Kaavya Narasimhalu

Severity of CIND and MCI predict incidence of dementia in an ischemic stroke cohort

Background: The utility of poststroke cognitive status, namely dementia, cognitive impairment no dementia (CIND), mild cognitive impairment (MCI), and no cognitive impairment (NCI), in predicting dementia has been previously examined. However, no studies to date have compared the ability of subtypes of MCI and CIND to predict dementia in a poststroke population. Methods: A cohort of ischemic stroke patients underwent neuropsychological assessment annually for up to 5 years. Dementia was defined using the DSM-IV criteria. Univariate and multivariable Cox proportional regression was performed to determine the ability of MCI subtypes, CIND severity, and individual domains of impairment to predict dementia. Results: A total of 362 patients without dementia were followed up for a mean of 3.4 years (17% drop out), with 24 developing incident dementia. Older age, previous and recurrent stroke, and CIND and MCI subtypes were significant predictors of dementia. In multivariable analysis controlling for treatment allocation, patients who were older, had previous or recurrent stroke, and had either CIND moderate or multiple domain MCI with amnestic component were at elevated risk for dementia. In multivariable domain analysis, recurrent strokes, age, and previous strokes, verbal memory, and visual memory were significant predictors of dementia. Receiver operating characteristic curve analysis showed that CIND moderate (area under the curve: 0.893) and multiple domain MCI with amnestic component (area under the curve: 0.832) were significant predictors of conversion to dementia. All other classifications of cognitive impairment had areas under the curve less than 0.7. Conclusion: Stroke patients with cognitive impairment no dementia (CIND) moderate are at higher risk of developing dementia, while CIND mild patients are not at increased risk of developing dementia.

The Prognostic Effects of Poststroke Cognitive Impairment No Dementia and Domain-Specific Cognitive Impairments in Nondisabled Ischemic Stroke Patients

Background and Purpose— There is some evidence that poststroke dementia, cognitive impairment no dementia (CIND), and mild cognitive impairment predict for poor outcomes such as dementia, death, and institutionalization. However, few studies have examined the prognostic value of CIND, CIND severity, and domain impairments in a poststroke cohort. Methods— A cohort of ischemic stroke patients with baseline cognitive assessments 3 months poststroke were followed up annually for outcomes of dependency, vascular events, and death for up to 5 years. Univariate and multivariate Cox proportional regression was performed to determine the ability CIND, CIND severity, and domain impairments to predict dependency, vascular outcomes, and death. Results— Four-hundred nineteen patients without dementia (mean age 60±11 years, 32% female) were followed for a mean of 3.2 years. Older age, diabetes, more severe strokes, CIND-mild, and CIND-moderate were independently predictive of dependency. There were no independent predictors of recurrent vascular events. Older age, diabetes, and CIND-moderate were independently predictive of death. In analyses of individual cognitive domains, impairments in visuomotor speed were independently predictive of dependency. Conclusions— In poststroke patients, CIND predicts dependency and death, while CIND severity discriminates patients with poor survival. Impairments in visuomotor speed independently predict dependency. Clinical Trial Registration— URL: http://clinicaltrials.gov. Unique Identifier: NCT00161070.

Improving Detection of Dementia in Asian Patients with Low Education: Combining the Mini-Mental State Examination and the Informant Questionnaire on Cognitive Decline in the Elderly

Background/Aims: Previous work combining the Mini-Mental State Examination (MMSE) and Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) has been conducted in western populations. We ascertained, in an Asian population, (1) the best method of combining the tests, (2) the effects of educational level, and (3) the effect of different dementia etiologies. Methods: Data from 576 patients were analyzed (407 nondemented controls, 87 Alzheimer’s disease and 82 vascular dementiapatients). Sensitivity, specificity and AUC values were obtained using three methods, the ‘And’ rule, the ‘Or’ rule, and the ‘weighted sum’ method. Results: The ‘weighted sum’ rule had statistically superior AUC and specificity results, while the ‘Or’ rule had the best sensitivity results. The IQCODE outperformed the MMSE in all analyses. Patients with no education benefited more from combined tests. There was no difference between Alzheimer’s disease and vascular dementia populations in the predictive value of any of the combined methods. Conclusion: We recommend that the IQCODE be used to supplement the MMSE whenever available and that the ‘weighted sum’ method be used to combine the MMSE and the IQCODE, particularly in populations with low education. As the study population selected may not be representative of the general population, further studies are required before generalization to nonclinical samples.

Cognitive decline in early Parkinson's disease†

Data on the prevalence and severity of cognitive impairment among patients with newly diagnosed idiopathic Parkinsons disease (PD) is limited. Using a prospectively collected clinical database, we studied the longitudinal trend of mini‐mental state examination (MMSE) change and baseline factors predictive for MMSE decline. One hundred six patients with mean age of 61.2 years and mean baseline MMSE of 27.8 ± 2.3 were studied. MMSE increased by 0.4 points/year among patients without cognitive decline (n = 73) and decreased by 2.39 points/year among patients with cognitive decline (n = 33). Univariate analysis demonstrated education, age of diagnosis, depression, and diabetes mellitus to be associated with cognitive decline. Motor scores and hallucination were not associated with cognitive decline. Multivariate analysis demonstrated higher level of education to be protective (HR = 0.91, 95% CI 0.82–0.99, P = 0.047) and depression having borderline significance in predicting cognitive decline (HR = 2.00, 95% CI 0.97–4.15, P = 0.061). We found that 31% of newly diagnosed idiopathic PD patients have measurable cognitive decline at an early stage of disease. Higher education is protective while depression may be predictive of cognitive decline.

Frontal subcortical ischemia is crucial for post stroke cognitive impairment.

BACKGROUND The incidence of post stroke cognitive impairment (PSCI) and predictive factors for PSCI among patients with acute lacunar infarcts is unclear. OBJECTIVE To study the impact of acute lacunar infarcts and chronic white matter disease in the development of PSCI. METHODS Prospective cohort study of stroke patients attending a tertiary neurology center. Patients with MRI confirmed acute lacunar infarcts without pre-existing dementia were recruited. Logistic regression was used to determine risk factors for developing PSCI. RESULTS 145 patients with a mean age of 55.8 years were studied of which 48 patients (33.1%) were identified to have PSCI. Patients with PSCI performed worse on the MMSE, MOCA and FAB and had significantly greater white matter hyperintensity (WMH) in the frontal subcortical (FSC) region (p = 0.006) and higher frontal subcortical acute infarct load (p = 0.002). Logistic regression demonstrated that deep subcortical WMH (odds ratio, OR = 1.45) and acute FSC infarcts (OR = 1.51) were associated with PSCI. High WMH load without acute FSC infarcts was associated with increased risk of PSCI (OR = 4.1). When patients developed acute FSC infarcts on pre-existing severe WMH, the risk of PSCI increased substantially (OR = 11.0). CONCLUSIONS Patients with acute lacunar infarcts in the FSC region have 1.5 times risk of PSCI. This risk increases substantially to 11 times when there is pre-existing severe white matter disease.

Inflammatory markers and their association with post stroke cognitive decline.

Background Population-based studies have demonstrated the association of inflammation and cognitive impairment. However, few studies to date have examined this association in ischemic stroke patients. Aims The study aims to determine the association between inflammatory markers and cognitive impairment. Methods Ischemic stroke patients with baseline neuropsychological assessments at three-months poststroke were followed up with annual neuropsychological assessments for up to five-years. Inflammatory markers (C-reactive protein, interleukin 1β, interleukin 6, interleukin 8, interleukin 10, interleukin 12, and tumor necrosis factor-α) were assayed, and logistic regression analyses were performed to determine associations between inflammatory markers and both baseline cognitive status and subsequent cognitive decline. Results There were 243 ischemic stroke patients in the study. In multivariable ordinal logistic regression analysis, age, education, ethnicity, stroke subtype, and interleukin 8 (OR 1·23 CI 1·05–1·44) levels were independently associated with baseline cognitive status. In multivariable logistic regression analyses, age, gender, recurrent strokes, and interleukin 12 (OR 25·02 CI 3·73 to 168·03) were independent predictors of subsequent cognitive decline. Conclusions Following ischemic stroke, higher serum interleukin 8 is independently associated with baseline cognitive impairment while higher serum interleukin 12 is associated with subsequent cognitive decline.

Post‐stroke subjective cognitive impairment is associated with acute lacunar infarcts in the basal ganglia

While recent studies have examined neuroimaging correlates of post‐stroke mild cognitive impairment (MCI), no studies have examined neuroimaging correlates of post‐stroke subjective cognitive impairment (SCI).

Utility of the AD8 as a Self-Rating Tool for Cognitive Impairment in an Asian Population

Background: AD8 is a brief informant interview used to detect early cognitive change. This study evaluated the diagnostic performance of the participant-rated AD8 (p-AD8) in a predominantly Chinese population. Methods: Data on demographics, clinical, and cognitive features were collected from 73 participants with no cognitive impairment (NCI), 27 participants with mild cognitive impairments, and 78 participants with Alzheimer’s disease–informant dyads. Agreement and discriminative properties of p-AD8 were assessed. Results: AD8 scores were associated with dementia severity. Participant and informant AD8 scores were moderately correlated within dementia dyads. The p-AD8 showed good diagnostic performance in differentiating between participants with NCI and participants with cognitive impairment (sensitivity = 85.0%, specificity = 74.0%, and area under the curve = 0.80), with a cutoff score of ≥1. Combination of impairment in Mini-Mental State Examination and p-AD8 is more useful in detecting cognitive impairment than using the AD8 alone. Conclusion: Within a transcultural setting, the p-AD8 demonstrated good discriminative validity and can be used to gain a preliminary understanding of an individual’s cognitive status.

Differences exist in the cognitive profile of mild Alzheimer's disease and subcortical ischemic vascular dementia.

Background/Aims: Our objective was to characterize the cognitive profile of patients with mild Alzheimer’s disease (AD) and subcortical ischemic vascular dementia (SIVD) matched using a functional scale. Methods: AD and SIVD were diagnosed using the NINCDS-ADRDA and the criteria proposed by Erkinjuntti et al., respectively. The Clinical Dementia Rating (CDR) scale was used to guide the identification of patients with mild dementia from a prospective clinical database. Regression analysis was applied to compare the 2 groups on global and individual cognitive domains. Results: The greatest cognitive differences between the 2 groups were observed in the domains of visuospatial function (p = 0.001), working memory (p = 0.013) and visuomotor speed (p = 0.028). No significant variation was demonstrated in the executive function domain (p = 0.646). Statistically significant differences between AD and SIVD patients were found in episodic memory delayed recall tasks but not in the immediate recall tasks. A trend towards severer depressive symptoms (p = 0.052) was observed among the SIVD patients. Conclusions: SIVD patients with mild dementia have greater deficits in visuospatial function, working memory and visuomotor speed and may also be more depressed compared to AD patients. Executive function tests in general do not distinguish the 2 groups, although timed executive tasks can separate them.

Validity of dementia diagnoses in two Swedish health registers

latent classes. This work further investigates cognitive change over time in any realized latent classes. Methods: Baseline raw data on seven standardized clinical tests (Digit Span, Digit Symbol-Coding, CVLT-II LDFR, RCFT 30-minute delay, LM-II, letter fluency and category fluency) from 737 participants from the AIBL-HC group were used in a multivariate latent-class model to test for the existence of more than one latent class after adjusting for various demographics. Linear mixed-effects models were used to examine cognitive change over time (baseline, 18 and 36 months). Results: Latent-class modelling suggested two classes existed within the HC group: a higher functioning (HHC) group and a normative (NHC) group. Performances for HHC were, on average, 1 standard deviation above NHC at baseline on all clinical test scores. A higher proportion of NHC (55%) were memory-complainers compared to HHC (48%). Cognitive scores for coding and category fluency decreased over time at a similar rate for both classes. Scores for letter fluency and RCFT delayed recall increased on average over time. For the remaining clinical variables the HHC group experienced a steep decline over the first 18 months followed by fairly stable results, while the NHC group either declined less rapidly, increased slightly or remained fairly stable over the whole 36 month period. Conclusions: Two distinct classes were found within the HC with the HHC group having significantly higher cognitive scores than the NHC, due perhaps to different self-selection mechanisms. Longitudinal results suggest caution with clinical variables chosen to model cognitive decline; variables from different cognitive domains exhibited increases over time suggesting a learning effect. Significant interactions implied differential effects with the HHC group seemingly catching up to the NHC group over time. Generally a decline in cognitive scores over time was observed.