of PCR presented a meaningful difference ($P$ <0.05). Especially, the urinary antigen test of $S.$ $pneumoniae$ was likely to be positive ($P$ <0.05) when more than two genes were positive in PCR results.

• The Journal of Korean Physical Therapy
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• v.19 no.3
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• pp.41-46
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• 2007

Purpose: This study was to investigate how dose the radiography findings are to magnetic resonance (MR) image findings in the L5-S1 instability patients. The subjects of this study were comprised of eleven males and fifteen females, who had Lumbago and agreed with this research. Methods: Radiography and MR images of Lumbar spine were acquired respectively from subjects in conditions of maximum flexion and extension. The horizontal and angular displacements in lumabosacral spine radiography were used to assess the instability of lumbar spine. MR images were also used to evaluate the intervertebral disc abnormalities and change of bone marrow. Results: The results are as follows. 1. In the case of flexion transitional displacement proposed by Dupuis et al, the specificity and negative predictive value were good accuracy ($0.7{\sim}0.8$), and the negative predictive value was in average. In the case of extension displacement, the negative predictive value was about average ($0.6{\sim}0.7$), but the sensitivity, specificity and positive predictive value were below the poor (<0.6). On the other side, the specificity was about average but other things were below in the case of angular displacement. 2. In the case of flexion transitional displacement proposed by Dupuis et al., compared with the intervertebral disc abnormalities, the negative prediction value was excellent, the sensitivity good, and the specificity about average. In the case of extension, the negative prediction value was about average, but the other things were poor. On the other side the specificity and negative predictive value had good accuracy and the sensitivity and positive prediction value were below average in the case of angular displacement. Conclusion: The above results show that the radiography finding is sufficiently helpful to find the lumbar spine instability as an economic point of view.

• Biomedical Science Letters
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• v.25 no.1
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• pp.99-106
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• 2019

Amyloid positron emission tomography (PET) allows early and accurate diagnosis in suspected cases of Alzheimer's disease (AD) and contributes to future treatment plans. In the present study, a method of implementing a diagnostic system to distinguish ${\beta}$-Amyloid ($A{\beta}$) positive from $A{\beta}$ negative with objectiveness and accuracy was proposed using a machine learning approach, such as the Principal Component Analysis (PCA) and Support Vector Machine (SVM). $^{18}F$-Florbetaben (FBB) brain PET images were arranged in control and patients (total n = 176) with mild cognitive impairment and AD. An SVM was used to classify the slices of registered PET image using PET template, and a system was created to diagnose patients comprehensively from the output of the trained model. To compare the per-slice classification, the PCA-SVM model observing the whole brain (WB) region showed the highest performance (accuracy 92.38, specificity 92.87, sensitivity 92.87), followed by SVM with gray matter masking (GMM) (accuracy 92.22, specificity 92.13, sensitivity 92.28) for $A{\beta}$ positivity. To compare according to per-subject classification, the PCA-SVM with WB also showed the highest performance (accuracy 89.21, specificity 71.67, sensitivity 98.28), followed by PCA-SVM with GMM (accuracy 85.80, specificity 61.67, sensitivity 98.28) for $A{\beta}$ positivity. When comparing the area under curve (AUC), PCA-SVM with WB was the highest for per-slice classifiers (0.992), and the models except for SVM with WM were highest for the per-subject classifier (1.000). We can classify $^{18}F$-Florbetaben amyloid brain PET image for $A{\beta}$ positivity using PCA-SVM model, with no additional effects on GMM.

• Journal of Korean Neurosurgical Society
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• v.64 no.3
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• pp.418-426
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• 2021

Objective : A role of diffusion-weighted imaging (DWI) in the diagnosis of cerebral venous thrombosis (CVT) is not well-understood. This study evaluates the effectiveness of DWI in the diagnosis of CVT. Methods : Literature search was conducted in electronic databases for the identification of studies which reported the outcomes of patients subjected to DWI for CVT diagnosis. Random-effects meta-analyses were performed to achieve overall estimates of important diagnostic efficiency indices including hyperintense signal rate, the sensitivity and specificity of DWI in diagnosing CVT, and the apparent diffusion coefficient (ADC) of DWI signal areas and surrounding tissue. Results : Nineteen studies (443 patients with 856 CVTs; age 40 years [95% confidence interval (CI), 33 to 43]; 28% males [95% CI, 18 to 38]; symptom onset to DWI time 4.6 days [95% CI, 2.3 to 6.9]) were included. Hyperintense signals on DWI were detected in 40% (95% CI, 26 to 55) of the cases. The sensitivity of DWI for detecting CVT was 22% (95% CI, 11 to 34) but specificity was 98% (95% CI, 95 to 100). ADC values were quite heterogenous in DWI signal areas. However, generally the ADC values were lower in DWI signal areas than in surrounding normal areas (mean difference-0.33×10-3 ㎟/s [95% CI, -0.44 to -0.23]; p<0.00001). Conclusion : DWI has a low sensitivity in detecting CVT and thus has a high risk of missing many CVT cases. However, because of its high specificity, it may have supporting and exploratory roles in CVT diagnosis.

• Proceedings of the KOR-BRONCHOESO Conference
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• 1993.05a
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• pp.103-103
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• 1993

Fine needle aspiration biopsy(FNAB) is widely used in screening of head and neck(H&N) masses because it has high accuracy and few damage. The 235 cases of FNAB were performed on patient with H&N mass at the Department of Otolaryngology, Hanyang University Hospital during 1 years, from March 1985 to February 1992. The 188 of 235 were proven histologically, clinically. The results obtained were as follows ; 1) FNAB for malignant H&N mass shows sensitivity of 81.5% specificity of 96.8%. 2) FNAB for malignant LN shows sensitivity of 86.0%, specificity of 88.9%. 3) FNAB for salivary gland shows sensitivity of 66.7%, specificity 81.8%. 4) FNAB for soft tissues, bone, and intraoral lesions shows sensitivity of 90%, specificity 95.8%. 5) FNAB for tuberculosis shows false negative of 55.2%. 6) The result of FNAB was not closely related with location or size of neck nodes.

• Journal of Community Nutrition
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• v.2 no.2
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• pp.129-134
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• 2000

The purpose of the present study is to evaluate the validity of the BMI as an indicator of obesity for Koreans. The usefulness of the BMI to represent overweight and obesity was evaluated by measuring the relative validity of sensitivity and specificity, and was compared with the validity of triceps skinfold thickness(mm). To measure the relative validity of the BMI and triceps skinfold thickness, body fat(%) was used as a reference measure of obesity. The study population included 844 participants aged 20-69 years who resided in Kuri City in Kyunggi province. Participants were measured regarding weight, height, triceps skinfold thickness and body fat. The prevalence of obesity for male subjects was 32.0%, 66.2%, and 0.9%, and for female subjects, 17.6%, 56.1%, 12.4% based on the BMI, triceps skinfold thickness, and body fat(%) respectively. The prevalence of obesity was higher based on the BMI or triceps skinfold thickness than body fat measurement. The sensitivity and specificity of the BMI were 33.3% and 67.9% in male subjects and 77.7% and 90.8% in female subjects. Sensitivity of the BMI was lower, and specificity was higher than those of triceps skinfold thickness. In summary, BMI as an indicator of obesity for Korean showed a tendency of overestimation of obesity prevalence. Therefore, there is a need to develop a more reliable obesity index other than the BMI for Koreans.

• Journal of radiological science and technology
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• v.43 no.6
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• pp.461-467
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• 2020

In the field of nuclear medicine, errors are sometimes generated because the assessment of the uniformity of gamma cameras relies on the naked eye of the evaluator. To minimize these errors, we created an artificial intelligence model based on CNN algorithm and wanted to assess its usefulness. We produced 20,000 normal images and partial cold region images using Python, and conducted artificial intelligence training with Resnet18 models. The training results showed that accuracy, specificity and sensitivity were 95.01%, 92.30%, and 97.73%, respectively. According to the results of the evaluation of the confusion matrix of artificial intelligence and expert groups, artificial intelligence was accuracy, specificity and sensitivity of 94.00%, 91.50%, and 96.80%, respectively, and expert groups was accuracy, specificity and sensitivity of 69.00%, 64.00%, and 74.00%, respectively. The results showed that artificial intelligence was better than expert groups. In addition, by checking together with the radiological technologist and AI, errors that may occur during the quality control process can be reduced, providing a better examination environment for patients, providing convenience to radiologists, and improving work efficiency.