Amanda Ng

Cerebral white matter hyperintensity in Parkinson's disease: A major risk factor for mild cognitive impairment

BACKGROUND Mild cognitive impairment (MCI) and dementia contribute to a poor quality of life among patients with PD. The influence of cerebral ischemia as a risk factor for MCI in PD has not been adequately investigated. To address this issue, we examined the influence of the volume and distribution of white matter hyperintensity (WMH) as a risk factor for MCI in early PD. METHODS Prospective study of patients with early idiopathic PD. All patients had baseline MRI-FLAIR, clinical assessment and detailed neuropsychological evaluation. Data on demographics, vascular risk factors, cognitive performance and WMH volumes were analyzed. RESULTS 91 patients; mean age 64.9 years, mean education of 10.5 years. 24 patients fulfilled the Movement Disorder Society criteria for MCI and were classified as PD-MCI while the rest were classified as PD with no cognitive impairment (PD-NCI). Patients with PD-MCI and PD-NCI did not differ in Hoehn & Yahr staging. PD-MCI patients had a higher prevalence of diabetes mellitus, hypertension and hyperlipidemia. PD-MCI patients had significantly greater volume of periventricular (6.04 ml vs. 2.66 ml, p = 0.001) and deep subcortical WMH (2.16 vs.1.44, p = 0.002). Regional WMH was significantly greater among PD-MCI in the frontal, parietal and occipital regions. Logistic regression analyses demonstrated WMH to be associated with PD-MCI independent of age, education, and vascular risk factors. Increasing WMH volume was associated with lower performance on executive function, memory and language. CONCLUSIONS WMH is an important risk factor for PD-MCI independent of vascular risk factors. PD patients with WMH should be regularly screened for MCI.

White Matter Disease Independently Predicts Progression from Mild Cognitive Impairment to Alzheimer’s Disease in a Clinic Cohort

Background: The contribution of vascular pathology to the rate of progression from mild cognitive impairment (MCI) to Alzheimer’s disease (AD) remains unclear. Objective: To ascertain the relative roles of cerebral white matter disease and medial temporal atrophy (MTA) in predicting progression from MCI to AD. Methods: MCI patients with baseline MRI and ≧18 months of longitudinal follow-up were evaluated. DSM-IV-TR criteria were used to diagnose conversion to dementia. MTA and white matter hyperintensity (WMH) were quantified using the Scheltens scale and modified Fazekas scale. Results: Of a total of 171 MCI patients, 79 patients with baseline MRI and longitudinal follow-up were studied. Twenty-three MCI patients who progressed to dementia (MCI-P) were identified corresponding to a 19.4% annual risk of conversion. In MCI-P patients, the mean Mini-Mental State Examination and Montreal Cognitive Assessment decline was 1.3 and 2.9 points, respectively. MTA, periventricular WMH and deep subcortical WMH were significantly greater in the MCI-P cohort. WMH was found to predict MCI-P with an odds ratio of 7.69 (p = 0.03). Conclusion: MTA and deep subcortical WMH independently predict conversion from MCI to AD. Optimization of vascular risk factors among patients with MCI can potentially reduce the conversion from MCI to AD.

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.

Frontotemporal Dementia in Southeast Asia: A Comparative Study

Background: The clinical profile of frontotemporal dementia (FTD) in Southeast Asia is not known. We characterized and compared the demographic and clinical characteristics of FTD patients in Southeast Asia with North Asian and Western patients. Methods: The study included Southeast Asian FTD patients presenting to a tertiary neurology institute. Behavioral variant (bv-FTD) and language variant (lv-FTD) subtypes of FTD were diagnosed based on the Lund-Manchester criteria. The patients were characterized according to demographics, clinical, neuroimaging and longitudinal profiles. Results: Twenty-five bv-FTD and 19 lv-FTD patients were identified, with a female predominance ratio of 2:1 and a mean age of 56 years. The mean MMSE score was 16.2, and 88.4% of patients had memory symptoms. Over 5.1 ± 2.4 years of follow-up, 60% of bv-FTD and 36.8% of lv-FTD patients developed a second FTD syndrome. bv-FTD was the predominant type of FTD among Southeast Asians. Conclusion: FTD represents an important cause of young-onset dementia in Southeast Asia. Greater awareness of FTD is required to ensure early diagnosis and management.

Cognitive Screening in Asia: Recognizing the Role of the Patient-Family Unit

Background/Aims: Cognitive screening programmes may improve awareness and help at-risk subjects receive earlier medical attention. Cognitive profiles of subjects who attend cognitive screening by personal choice (self-referred) compared to those where the referral was initiated by family members (family-referred) were compared. Methods: A cross-sectional survey of community subjects attending a cognitive screening initiative. Performance on the MMSE, Frontal Assessment Battery (FAB), Elderly Cognitive Assessment Questionnaire (ECAQ) and Even Briefer Assessment Scale for Depression was evaluated. Results: A total of 342 subjects with a mean age of 59.2 ± 9.0 years were screened. Overrepresentation of Chinese and Indian subjects and underrepresentation of Malay subjects was noted. The prevalence of cognitive impairment ranged from 7.0 to 9.6% depending on the screening instrument used. Of the 342 subjects, 267 were self-referred, while 75 subjects were family-referred. Family-referred subjects had lower MMSE (p < 0.001), lower ECAQ (p < 0.001) and lower FAB (p < 0.001) scores but were not more depressed compared to self-referred subjects (p = 0.904). Only the difference in ECAQ scores remained significant after adjustment for baseline differences in age and education. The prevalence of hypertension, diabetes mellitus and hypercholesterolaemia was not statistically different between the 2 groups. Conclusions: Family members play a crucial role in the diagnosis of cognitive impairment, especially in older subjects with fewer years of education.

Community Cognitive Screening: Do differences exist between self referred and family referred subjects?

with CDRS score 0.5, who did not meet the DSM-IV dementia criteria, were selected and diagnosed as MCI. 38 subjects with CDRS score 0.5 or more, who met the DSM-IV dementia criteria were diagnosed as AD. Old age, low levels of education, histroy of head trauma were associated significantly with AD (p<0.01, p<0.01 p<0.05). Interestingly, the proportion of subjects on DM medications was significantly different among the three groups (p<0.05). There were significant differences in the mean score of MMSE-KC and GDS-K among normal, MCI and the AD group (p<0.01, p<0.01). These scores were significantly correlated with each other in this study population (p<0.05). There was a significant correlation between the MMSE-KC score and serum total cholesterol and triglyceride levels in MCI group (p<0.05, p<0.05), but not in normal controls and AD group. Finally, we found that the mean score of Hachinski Ischemic Scale was significantly different among three groups (p<0.05). Conclusions: Our results strongly suggested that many vascular risk factors are associated with cognitive impairments in MCI and AD patients. In this study,serum lipid levels were associated with global cognitive dysfunction in MCI group. We confirmed that DM is a risk factor for MCI and AD in our Korean population.