Role of Ultrasonography and Conventional Radiography in the Detection of Maxillofacial Fractures: A Comparative Study

Objective: With the collaboration of the trauma department, our study was designed to compare the effectiveness of ultrasonography (USG) and conventional radiography in the detection of bony fractures related to oral and maxillofacial regions. Methodology: This comparative study was conducted from March 2020 to March 2021 by the Radiology department of Sarghoda medical college hospital with the collaboration of the trauma department. Ultrasonography was performed by using GE- USG machine along with a linear extraoral transducer (frequency range 7-15 MHZ). Patients were asked to sit in a seated position facing the sinologist. Transducers were placed over the site by applying the sterile gel. Results: The overall sensitivity and specificity rate of ultrasonography was reported as 83.33% and 98.88% respectively in all sites whereas the sensitivity and specificity rate of conventional radiographs were reported as 70.24%, 100%. The negative predictive value of USG was reported as 96.17% along with 94.59% positive predictive value. In the contrast, conventional radiography gave a better positive predictive value (100%) than USG In our study we found better results of ultrasonography in terms of sensitivity and negative predictive value. Conclusion: In conclusion, our study depicts that ultrasonography is an economical, useful diagnostic tool for examining the bony fractures of facial trauma with a better sensitivity rate when compared to conventional radiographs.

Measuring Utility of VASS Elder Mistreatment Screener Within Community Dwelling U.S. Chinese Older Adults

Elder mistreatment (EM) is often underreported, making potential screening a valuable tool. There is limited literature on the screening utility, especially for minority populations. This abstract aims to study sensitivity and specificity of a commonly used 10-point EM screener compared to a detailed EM questionnaire among Chinese older adults. This study used data from a representative sample of 3,157 community-dwelling U.S. Chinese older adults 60+. Chi-squared test was conducted between VASS 10-questionare screener and EM measured by 56 items on psychological, physical and sexual mistreatment, caregiver neglect and financial exploitation subtypes. Sensitivity and specificity was calculated using the Bayes Theorem. In this sample, average age was 72 and 59% female. 637 (20.30%) reported any EM while 475 (15.14%) older adults screened positive for EM. Of participants reporting any EM, 365 (57.30%) did not screen positive for EM. The screener had a sensitivity of 42.70% and specificity of 91.88% for all EM subtypes. Gaps between reported EM and negative EM screener is smaller in psychological (sensitivity 72.85%, specificity 91.07%) and physical (sensitivity 63.64%, specificity 86.66%) EM subtypes, but much larger in financial exploitation (sensitivity 34.60%, specificity 86.85%) and neglect (sensitivity 14.11%, specificity 84.75%). The VASS screener demonstrates poor sensitivity but acceptable specificity rate for any EM. The screener showed better sensitivity and specificity for physical and psychological mistreatment, but performed worse for more common forms of mistreatment like financial exploitation and neglect. Modifying this screener may improve sensitivity and specificity in identifying EM.

The Accuracy of Molecular Detection Targeting the Mutation C2611T for Detecting Moderate-Level Azithromycin Resistance in Neisseria gonorrhoeae: A Systematic Review and Meta-Analysis

Background: Neisseria gonorrhoeae (N. gonorrhoeae) is now recognized as a commonly reported sexually transmitted pathogen, and the increasing drug resistance of N. gonorrhoeae has become a serious public health problem. The accuracy of molecular detection for detecting moderate-level azithromycin resistance is not well-established. We summarized the data from studies of the N. gonorrhoeae 23S rRNA mutation at position 2611 with azithromycin resistance to determine the relationship between the mutation and resistance. Methods and Findings: In this systematic review and meta-analysis, two researchers independently searched six databases for studies with data for the azithromycin minimum inhibitory concentrations (MICs) and the 23S rRNA mutation C2611T of each N. gonorrhoeae isolate. Since the breakpoint of moderate-level resistance to azithromycin (ML-AzmR) was not determined, we divided the moderate level into two groups according to the range of MICs (moderate resistance limited to 2–128 mg/L or 4–128 mg/L) for data extraction. A random-effects model was used to calculate the pooled sensitivity rate, the specificity rate, the pooled positive likelihood ratio (PLR), the negative likelihood ratio (NLR), and the diagnostic odds ratio (DOR). Meta-regression analyses by detection method, isolates sampling (a random sample or not), location, and sample size were performed to explore the possible causes of heterogeneity. The potential publication bias of the included studies was conducted by the Deeks’ test. We included 20 studies in our study: 20 studies have data of N. gonorrhoeae with MICs between 2 and 128 mg/L with mutation or without mutation at position 2611(4759 samples), and 14 studies have data of N. gonorrhoeae with MICs between 4 and 128 mg/L (3367 samples). In the group with the moderate level of 2–128 mg/L, the pooled sensitivity rate of the molecular assays was determined to be 71.9% (95% CI, 67.6–74%), the pooled specificity rate was 98.7% (95% CI, 98.2–99.0%), and the DOR ranged from 55.0 to 351.3 (mean, 139.1). In the 4–128 mg/L group, the pooled sensitivity rate was 91.9% (95% CI, 88.9–94.2%), the pooled specificity rate was 95.9% (95% CI, 95.1–96.6%), and the DOR ranged from 41.9 to 364.1 (mean, 123.6). Conclusion: Through this meta-analysis, we found that the C2611T mutation of 23S rRNA is valuable for the molecular diagnostic of moderate-level azithromycin resistance (ML-AzmR) in N. gonorrhoeae, especially when the moderate level is set at 4–128 mg/L. This rapid molecular detection method can be used for the rapid identification of ML-AzmR isolates in the clinic.

Study of Bagging Application in the Safe-Level Smote Method in Handling Unbalanced Classification

The problems of imbalanced class classification have been found in many real applications. It has potential to make the minority class instances tend to be classified into the majority class. This study examined the performance of bagging method’s application in safe-level SMOTE based on Support Vector Machine classifier. The data used consisted of three types based on the proportion of observations in the majority and minority classes. Each type of data has three variables, two independent variables and one variable dependent. The observations of independent variables were generated based on multivariate normal distribution, while dependent variables are binary. The results showed that the classifier has a high accuracy and sensitivity for all types of data for both in the imbalanced class and the balanced class (obtained by safe-level SMOTE and safe-level SMOTEBagging). Nevertheless, specificity was the main measure in assessing the performance of the classifier because it provides accuracy in classifying the minority class observations. The specificity increased when the number of observations between the two classes were approximately balance due to the implementation of safe-level SMOTE. The best performance of the Support Vector Machine in predicting minority class observations was achieved when bagging were applied in safe-level SMOTE. The specificity rate for all types of data were 77.93 percent, 78.46 percent, and 85.69 percent, respectively.

A-204 Cross-Validation of the Dot Counting Test in a Nonclinical Sample

Objective Studies have indicated that nonclinical participants in neuropsychological research do not always perform validly on testing (e.g., An, Zakzanis, & Joordens, 2012). As such, we cross-validated a brief yet well-researched performance validity test, the Dot Counting Test (DCT), in a validly performing nonclinical sample. Method Participants were 50 college students (mean age = 19.92; mean education = 14.10) who completed a neuropsychological test battery under the instruction to provide their best effort on all tests. Freestanding performance validity tests included the Test of Memory Malingering (TOMM) and DCT. To ensure that only valid participants were included in the study, it was required that participants pass all examined TOMM validity indices (i.e., Trial 1, Trial 2, Retention, Albany Consistency Index, and Invalid Forgetting Frequency Index; no participant failed any of these indices). Results The first DCT E-score cutoff at which 90% specificity was obtained was > 13. At a cutoff of > 17 (a previously established clinical group cutoff), 98% specificity was obtained. At a cutoff of > 21, 100% specificity was obtained. Conclusions Results cross-validate the DCT for use in a nonclinical sample. Multiple cutoffs are reported, along with corresponding specificity rates. Researchers can now choose the cutoff, which corresponds to their desired specificity rate, to use in nonclinical research studies to help ensure that invalidly performing participants are excluded from future research.

An Improved Image Segmentation System

In this paper, we present a solution-based cooperation approach for strengthening the image segmentation.This paper proposes a cooperative method relying on Multi-Agent System. The main contribution of this work is to highlight the importance of cooperation between the contour and region growing based on Multi-Agent System (MAS). Consequently, agents’ interactions form the main part of the whole process for image segmentation. Similar works were proposed to evaluate the effectiveness of the proposed solution. The main difference is that our Multi-Agent System can perform the segmentation process ensuring efficiency. Our results show that the performance indices in the system were higher. Furthermore, the integration of the cooperation paradigm allows to speed up the segmentation process. Besides, the tests reveal the robustness of our method by proving competitive results. Our proposal achieved an accuracy of 93,51%± 0,8, a sensitivity of 93,53%± 5,08 and a specificity rate of 92,64%± 4,01.

Boosted trees to predict pneumonia, growth, and meat percentage of growing-finishing pigs1

In pig production, efficiency is benefiting from uniform growth in pens resulting in single deliveries from a pen of possibly all animals in the targeted weight range. Abnormalities, like pneumonia or aberrant growth, reduce production efficiency as it reduces the uniformity and might cause multiple deliveries per batch and pigs delivered with a low meat yield or outside the targeted weight range. Early identification of pigs prone to develop these abnormalities, for example, at the onset of the growing-finishing phase, would help to prevent heterogeneous pens through management interventions. Data about previous production cycles at the farm combined with data from the piglet’s own history may help in identifying these abnormalities. The aim of this study, therefore, was to predict at the onset of the growing-finishing phase, that is, at 3 mo in advance, deviant pigs at slaughter with a machine-learning technique called boosted trees. The dataset used was extracted from the farm management system of a research center. It contained over 70,000 records of individual pigs born between 2004 and 2016, including information on, for example, offspring, litter size, transfer dates between production stages, their respective locations within the barns, and individual live-weights at several production stages. Results obtained on an independent test set showed that at a 90% specificity rate, the sensitivity was 16% for low meat percentage, 20% for pneumonia and 36% for low lifetime growth rate. For low lifetime growth rate, this meant an almost three times increase in positive predictive value compared to the current situation. From these results, it was concluded that routine performance information available at the onset of the growing-finishing phase combined with data about previous production cycles formed a moderate base to identify pigs prone to develop pneumonia (AUC > 0.60) and a good base to identify pigs prone to develop growth aberrations (AUC > 0.70) during the growing-finishing phase. The mentioned information, however, was not a sufficient base to identify pigs prone to develop low meat percentage (AUC < 0.60). The shown ability to identify growth aberrations and pneumonia can be considered a good first step towards the development of an early warning system for pigs in the growing-finishing phase.

NEW ELECTROCARDIOGRAPHIC CRITERIA FOR DIFFERENTIAL DIAGNOSIS OF TACHYCARDIAS WITH ADVANCED QRS COMPLEXES ACCORDING TO THE TYPE OF BLOCKADE OF LEFT BUNDLE OF HIS

Aim. To evaluate standard 12-lead electrocardiogram (ECG) indices for the differential diagnosis of left bundle branch block (LBBB) tachycardias.Material and Methods. The study analyses 244 ECG indices in 63 retrospective patients (85 males and 39 females aged 50±12 years) with LBBB type tachycardias. The electrophysiological study identified ventricular tachycardias (VT) (VT group, n=20), supraventricular tachycardias (SVT) with LBBB (SVT+LBBB group, n=23) or antidromic SVTs (WPW group, n=20). Unifactorial, multifactorial, and ROC analyses were performed to develop diagnostic ECG algorithms. The prognostic accuracy of the algorithms was subsequently evaluated in a prospective group of patients with LBBB tachycardias (n=57).Results. ECG signs of LBBB VTs were as follows: 1) the presence of the initial R wave in the lead aVL; 2) the absence of a split (M-shaped) R wave in the lead I; and 3) the S wave duration in the lead V1≤100 ms. For antidromic LBBB tachycardias, the ECG signs were as follows: 1) the duration of the R waves in the lead V2≥45 ms; 2) the absence of a split R waves (M-shaped) in the lead I; and 3) the duration of the R wave in the lead aVL>30 ms. The accuracy of the algorithm for diagnosis of VT with LBBB was 95% (sensitivity of 97%, specificity of 92%). The accuracy of the algorithm for diagnosis of antidromic tachycardias was 84% (sensitivity rate of 65%, specificity rate of 100%).Conclusion. Our data showed new very powerful criteria for differential diagnosis between various LBBB tachycardias even in comparison with well-known ECG algorithms of Wellens, Brugada, Griffith, Scheinman, Vereckei, Sasaki, et al.

NEW ELECTROCARDIOGRAPHIC CRITERIA FOR DIFFERENTIAL DIAGNOSIS OF TACHYCARDIAS WITH ADVANCED QRS COMPLEXES ACCORDING TO THE TYPE OF BLOCKADE OF LEFT BUNDLE OF HIS

Aim. To evaluate standard 12-lead electrocardiogram (ECG) indices for the differential diagnosis of left bundle branch block (LBBB) tachycardias.Material and Methods. The study analyses 244 ECG indices in 63 retrospective patients (85 males and 39 females aged 50±12 years) with LBBB type tachycardias. The electrophysiological study identified ventricular tachycardias (VT) (VT group, n=20), supraventricular tachycardias (SVT) with LBBB (SVT+LBBB group, n=23) or antidromic SVTs (WPW group, n=20). Unifactorial, multifactorial, and ROC analyses were performed to develop diagnostic ECG algorithms. The prognostic accuracy of the algorithms was subsequently evaluated in a prospective group of patients with LBBB tachycardias (n=57).Results. ECG signs of LBBB VTs were as follows: 1) the presence of the initial R wave in the lead aVL; 2) the absence of a split (M-shaped) R wave in the lead I; and 3) the S wave duration in the lead V1≤100 ms. For antidromic LBBB tachycardias, the ECG signs were as follows: 1) the duration of the R waves in the lead V2≥45 ms; 2) the absence of a split R waves (M-shaped) in the lead I; and 3) the duration of the R wave in the lead aVL>30 ms. The accuracy of the algorithm for diagnosis of VT with LBBB was 95% (sensitivity of 97%, specificity of 92%). The accuracy of the algorithm for diagnosis of antidromic tachycardias was 84% (sensitivity rate of 65%, specificity rate of 100%).Conclusion. Our data showed new very powerful criteria for differential diagnosis between various LBBB tachycardias even in comparison with well-known ECG algorithms of Wellens, Brugada, Griffith, Scheinman, Vereckei, Sasaki, et al.

Evaluation of the Bio-Rad Geenius HIV 1/2 Assay as Part of a Confirmatory HIV Testing Strategy for Quebec, Canada: Comparison with Western Blot and Inno-Lia Assays

ABSTRACT The rapid confirmatory Bio-Rad Geenius HIV 1/2 assay was evaluated as an alternative to the HIV-1 Western blot (WB) confirmatory assay. A total of 370 retrospective samples collected from 356 patients were tested. Sensitivity of the Geenius assay to detect HIV-1 and HIV-2 infections was 100% and 97%, respectively, and that of the WB assay was 86% and 39%, respectively. Geenius reduced the number of indeterminate results by 85% and exhibited a differentiation capacity for HIV-1 and HIV-2 of 100% and 89%, respectively. Three of 10 patients presenting with an early HIV infection (1 to 2 weeks before seroconversion by WB) were positive using Geenius. None of the HIV-negative samples were positive using Geenius or WB. However, 7% and 10% of them were indeterminate with Geenius and WB, respectively, leading to a specificity rate of 93% for Geenius and 90% for WB. Ninety cadaveric samples (54 negative, 23 HIV-1 positive, and 3 HIV-1 indeterminate) were tested with Geenius, leading to a sensitivity of 100%, a specificity of 96%, and an indeterminate rate of 4%. Our results indicate that the Bio-Rad Geenius HIV 1/2 rapid test exhibits better sensitivity to detect HIV-1 infections and better performance than WB to confirm and differentiate between HIV-1 and HIV-2 infections. The performance of this new confirmatory assay to detect early infections, to reduce the rate of indeterminate status, and to confirm HIV-1 infection in cadaveric blood samples makes Geenius a potent reliable alternative to the WB.