Self-awareness and underestimation of cognitive abilities in patients with adult temporal lobe epilepsy after surgical treatment.

INTRODUCTION: Self-awareness of cognitive, emotional, functional, and social performance is critical for compliance with treatment. However, few studies have investigated self-awareness and the associated effects on other cognitive variables in patients with temporal lobe epilepsy (TLE) after surgical treatment. AIM: This study was designed to investigate the prevalence of impaired self-awareness (ISA) in patients with TLE who have undergone surgical treatment. Associated correlations with clinical variables (frequency of seizures before surgery, time elapsed since the epilepsy diagnosis, depression, and anxiety) and verbal and visual episodic memory function and differences between patients with right and left TLE were also investigated. METHOD: Twenty-three adults with TLE after surgical treatment were assessed with the Patient Competency Rating Scale (PCRS-R-BR), the Rey Auditory Verbal Learning Task (RAVLT), and the Modified Ruche Visuospatial Learning Test (RUCHE-M). Patients were considered to have memory dysfunction if delayed recall as assessed with the RUCHE-M or RAVLT was at or below the 25th percentile. Patients were considered to have ISA if PCRS-R-BR discrepancy scores were at or above the 75th percentile. Underestimated cognitive ability (UCA) was defined as a PCRS-R-BR discrepancy percentile score ≤25. Results were analyzed using frequency, Spearman correlation, regression analyses, and the Mann-Whitney test. RESULTS: Frequency analysis of the total sample indicated ISA in 39.13% of patients (n = 9), UCA in 39.13% of patients (n = 9), and impaired verbal and/or visual memory performance in 69.56% of patients (n = 16). Moderate positive correlations were found between the frequency of seizures before surgical treatment and relatives' reports, as well as between the duration of time that had elapsed since the epilepsy diagnosis and patient reports. Negative and moderate correlations were found between the frequency of seizures and the discrepancy score, as well as between depression and patient reports. No differences in PCRS-R-BR were found between patients with right vs. left TLE. No clinical variables significantly predicted self-report or self-awareness. CONCLUSION: Patients with TLE exhibit various patterns of ISA and negative effects on cognitive function after surgical treatment. Emotional factors and relatives' reports must be considered when assessing these patients.

Estimating biological accuracy of DSM for attention deficit/hyperactivity disorder based on multivariate analysis for small samples.

OBJECTIVE: To estimate whether the "Diagnostic and Statistical Manual of Mental Disorders" (DSM) is biologically accurate for the diagnosis of Attention Deficit/ Hyperactivity Disorder (ADHD) using a biological-based classifier built by a special method of multivariate analysis of a large dataset of a small sample (much more variables than subjects), holding neurophysiological, behavioral, and psychological variables. METHODS: Twenty typically developing boys and 19 boys diagnosed with ADHD, aged 10-13 years, were examined using the Attentional Network Test (ANT) with recordings of event-related potentials (ERPs). From 774 variables, a reduced number of latent variables (LVs) were extracted with a clustering of variables method (CLV), for further reclassification of subjects using the k-means method. This approach allowed a multivariate analysis to be applied to a significantly larger number of variables than the number of cases. RESULTS: From datasets including ERPs from the mid-frontal, mid-parietal, right frontal, and central scalp areas, we found 82% of agreement between DSM and biological-based classifications. The kappa index between DSM and behavioral/psychological/neurophysiological data was 0.75, which is regarded as a "substantial level of agreement". DISCUSSION: The CLV is a useful method for multivariate analysis of datasets with much less subjects than variables. In this study, a correlation is found between the biological-based classifier and the DSM outputs for the classification of subjects as either ADHD or not. This result suggests that DSM clinically describes a biological condition, supporting its validity for ADHD diagnostics.