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Objective: Here we report an investigation on the accuracy of the b Test, a measure to identify malingering of cognitive symptoms, in detecting malingerers of mild cognitive impairment. Method: Three groups of participants, patients with Mild Neurocognitive Disorder ( n = 21), healthy elders (controls, n = 21), and healthy elders instructed to simulate mild cognitive disorder (malingerers, n = 21) were administered two background neuropsychological tests (MMSE, FAB) as well as the b Test. Results: Malingerers performed significantly worse on all error scores as compared to patients and controls, and performed poorly than controls, but comparably to patients, on the time score. Patients performed significantly worse than controls on all scores, but both groups showed the same pattern of more omission than commission errors. By contrast, malingerers exhibited the opposite pattern with more commission errors than omission errors. Machine learning models achieve an overall accuracy higher than 90% in distinguishing patients from malingerers on the basis of b Test results alone. Conclusions: Our findings suggest that b Test error scores accurately distinguish patients with Mild Neurocognitive Disorder from malingerers and may complement other validated procedures such as the Medical Symptom Validity Test.

Objective: The aim of this study was to determine which characteristics could better distinguish dementia with Lewy bodies (DLB) from Alzheimer's disease (AD) at the mild cognitive impairment (MCI) stage, with particular emphasis on visual space and object perception abilities., Methods: Fifty-three patients with mild cognitive deficits that were eventually diagnosed with probable DLB (MCI-DLB: n = 25) and AD (MCI-AD: n = 28) at a 3-year follow-up were retrospectively studied. At the first visit, the patients underwent cognitive assessment including the Qualitative Scoring Mini Mental State Examination Pentagon Test and the Visual Object and Space Perception Battery. The Neuropsychiatric Inventory Questionnaire, Unified Parkinson's Disease Rating Scale (UPDRS) and questionnaires for cognitive fluctuations and sleep disorders were also administered., Results: The best clinical predictor of DLB was the presence of soft extrapyramidal signs (mean UPDRS score: 4.04 ± 5.9) detected in 72% of patients, followed by REM sleep behavior disorder (60%) and fluctuations (60%). Wrong performances in the pentagon's number of angles were obtained in 44% of DLB and 3.7% of AD patients and correlated with speed of visual attention. Executive functions, visual attention and visuospatial abilities were worse in DLB, while verbal episodic memory impairment was greater in AD. Deficits in the visual-perceptual domain were present in both MCI-DLB and AD., Conclusions: Poor performance in the pentagon's number of angles is specific of DLB and correlates with speed of visual attention. The dorsal visual stream seems specifically more impaired in MCI-DLB with respect to the ventral visual stream, the latter being involved in both DLB and AD. These cognitive features, associated with subtle extrapyramidal signs, should alert clinicians to a diagnostic hypothesis of DLB.

The aim of this study was to build an instrument, the numerical activities of daily living (NADL), designed to identify the specific impairments in numerical functions that may cause problems in everyday life. These impairments go beyond what can be inferred from the available scales evaluating activities of daily living in general, and are not adequately captured by measures of the general deterioration of cognitive functions as assessed by standard clinical instruments like the MMSE and MoCA. We assessed a control group (n = 148) and a patient group affected by a wide variety of neurological conditions (n = 175), with NADL along with IADL, MMSE, and MoCA. The NADL battery was found to have satisfactory construct validity and reliability, across a wide age range. This enabled us to calculate appropriate criteria for impairment that took into account age and education. It was found that neurological patients tended to overestimate their abilities as compared to the judgment made by their caregivers, assessed with objective tests of numerical abilities.

Adherence to a medical regimen has been defined as the extent to which a patient's behavior coincides with clinical prescriptions. In liver transplant patients, adherence to immunosuppressive therapy and to medical indications in general is crucial for short- and long-term outcomes. Nonadherence to immunosuppression carries a risk of graft rejection and potential graft loss, whereas nonadherence to general medical indications (eg, avoiding alcohol intake and smoking after transplantation) may be associated with other complications such as de novo tumors and increasing health care costs. Among adult liver transplant patients, the rate of nonadherence to immunosuppressive drugs ranges from 15% to 40%, whereas the rate of nonadherence to clinical appointments ranges from 3% to 47%. The wide range of reported rates is due to different definitions of the term nonadherence and the variety of methods used to measure adherence in the medical literature. Nonadherence seems to be nearly 4 times higher in pediatric and adolescent patients versus adult transplant recipients. Several nonadherence risk factors, such as high medication costs, psychiatric disorders, the conviction that the medication is harmful, and side effects of immunosuppressive therapy, have been described among adult liver transplant patients. The risk factors for nonadherence in pediatric and adolescent liver transplant patients are psychological distress, the functional status of their families, and the impact of immunosuppressive side effects on their physical appearance. A single approach to promoting adherence to general medical prescriptions has been proved to be ineffectual, so a multidisciplinary strategy should be adopted to achieve significant improvements in this field. The aim of this review is to analyze the published literature on adherence in liver transplant patients with a particular focus on the reported prevalence and the identified risk factors. Patients have been split into 2 age groups (adults and children/adolescents) because the scale of the problem and the potential risk factors differ in the 2 groups., (Copyright © 2011 American Association for the Study of Liver Diseases.)