Independent Criterion Research Articles

Examining Traditional and Novel Validity Indicators from the Medical Symptom Validity Test Across Levels of Verbal and Visual Memory Impairment.

This cross-sectional study examined accuracy of traditional Medical Symptom Validity Test (MSVT) validity indicators, including immediate recognition (IR), delayed recognition (DR), and consistency (CNS), as well as a novel indicator derived from the mean performance on IR, DR, and CNS across verbal, visual, and combined learning and memory impairment bands. A sample of 180 adult outpatients was divided into valid (n = 150) and invalid (n = 30) groups based on results of four independent criterion performance validity tests. Verbal and visual learning and recall were classified as indicative of no impairment, mild impairment, or severe impairment based on performance on the Rey Auditory Verbal Learning Test and Brief Visuospatial Memory Test-Revised, respectively. In general, individual MSVT subtests were able to accurately classify performance as valid or invalid, even in the context of severe learning and memory deficits. However, as verbal and visual memory impairment increased, optimal MSVT cut-scores diverged from manual-specified cutoffs such that DR and CNS required cut-scores to be lowered to maintain adequate specificity. By contrast, the newly proposed scoring algorithm generally showed more robust psychometric properties across the memory impairment bands. The mean performance index, a novel scoring algorithm using the mean of the three primary MSVT subtests, may be a more robust validity indicator than the individual MSVT subtests in the context of bona fide memory impairment.

Optimal sensor placement for uncertain inverse problem of structural parameter estimation

This paper presents an optimal sensor placement approach for the uncertain inverse problem of structural parameter estimation, aiming to mitigate the ill-posedness problem that often exists in inverse procedures. The key idea is to select the sensor positions with the most sensitive measured responses to the structural parameters and the least correlated measured responses at the selected positions. Our optimization strategy is to convert the traditional minimum variance criterion of structural parameters to be identified into a new maximum independent mean-variance criterion of structural responses, so that the complex optimal sensor placement problem is transformed into a forward uncertainty propagation problem. Then, two orthogonal matching pursuit (OMP) methods based on Monte Carlo simulation (MCS) and dimension reduction integration (DRI) method are presented in this work, in which the MCS and the much more efficient DRI method are employed to solve the forward uncertainty propagation problem, and the OMP methods in sample form and moment form are developed to determine the optimal sensor placement for the identification procedure by considering the uncertainties in the measured responses. A Markov Chain Monte Carlo algorithm is adopted to identify the distributions of structural parameters eventually. Numerical and experimental examples are presented to verify the practicability and effectiveness of the proposed methods.

All of the accuracy in half of the time: Assessing abbreviated versions of the Test of Memory Malingering in the context of verbal and visual memory impairment

Objective The Test of Memory Malingering (TOMM) Trial 1 (T1) and errors on the first 10 items of T1 (T1-e10) were developed as briefer versions of the TOMM to minimize evaluation time and burden, although the effect of genuine memory impairment on these indices is not well established. This study examined whether increasing material-specific verbal and visual memory impairment affected T1 and T1-e10 performance and accuracy for detecting invalidity. Method: Data from 155 neuropsychiatric patients administered the TOMM, Rey Auditory Verbal Learning Test (RAVLT), and Brief Visuospatial Memory Test-Revised (BVMT-R) during outpatient evaluation were examined. Valid (N = 125) and invalid (N = 30) groups were established by four independent criterion performance validity tests. Verbal/visual memory impairment was classified as ≥37 T (normal memory); 30 T-36T (mild impairment); and ≤29 T (severe impairment). Results: Overall, T1 had outstanding accuracy, with 77% sensitivity/90% specificity. T1-e10 was less accurate but had excellent discriminability, with 60% sensitivity/87% specificity. T1 maintained excellent accuracy regardless of memory impairment severity, with 77% sensitivity/≥88% specificity and a relatively invariant cut-score even among those with severe verbal/visual memory impairment. T1-e10 had excellent classification accuracy among those with normal memory and mild impairment, but accuracy and sensitivity dropped with severe impairment and the optimal cut-score had to be increased to maintain adequate specificity. Conclusion: TOMM T1 is an effective performance validity test with strong psychometric properties regardless of material-specificity and severity of memory impairment. By contrast, T1-e10 functions relatively well in the context of mild memory impairment but has reduced discriminability with severe memory impairment.

Brief executive-function assessment tool: A new cognitive impairment screening tool for alcohol and other drug services

Accurate screening for cognitive impairment in alcohol and other drug (AOD) services would help to identify individuals who may need supports to obtain the greatest benefit from substance use disorder (SUD) treatment. At present there is no screening measure that has been developed specifically to detect cognitive impairment in a SUD population. This study examines the psychometric properties of the Brief Executive-function Assessment Tool (BEAT), which was specifically designed for this purpose. This study involving 501 individuals with SUD and 145 normal control participants established internal consistency (n = 646; 0.734), interrater (n = 60; 0.994), and test–retest reliability (n = 177; 0.845), and construct (all correlations p ≤ 0.05), and criterion (n = 467; ANCOVA p < 0.001) validity. Test operating characteristics (n = 500; 87% sensitivity, 71% specificity, 21% PPP, and 99% NPP) were also established relative to an independent criterion variable made up of three established performance-based neuropsychological tests. Findings support the reliability and validity of the BEAT as a screening measure of executive function impairment with high sensitivity and a low rate of false negatives.

How will I know about local energy projects? A conjoint-analysis of communication preferences in Germany

In an interconnected world like ours, boundaries between nations and between political, economic, and ecological challenges fade away. Within renewable energy and infrastructure projects, fields of tension evolve between global goals and local worries, and often protest arises. Communication strategies can be a way to involve citizens in project development and to build a dialogue instead of hardened fronts. However, it is unclear whether communication requirements and willingness to protest are connected and to which extent communication strategies help to create and shape a dialogue between potential protesters and other stakeholders. A conjoint approach was chosen to determine relationships between communication and protest motivation in the energy context. We compare this with mobility infrastructure and local political projects as examples, to find out whether results are unique or generalizable.Overall, we found generalizable aspects, that are the same for the energy and the example contexts. Point in time, informing person and participation were relevant decision criteria, whereas information channel was the least important independent communication criterion for all contexts. Two essential decision patterns were identified focusing either on source or on time of information. These patterns were influenced by diverse individual factors, e.g. age and protest experience.

Prevalence and comorbidity of borderline personality traits in the Quebec general population aged 12-14years.

The early identification of borderline personality traits (BPT) in adolescents helps to prevent their progression. Data are available for the clinical population, but little has been published on the general population, especially regarding age and sex distribution in adolescence. Even less is known about the comorbidity of BPT with other mental disorders. We estimated the prevalence of BPT, by sex, age, and comorbidity, in a sample of adolescents aged 12-14years (n = 799) from the Quebec Mental Health Survey. A complex sampling design was used to ensure representativeness. BPT was assessed with the abbreviated-diagnostic interview for borderlines-revised, with the adolescent as an informant. Reliability coefficients were above 0.80. Several levels of severity were explored using an independent criterion, defined by impairment according to the Columbia impairment scale. The overall prevalence of BPT was 6.3%. Prevalence estimates for the most impaired were 3.2% for the entire sample and 1.3% for 12-year-olds. Prevalence increased significantly with age for most impairment levels but did not differ significantly between the sexes. In adolescents, BPT displayed moderate-to-strong comorbidity with anxiety (AD) and insomnia disorders, and very strong comorbidity with depressive (DD), attention deficit hyperactivity (ADHD), and oppositional defiant/conduct disorders (ODD/CD). We, therefore, make two clinical recommendations for child psychiatry practice: (1) with respect to the lower rate of male adolescents attending BPT Health Programs, increase BPT screening in male adolescents; (2) evaluate BPT when children with ADHD or ODD/CD develop AD or DD during adolescence.

Every second counts: A comparison of four dot counting test scoring procedures for detecting invalid neuropsychological test performance.

Although performance validity tests (PVTs) are an integral element of neuropsychological assessment, most PVTs have historically been restricted to the memory domain. The Dot Counting Test (DCT) is a nonmemory PVT shown to reliably identify invalid performance. Although several traditional and abbreviated scoring methods have been derived, no study to date has directly compared the available scoring approaches within a single sample. This cross-sectional study cross-validated 4 different DCT scoring approaches, including the traditional rounded E-score proposed within the manual, an unrounded E-score, and 2 abbreviated scoring procedures based on 4- and 6-card versions (DCT-4 and DCT-6, respectively) in a diverse mixed clinical neuropsychiatric sample (N = 132). Validity groups were established by 5 independent criterion PVTs (102 valid and 30 invalid). Receiver operating characteristic curve analyses yielded significant areas under the curve (AUCs = .84-.86) for the overall sample, with sensitivities of 50%-67% at ≥ 89% specificity. The DCT scores had outstanding classification accuracy (AUCs ≥ .92; sensitivities = 80%-83%) in the unimpaired group and excellent classification accuracy in the impaired group (AUCs = .79-.81; sensitivities = 43%-60%). Whereas negligible differences emerged between the 4 scoring methods for the cognitively intact group, the DCT-4 showed notably stronger psychometric properties among the overall sample in general and the mild cognitive impairment group in particular. Results corroborate previous findings suggesting that the DCT is a robust PVT, regardless of the employed scoring procedure, and replicate support for the abbreviated DCT-4 as the recommended validity indicator. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Mean response latency indices on the Victoria Symptom Validity Test do not contribute meaningful predictive value over accuracy scores for detecting invalid performance

The utility of the Victoria Symptom Validity Test (VSVT) as a performance validity test (PVT) has been primarily established using response accuracy scores. However, the degree to which response latency may contribute to accurate classification of performance invalidity over and above accuracy scores remains understudied. Therefore, this study investigated whether combining VSVT accuracy and response latency scores would increase predictive utility beyond use of accuracy scores alone. Data from a mixed clinical sample of 163 patients, who were administered the VSVT as part of a larger neuropsychological battery, were analyzed. At least four independent criterion PVTs were used to establish validity groups (121 valid/42 invalid). Logistic regression models examining each difficulty level revealed that all VSVT measures were useful in classifying validity groups, both independently and when combined. Individual predictor classification accuracy ranged from 77.9 to 81.6%, indicating acceptable to excellent discriminability across the validity indices. The results of this study support the value of both accuracy and latency scores on the VSVT to identify performance invalidity, although the accuracy scores had superior classification statistics compared to response latency, and mean latency indices provided no unique benefit for classification accuracy beyond dimensional accuracy scores alone.

Block Cipher Nonlinear Confusion Components Based on New 5-D Hyperchaotic System

The security strengths of block ciphers greatly rely on the confusion components which have the tendency to transform the data nonlinearly into the perplexed form. This paper proposes to put forward a novel scheme of generating cryptographically strong nonlinear confusion components of block ciphers, usually termed as substitution-boxes (S-boxes). The anticipated S-box design scheme is based on a novel five-dimensional (5-D) chaotic system analyzed in this paper. The proposed 5-D dynamical system consists of hyperchaotic phenomenon, KY dimension, conservativity, unstable equilibrium point, and complex phase attractors which are suited for cryptographic applications. The S-box based on hyperchaotic system is made to evolve in order to generate an optimized S-box for high nonlinearity score to make it robust against many linear attacks. The performance analysis of proposed S-box demonstrates that it has bijectivity, high nonlinearity; satisfied strict avalanche criterion and bits independent criterion; low differential and linear probabilities. Moreover, performance appraisal of proposed S-box justifies its better strength and features over many recently investigated S-boxes.

An Improved Method of the Finite-Difference Sparse Phase Unwrapping

Phase unwrapping (PU) is a significant problem for reconstructing the deformation field during synthetic aperture radar interferometry analysis. The various 2-D PU algorithms can be divided into two categories: path-following methods and optimization-based methods. The former predefine an integration path in which the phase gradient is integrated to obtain the unwrapped results. The latter are path independent and error criterion oriented. The integration of the finite differences and the minimum cost flow solver describes a global optimization problem between the phase residues over closed spatial triangles computed over redundant neighboring edge sets. We propose a modified network using a simplified mathematical formulation for linear programming (LP) in the finite differences PU. Our algorithm has three major advantages over current methods. First, the modified network combines the Delaunay triangulation and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">K</i> nearest points to avoid isolated regions in the PU process. Second, modified formulation of the LP solver can directly obtain the phase ambiguity cycles of all points without integration. Finally, the combination of the new network and modified LP can achieve better PU results than the other state-of-the-art techniques. We applied our method to synthetic and real data from January 24, 2020 Mw 6.7 earthquake in Doğanyol–Sivrice, Turkey to August 8, 2017 Mw 6.5 earthquake in Jiuzhaigou, China. Comprehensive comparisons validate the effectiveness of our method.

Feature Selection Methods Based on Symmetric Uncertainty Coefficients and Independent Classification Information

Feature selection is a critical step in the data preprocessing phase in the field of pattern recognition and machine learning. The core of feature selection is to analyze and quantify the relevance, irrelevance, and redundancy between features and class labels. While existing feature selection methods give multiple explanations for these relationships, they ignore the multi-value bias of class-independent features and the redundancy of class dependent features. Therefore, a feature selection method (Maximal independent classification information and minimal redundancy, MICIMR) is proposed in this paper. Firstly, the relevance and redundancy terms of class independent characteristics are calculated respectively based on the symmetric uncertainty coefficient. Secondly, it calculates the relevance and redundancy terms of class-dependent features according to the independent classification information criterion. Finally, the selection criteria for these two characteristics are combined. To verify the effectiveness of the MICIMR algorithm, five feature selection methods are compared with the MICIMR algorithm on fifteen real datasets. The experimental results demonstrate that the MICIMR algorithm outperforms the other feature selection algorithms in terms of redundancy rate as well as classification accuracy (Gmean_macro and F1_macro).

Fuzzy Mathematics Comprehensive Forecasting Analysis of Metal Mine Rockburst Based on Multiple Criteriahere

The underground environment in deep mines is complicated and the risk of rockburst is high during excavation. Therefore, it is of great significance to study the tendency of rockburst during excavation. At present, scholars from various countries have analyzed rockburst phenomena from the aspects of strength, stiffness, energy, etc., and have proposed various assumptions and criteria. However, these assumptions and criteria often only consider individual factors, which will lead to one-sidedness and limitations. This article takes the deep mining process of a metal mine as the research background. Based on the results of each independent criterion, fuzzy mathematical theory is introduced to evaluate the rockburst intensity and fuzzy comprehensiveness of various types of rocks in the project. The research results show that the multi-criteria comprehensive evaluation of fuzzy mathematics can well integrate the analysis results of each criterion, and has higher consistency with the actual situation in engineering.

Glucose variability in pregnant women with newly diagnosed hyperglycemia

Background: High-performance parallel next-generation sequencing (NGS) allows for identification of various maturity-onset diabetes of the young (MODY) subtypes also during pregnancy. As this method is expensive and time-consuming, it has proposed to use various predictors for the diagnosis of mutation in the hexokinase (GCK)/MODY2 gene, helping to select the patients for subsequent molecular genetic testing. Hyperglycemia due to MODY2 is commonly newly diagnosed during pregnancy; therefore, there is a search for factors specific to this mutation in pregnant women.Aim: To evaluate blood glucose variability in pregnant women with newly diagnosed hyperglycemia at early gestation and to determine the threshold value of the glycemic variability coefficient for pregnant women with a mutation in the GCK/MODY2 gene.Materials and methods: This observational single center study included 41 pregnant women with newly diagnosed early hyperglycemia (not meeting the criteria for manifest diabetes mellitus). Molecular genetic testing was performed in all of them. According to its results, they were retrospectively categorized into two groups: with early gestational diabetes mellitus (GDM, no mutations) and with hyperglycemia related to a mutation in the GCK/MODY2 gene. A comparative analysis of glycemic variability in the two groups was performed. Sensitivity and specificity of the cutoff value for the coefficient of variability as a diagnostic marker of MODY2 were also calculated.Results: The pregnant women with GDM had significantly higher age and body mass index (BMI) than those with MODY2 (p&lt;0.05). There were significant differences in venous fasting plasma glucose and glycated hemoglobin, with these parameters being higher in the pregnant women with MODY2 (p&lt;0.05). In the patients with a mutation in the GCK gene, hyperglycemia was diagnosed earlier and insulin therapy was started earlier during pregnancy than in those with GDM (p&lt;0.05). The ROC analysis of the diagnostic accuracy of the variability coefficient showed that at the threshold CV (coefficient of variation) value of 20.8, the area under the curve was 0.742 (95% confidence intervals 0.597 to 0.888; p&lt;0.005), with the sensitivity of 65% and the specificity of 65.4%.Conclusion: The calculated sensitivity of 65% and specificity of 65.4% for the CV of 20.8 do not allow for its use as an independent selection criterion for subsequent confirmation of MODY2. However, its combination with the A.J. Chakera criteria (BMI&lt;25 kg/m2 and fasting glucose≥5.5 mmol with 68% sensitivity and 96% specificity) allows to clarify the category of pregnant women with newly detected early hyperglycemia, to whom the search for mutations in the GCK gene should be recommended.

A Known-Groups Validation of the Medical Symptom Validity Test and Analysis of the Genuine Memory Impairment Profile.

This study cross-validated the Medical Symptom Validity Test (MSVT) in a mixed neuropsychiatric sample and examined its accuracy for identifying invalid neuropsychological performance using a known-groups design. Cross-sectional data from 129 clinical patients who completed the MSVT were examined. Validity groups were established using six, independent criterion performance validity tests, which yielded 98 patients in the valid group and 31 in the invalid group. All MSVT subtest scores were significantly lower in the invalid group (ηp2=.22-.39). Using published cut-scores, sensitivities of 42% to 71% were found among the primary effort subtests, and 74% sensitivity/90% specificity was observed for the overall MSVT. Among this sample, the MSVT component validity scales produced areas under the curve of .78-.86, suggesting moderate classification accuracy. At optimal cut-scores, the MSVT primary effort validity scales demonstrated 55% to 71% sensitivity/91% to 93% specificity, with the Consistency subtest exhibiting the strongest psychometric properties. The MSVT exhibited relatively robust sensitivity and specificity, supporting its utility as a briefer freestanding performance validity test to its predecessor, the Word Memory Test. Finally, the Genuine Memory Impairment Profile appears promising for patients with Major Neurocognitive Disorder, but is cautioned against for those without significant functional decline in activities of daily living at this time.

Improved 2D Discrete Hyperchaos Mapping with Complex Behaviour and Algebraic Structure for Strong S-Boxes Generation

This paper proposes to present a novel method of generating cryptographic dynamic substitution-boxes, which makes use of the combined effect of discrete hyperchaos mapping and algebraic group theory. Firstly, an improved 2D hyperchaotic map is proposed, which consists of better dynamical behaviour in terms of large Lyapunov exponents, excellent bifurcation, phase attractor, high entropy, and unpredictability. Secondly, a hyperchaotic key-dependent substitution-box generation process is designed, which is based on the bijectivity-preserving effect of multiplication with permutation matrix to obtain satisfactory configuration of substitution-box matrix over the enormously large problem space of 256!. Lastly, the security strength of obtained S-box is further elevated through the action of proposed algebraic group structure. The standard set of performance parameters such as nonlinearity, strict avalanche criterion, bits independent criterion, differential uniformity, and linear approximation probability is quantified to assess the security and robustness of proposed S-box. The simulation and comparison results demonstrate the effectiveness of proposed method for the construction of cryptographically sound S-boxes.

Predictive value of premature atrial complex characteristics in pulmonary vein isolation for patients with paroxysmal atrial fibrillation

Premature atrial complexes from pulmonary veins are the main triggers for atrial fibrillation in the early stages. Thus, pulmonary vein isolation is the cornerstone of catheter ablation for paroxysmal atrial fibrillation. However, the success rate remains perfectible. To assess whether premature atrial complex characteristics before catheter ablation can predict pulmonary vein isolation success in paroxysmal atrial fibrillation. We investigated consecutive patients who underwent catheter ablation for paroxysmal atrial fibrillation from January 2013 to April 2017 in two French centres. Patients were included if they were treated with pulmonary vein isolation alone, and had 24-hour Holter electrocardiogram data before catheter ablation available and a follow-up of≥6 months. Catheter ablation success was defined as freedom from any sustained atrial arrhythmia recurrence after a 3-month blanking period following catheter ablation. One hundred and three patients were included; all had an acute successful pulmonary vein isolation procedure, and 34 (33%) had atrial arrhythmia recurrences during a mean follow-up of 30±15 months (group 1). Patients in group 1 presented a longer history of atrial fibrillation (71.9±65.8 vs. 42.9±48.4 months; P=0.008) compared with those who were "free from arrhythmia" (group 2). Importantly, the daily number of premature atrial complexes before catheter ablation was significantly lower in group 1 (498±1413 vs. 1493±3366 in group 2; P=0.028). A daily premature atrial complex cut-off number of<670 predicted recurrences after pulmonary vein isolation (41.1% vs. 13.3%; sensitivity 88.2%; specificity 37.7%; area under the curve 0.635; P=0.017), and was the only independent predictive criterion in the multivariable analysis (4-fold increased risk). Preprocedural premature atrial complex analysis on 24-hour Holter electrocardiogram in paroxysmal atrial fibrillation may improve patient selection for pulmonary vein isolation.

Purulent-septic complications of acute necrotizing pancreatitis: prognosis of development and early diagnosis

Aim. To determine frequency and causes of purulent-septic complications of acute necrotizing pancreatitis, to elaborate and introduce into clinical practice prognostic and early diagnostic criteria for infection of pathological foci in the pancreas.Material and methods. Prospective cohort study of 70 patients with severe acute necrotizing pancreatitis was performed in one intensive care department during the years 2015-2019. Clinical, bacteriological and instrumental examinations were carried out. Serum concentration of sCD14 receptors and presepsin were determined.Results. Overall mortality rate reached 18.8 %, but it was twice as high in patients with purulent-septic complications (P &lt; 0.05). Primary infection of pancreatic necrotic tissues was diagnosed in 21 (55.7 %) patients. Secondary infection of pathological foci was identified in 22 (57.9 %) patients who had been operated before the 4th week and in 6 (18.6 %) – at latter periods of the disease onset. It was found that the serum content of sCD14 receptors above 1670 ng/ml at admission had been served as an independent prognostic criterion for the development of purulent-septic complications (sensitivity – 87 %, specificity – 81 %). The level of presepsin was three-four times higher in the patients with infectious complications than that in the individuals with sterile pancreatic necrosis (P &lt; 0.01). The study showed strong correlation between presepsin concentration and infectious complications: presepsin level increased to 677 ± 30 pg/ml in patients with local purulent processes, to 988 ± 47 pg/ml – with sepsis, and to 2668 ± 583 pg/ml – with septic shock. Presepsin was the biomarker with high performance for all types of infected complications in acute necrotizing pancreatitis (ROC AUC 0.956 ± 0.007 (Р &lt; 0.0001)).Conclusions. High level of sCD14 at admission is associated with the development of infected acute necrotizing pancreatitis. Presepsin concentration is early and highly sensitive and specific marker of purulent-septic complications in acute pancreatitis.

The Effect of the Primitive Irreducible Polynomial on the Quality of Cryptographic Properties of Block Ciphers

Substitution boxes are the only nonlinear component of the symmetric key cryptography and play a key role in the cryptosystem. In block ciphers, the S-boxes create confusion and add valuable strength. The majority of the substitution boxes algorithms focus on bijective Boolean functions and primitive irreducible polynomial that generates the Galois field. For binary field F2, there are exactly 16 primitive irreducible polynomials of degree 8 and it prompts us to construct 16 Galois field extensions of order 256. Conventionally, construction of affine power affine S-box is based on Galois field of order 256, depending on a single degree 8 primitive irreducible polynomial over ℤ2. In this manuscript, we study affine power affine S-boxes for all the 16 distinct degree 8 primitive irreducible polynomials over ℤ2 to propose 16 different 8×8 substitution boxes. To perform this idea, we introduce 16 affine power affine transformations and, for fixed parameters, we obtained 16 distinct S-boxes. Here, we thoroughly study S-boxes with all possible primitive irreducible polynomials and their algebraic properties. All of these boxes are evaluated with the help of nonlinearity test, strict avalanche criterion, bit independent criterion, and linear and differential approximation probability analyses to measure the algebraic and statistical strength of the proposed substitution boxes. Majority logic criterion results indicate that the proposed substitution boxes are well suited for the techniques of secure communication.

MRI predictors for brain invasion in meningiomas.

In the 2016 revision of the World Health Organization classification of central nervous system tumours, brain invasion was added as an independent histological criterion for the diagnosis of a World Health Organization grade II atypical meningioma. The aim of this study was to assess whether magnetic resonance imaging characteristics can predict brain invasion for meningiomas. We conducted a retrospective review of all meningiomas resected at our institution between 2005 and 2016 which had preoperative magnetic resonance imaging and included brain tissue within the pathology specimen. One hundred meningiomas were included in the study, 60 of which had histopathological brain invasion, 40 of which did not. Magnetic resonance imaging characteristics of tumours were evaluated for potential predictors of brain invasion. Tumour location, size, perilesional oedema, contour, cerebrospinal fluid cleft, peritumoral cyst, dural venous sinus invasion, bone invasion, hyperostosis and the presence of enlarged pial arteries and veins were evaluated. Data were analysed using conventional chi-square, Fisher's exact test and logistic regression. The volume of peritumoral oedema was significantly higher in the brain-invasive meningioma group compared to the non-brain-invasive group. The presence of a complete cleft was a rare finding that was only found in non-brain-invasive meningiomas. The presence of enlarged pial feeding arteries was a rare finding that was only found in brain-invasive meningiomas. An increased volume of perilesional oedema is associated with the likelihood of brain invasion for meningiomas.

A-210 Does Rounding Matter? Cross-Validation of E-Score Calculation Method for the Dot Counting Test

Abstract Objective Recent evidence suggested the traditional “rounding” procedure used to calculate Dot Counting Test (DCT) E-score cut-offs provides little advantage and may inadvertently lower test sensitivity. This study examined whether DCT psychometric properties differ when E-score values are rounded. Method This cross-sectional study included 132 mixed neuropsychiatric patients who completed the DCT during outpatient evaluation. The sample was 55% female/45% male and 36% Caucasian/35% African American/20% Hispanic/7% Asian/2% other, with mean age of 44.4 (SD=16.1), and mean education of 14.0 years (SD=2.5). In total, 105 (80%) had valid neuropsychological test performance and 27 (20%) had invalid performance based on 4 independent criterion performance validity tests. Results In the overall sample, receiver operating characteristic (ROC) curve analyses yielded significant areas under the curve (.802-.817) for both rounded and unrounded E-score values with respective optimal cut-scores of ≥19 and ≥19.73, both producing 44% sensitivity/93% specificity. Among cognitively impaired patients, ROC curve analyses yielded significant AUCs (.756-.764), and suggested the same cut-scores and sensitivities, albeit with minimally reduced specificity (traditional: 91%; unrounded: 92%). In contrast, more liberal cut-scores of ≥13 (traditional) and ≥13.745 (unrounded) were indicated among cognitively unimpaired patients (AUCs: .880-.906), and sensitivity was notably improved (traditional: 74%; unrounded: 67%) with equivalent specificity (90%). Conclusions Findings from the overall sample suggested marginally better classification accuracy for the traditional E-score, though both methods demonstrated comparable psychometric properties. The optimal cut-score for cognitively unimpaired patients replicated findings from prior literature, but a higher cut-score was indicated for cognitively impaired patients.