Background and purpose: Age related white matter changes (ARWMC) are frequent in non-demented old subjects and are associated with impaired cognitive function. Our aim was to study the influence of vascular risk factors and ARWMC on the neuropsychological performance of an independent elderly population, to see if vascular risk factors impair cognition in addition to the effects of ARWMC. Methods: Independent subjects, aged 65-84 years, with any degree of ARWMC were assessed using a comprehensive neuropsychological battery including the Mini-Mental State Examination (MMSE), VADASCog (Alzheimer's disease assessment scale) and the Stroop and Trail Making test. Vascular risk factors were recorded and ARWMC (measured by MRI) were graded into three classes. The impact of vascular risk factors and ARWMC on neuropsychological performance was assessed by linear regression analyses, with adjustment for age and education. Results: 638 patients (74.1 (5) years old, 55% women) were included. Patients with severe ARWMC performed significantly worse on global tests of cognition, executive functions, speed and motor control, attention, naming and visuoconstructional praxis. Diabetes interfered with tests of executive function, attention, speed and motor control, memory and naming. Arterial hypertension and stroke influenced executive functions and attention. The effect of these vascular risk factors was independent of the severity of ARWMC, age and education. Conclusion: ARWMC is related to worse performance in executive function, attention and speed. Diabetes, hypertension and previous stroke influenced neuropsychological performance, independently of the severity of ARWMC, stressing the need to control vascular risk factors in order to prevent cognitive decline in the elderly. C erebral age related white matter changes (ARWMC) are frequently described on brain imaging in demented and non-demented elderly subjects.1 2 Some demographic and vascular risk factors are associated with a higher risk of developing ARWMC, with major emphasis on age, hypertension and stroke. [3][4][5][6] On the other hand, recent epidemiological evidence indicates that vascular risk factors play a role in the development of cognitive impairment and dementia, including degenerative dementia.7-11 ARWMC can be a mediator between vascular risk factors and cognitive decline, while some demographic characteristics can contribute towards protecting cognitive function.12 Our aim was to study the influence of ARWMC and vascular risk factors on the neuropsychological performance of non-disabled independent elderly people with ARWMC and to analyse if vascular risk factors had an independent effect on cognitive performance. METHODSThe LADIS (Leukoaraiosis and Disability) study is a prospective multinational European project investigating the independent impact of ARWMC on the transition to disability in the elderly. The rationale, methodology and baseline assessment have been described previously.12 13 Investigators were provided with a specifically developed han...

Post-stroke cognitive impairment (PSCI) includes all forms of cognitive decline that develop after stroke, even if not severe enough to fit the criteria of dementia. Our aims were to investigate the predictive value of a brief bedside examination (Montreal Cognitive Assessment, MoCA) in the acute phase of stroke on the diagnosis of mid-term PSCI, taking into account other clinical, cognitive, functional, and neuroimaging predictors. Consecutive patients admitted to a stroke unit were evaluated with MoCA between 5 and 9 days after stroke. At baseline, clinical, functional, and neuroimaging data were collected. Patients were reassessed between 6 and 9 months after stroke by means of an extensive neuropsychological and functional evaluation. Out of 137 enrolled stroke patients, 80 (58.4%) were followed up (mean age 68.2 ± 14.6 years, males 66%, mean NIHSS score 3.6 ± 4.8). PSCI was diagnosed in 47 patients (59%; 35 mild cognitive impairment, 12 dementia). Controlling for age, education, functional and cognitive pre-morbid status, stroke severity, and pre-existing lacunar infarcts, MoCA baseline score [OR (95% CI) = 1.4(1.1-1.8)] for each point] and leukoaraiosis severity [OR (95% CI) = 0.4(0.2-0.9)] for each point of the van Swieten scale] were independently associated with PSCI. Using a ROC analysis, a cut-off of 21 predicted the diagnosis of PSCI with 91.4 % sensitivity, 75.8 % specificity, 80 % positive predictive value, and 89.3 % negative predictive value. In a sample of mild stroke patients, MoCA seems to be a good predictor of mid-term PSCI, making it a possible candidate for a brief cognitive screening in the acute stroke setting.

Overall, the recognition of the disease before the development of the full clinical-neuroimaging picture may be challenging. Moreover, as we recently reported, none of the Background and Purpose-Cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) phenotype is highly variable, and, although the full clinical-neuroimaging picture may be suggestive of the disease, no characteristic is pathognomonic. Thus, a genetic test remains the diagnostic gold standard, but because it is costly and time-consuming, a pregenetic screening appears desirable. We aimed at developing the CADASIL scale, a screening tool to be applied in the clinical setting. Methods-A preliminary scale was created assigning weighted scores to common disease features based on their frequencies obtained in a pooled analysis of selected international CADASIL series. The accuracy of the scale versus the genetic diagnosis was tested with receiver operating characteristic analysis after the application of this scale to 61 CADASIL and 54 NOTCH3-negative patients (no pathogenic mutation on exons 2-23 of the NOTCH3 gene). To improve the scale accuracy, we then developed an ad hoc optimization algorithm to detect the definitive scale. A third group of 39 patients affected by sporadic small-vessel disease was finally included in the algorithm to evaluate the stability of the scale. Results-The cutoff score of the definitive CADASIL scale had a sensitivity of 96.7% and a specificity of 74.2%. This scale was robust to contamination of patients with sporadic small-vessel disease. Conclusions-The CADASIL scale is a simple and sufficiently accurate screening tool to select patients with a high probability to be affected by the disease and therefore to be subjected to the genetic testing.

The relationship between age-related white matter changes and cognitive performance in independent elderly people is still not clear. The Leukoaraiosis and Disability in the Elderly study (LADIS) involves 11 European centers. It aims to assess the role of the age-related white matter changes as an independent factor in the transition to disability, and in cognitive performance of an independent elderly population. A comprehensive neuropsychological battery was constructed in order to harmonize the cognitive assessment across countries. Patients were evaluated at baseline and during the 3-year follow-up with the Mini-Mental State Examination, a modified version of the VADAS-Cog (Alzheimer’s Dementia Assessment Scale plus tests of Delayed recall, Symbol digit, Digit span, Maze, Digit cancellation and Verbal fluency), Trail making and Stroop test. Six hundred thirty-eight patients (mean age 74 ± 5 years; mean educational level 10 ± 4, F/M: 351/287) were included in this study. Neuropsychological data were analyzed test by test and also grouped in three compound measures (executive, memory and speed/motor control domains). Older subjects (>74 years) performed significantly worse than younger subjects on the ADAS-Mod and on the tests of memory (t₆₃₁ = 3.25; p = 0.001), executive functions (t₅₈₁ = 4.68; p = 0.001) and speed/motor control (t₅₈₇ = 4.01; p = 0.001). Participants with higher educational level (>8 years of school) showed better performances on the compound measures for memory (t₆₃₁ = 3.25; p = 0.001), executive functions (t₅₈₁ = 4.68; p = 0.001) and speed/motor control (t₅₈₇ = 4.01; p = 0.001). Using multiple regression analysis models to study the influence of demographic variables on cognitive performance, age and education remained important variables influencing test performance. In the LADIS population baseline data, older age and lower educational levels negatively influence neuropsychological performance.