Short-term effects of cannabis consumption on cognitive performance in medical cannabis patients.

This observational study examined the acute cognitive effects of cannabis. We hypothesized that cognitive performance would be negatively affected by acute cannabis intoxication. Twenty-two medical cannabis patients from Southwestern Ontario completed the study. The majority (n = 13) were male. Mean age was 36.0 years, and mean level of education was 13.7 years. Participants were administered the same brief neurocognitive battery three times during a six-hour period: at baseline ("Baseline"), once after they consumed a 20% THC cannabis product ("THC"), and once again several hours later ("Recovery"). The average self-reported level of cannabis intoxication prior to the second assessment (i.e., during THC) was 5.1 out of 10. Contrary to expectations, performance on neuropsychological tests remained stable or even improved during the acute intoxication stage (THC; d: .49-.65, medium effect), and continued to increase during Recovery (d: .45-.77, medium-large effect). Interestingly, the failure rate on performance validity indicators increased during THC. Contrary to our hypothesis, there was no psychometric evidence for a decline in cognitive ability following THC intoxication. There are several possible explanations for this finding but, in the absence of a control group, no definitive conclusion can be reached at this time.

Differentiating epilepsy from psychogenic nonepileptic seizures using neuropsychological test data.

OBJECTIVE: Differentiating epileptic seizures (ES) from psychogenic nonepileptic seizures (PNES) represents a challenging differential diagnosis with important treatment implications. This study was designed to explore the utility of neuropsychological test scores in differentiating ES from PNES. METHOD: Psychometric data from 72 patients with ES and 33 patients with PNES were compared on various tests of cognitive ability and performance validity. Individual measures that best discriminated the diagnoses were then entered as predictors in a logistic regression equation with group membership (ES vs. PNES) as the criterion. RESULTS: On most tests of cognitive ability, the PNES sample outperformed the ES sample (medium-large effect) and was less likely to fail the Reliable Digit Span. However, patients with PNES failed two embedded validity indicators at significantly higher rates (risk ratios (RR): 2.45-4.16). There were no group differences on the Test of Memory Malingering (TOMM). A logistic regression equation based on seven neuropsychological tests correctly classified 85.1% of patients. The cutoff with perfect specificity was associated with 0.47 sensitivity. CONCLUSIONS: Consistent with previous research, the utility of psychometric methods of differential diagnosis is limited by the complex neurocognitive profiles associated with ES and PNES. Although individual measures might help differentiate ES from PNES, multivariate assessment models have superior discriminant power. The strongest psychometric evidence for PNES appears to be a consistent lack of impairment on tests sensitive to diffuse neurocognitive deficits such as processing speed, working memory, and verbal fluency. While video-electroencephalogram (EEG) monitoring is the gold standard of differential diagnosis, psychometric testing has the potential to enhance clinical decision-making, particularly in complex or unclear cases such as patients with nondiagnostic video-EEGs. Adopting a standardized, fixed neuropsychological battery at epilepsy centers would advance research on the differential diagnostic power of psychometric testing.