How to understand it: Neuropsychological testing

Neuropsychological testing is a key diagnostic tool for assessing people with dementia and mild cognitive impairment, but can also help in other neurological conditions such as Parkinson’s disease, stroke, multiple sclerosis, traumatic brain injury and epilepsy. While cognitive screening tests offer gross information, detailed neuropsychological evaluation can provide data on different cognitive domains (visuospatial function, memory, attention, executive function, language and praxis) as well as neuropsychiatric and behavioural features. We should regard neuropsychological testing as an extension of the neurological examination applied to higher order cortical function, since each cognitive domain has an anatomical substrate. Ideally, neurologists should discuss the indications and results of neuropsychological assessment with a clinical neuropsychologist. This paper summarises the rationale, indications, main features, most common tests and pitfalls in neuropsychological evaluation

Using the Oxford Cognitive Screen to detect cognitive impairment in stroke patients: a comparison with the Mini-Mental State Examination

Background: The Oxford Cognitive Screen (OCS) was recently developed with the aim of describing the cognitive deficits after stroke. The scale consists of 10 tasks encompassing five cognitive domains: attention and executive function, language, memory, number processing, and praxis. OCS was devised to be inclusive and un-confounded by aphasia and neglect. As such, it may have a greater potential to be informative on stroke cognitive deficits of widely used instruments, such as the Mini-Mental State Examination (MMSE) or the Montreal Cognitive Assessment, which were originally devised for demented patients. Objective: The present study compared the OCS with the MMSE with regards to their ability to detect cognitive impairments post-stroke. We further aimed to examine performance on the OCS as a function of subtypes of cerebral infarction and clinical severity. Methods: 325 first stroke patients were consecutively enrolled in the study over a 9-month period. The OCS and MMSE, as well as the Bamford classification and NIHSS, were given according to standard procedures. Results: About a third of patients (35.3%) had a performance lower than the cutoff (<22) on the MMSE, whereas 91.6% were impaired in at least one OCS domain, indicating higher incidences of impairment for the OCS. More than 80% of patients showed an impairment in two or more cognitive domains of the OCS. Using the MMSE as a standard of clinical practice, the comparative sensitivity of OCS was 100%. Out of the 208 patients with normal MMSE performance 180 showed impaired performance in at least one domain of the OCS. The discrepancy between OCS and MMSE was particularly strong for patients with milder strokes. As for subtypes of cerebral infarction, fewer patients demonstrated widespread impairments in the OCS in the Posterior Circulation Infarcts category than in the other categories. Conclusion: Overall, the results showed a much higher incidence of cognitive impairment with the OCS than with the MMSE and demonstrated no false negatives for OCS vs MMSE. It is concluded that OCS is a sensitive screen tool for cognitive deficits after stroke. In particular, the OCS detects high incidences of stroke-specific cognitive impairments, not detected by the MMSE, demonstrating the importance of cognitive profiling

Development of a video-simulation instrument for assessing cognition in older adults

Abstract Background Commonly used methods to assess cognition, such as direct observation, self-report, or neuropsychological testing, have significant limitations. Therefore, a novel tablet computer-based video simulation was created with the goal of being valid, reliable, and easy to administer. The design and implementation of the SIMBAC (Simulation-Based Assessment of Cognition) instrument is described in detail, as well as informatics “lessons learned” during development. Results The software emulates 5 common instrumental activities of daily living (IADLs) and scores participants’ performance. The modules were chosen by a panel of geriatricians based on relevance to daily functioning and ability to be modeled electronically, and included facial recognition, pairing faces with the correct names, filling a pillbox, using an automated teller machine (ATM), and automatic renewal of a prescription using a telephone. Software development included three phases 1) a period of initial design and testing (alpha version), 2) pilot study with 10 cognitively normal and 10 cognitively impaired adults over the age of 60 (beta version), and 3) larger validation study with 162 older adults of mixed cognitive status (release version). Results of the pilot study are discussed in the context of refining the instrument; full results of the validation study are reported in a separate article. In both studies, SIMBAC reliably differentiated controls from persons with cognitive impairment, and performance was highly correlated with Mini Mental Status Examination (MMSE) score. Several informatics challenges emerged during software development, which are broadly relevant to the design and use of electronic assessment tools. Solutions to these issues, such as protection of subject privacy and safeguarding against data loss, are discussed in depth. Collection of fine-grained data (highly detailed information such as time spent reading directions and the number of taps on screen) is also considered. Conclusions SIMBAC provides clinicians direct insight into whether subjects can successfully perform selected cognitively intensive activities essential for independent living and advances the field of cognitive assessment. Insight gained from the development process could inform other researchers who seek to develop software tools in health care