No abstract

The objective was to study the effects of age, education and gender on verbal fluency in cognitively unimpaired, older individuals. The methods used were as follows: cognitively unimpaired elderly (55-84 years) subjects (n=153), were administered category (animal) (CF) and letter (/pa/) (LF) fluency tasks, in their native language of Malayalam. Results and conclusions were (1) Level of education, but not age or gender, significantly influence LF. (2) Level of education (directly) and in the elderly subjects, age (inversely) affect CF. (3) Age, but not education, has a differential effect on the tasks of verbal fluency, influencing CF more than LF.

The m-ACE provides a culture-fair Malayalam adaptation of the ACE with component items of equivalent difficulty.

Identifying a core set of features is one of the most important steps in the development of an automated seizure detector. In most of the published studies describing features and seizure classifiers, the features were hand-engineered, which may not be optimal. The main goal of the present paper is using deep convolutional neural networks (CNNs) and random forest to automatically optimize feature selection and classification. The input of the proposed classifier is raw multi-channel EEG and the output is the class label: seizure/nonseizure. By training this network, the required features are optimized, while fitting a nonlinear classifier on the features. After training the network with EEG recordings of 26 neonates, five end layers performing the classification were replaced with a random forest classifier in order to improve the performance. This resulted in a false alarm rate of 0.9 per hour and seizure detection rate of 77% using a test set of EEG recordings of 22 neonates that also included dubious seizures. The newly proposed CNN classifier outperformed three data-driven feature-based approaches and performed similar to a previously developed heuristic method.

Objective:To develop and validate an Instrumental Activities of Daily Living Scale for elderly people (IADL-E) to use in conjunction with cognitive screening tests for dementia in an educationally and socioculturally heterogeneous population.Method: Eleven IADL items were selected and weighted for major factors causing heterogeneity in the population -gender, education, social (rural/urban) setting and age. Each item was rated for its applicability (yes/no), degree of disability (scored from 0 to 2) and causative impairment (cognitive and/or physical). From this a composite index of cognitive (CDI) or physical (PDI) disability was derived. Validation was performed retrospectively on 240 subjects: 135 without and 105 with dementia by DSM-IV. Results: The IADL-E had a high internal consistency (α = 0.95). The area under the receiver operating characteristic (ROC) curve was 0.97 (CI = 0.94-0.99). A cutoff score of 16 on CDI provided a sensitivity of 0.91, specificity 0.99 and positive predictive value 0.76 (at 5% base rate). IADL-E correlated highly with clinical (DSM-IV, κ = 0.89), functional (CDR, 0.82) and cognitive (Mini-mental Status Examination, MMSE, 0.74) diagnoses. It showed good responsiveness, with the change on CDI over a median of 23 months correlating significantly with that on MMSE (coefficient = -0.382, CI = -0.667 to -0.098; p = 0.009). Individual items had good interrater and test-retest reliability. 461 462 P. S. Mathuranath et al. Conclusions:The IADL-E is a reliable, sensitive and responsive scale of functional abilities useful in dementia screening in a socioculturally heterogeneous population.

Background Data on the prevalence of dementia in India with a large and aging population is scant. We studied prevalence of AD and dementia in Kerala, South India, and effects of age, education and gender on it. Methods 2-phase survey on 2466 individuals aged ≥55 years living in community. Men constituted 41%, < 75 years age in 76.9% and education ≥4 years in 69.6%. Screening (Phase I) using the instrumental activity of daily living scale for the elderly (IADL-E) and the Addenbrooke’s cognition examination (ACE). Diagnostic-assessment (Phase II) was in 532 screen-positives and 247 (10%) screen-negatives. Results 93 (3.77%) ≥55 years and 81 (4.86%) ≥65 years of age had dementia. Age adjusted (against US-population in 2000) dementia (and AD) rates were 4.86% (1.91%) in age ≥55 years and 6.44% (3.56%) in ≥65 years. Odds for dementia (and AD) were high with increasing-age 5.89 (15.33) in 75–84, 13.23 (25.92) ≥85 years, and in women 1.62 (2.95); and low 0.27 (0.16) if education was ≥9 years. Age and low education increased dementia. Age and female gender increased AD. Conclusion Prevalence of dementia and AD is higher than any reported from the subcontinent suggesting that dementia in Kerala in South India is not uncommon. Increasing age increased dementia and AD. Low-education is associated with dementia and female-gender with AD.

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This study provides Class III evidence that sirolimus does not significantly reduce seizure frequency in children with TSC and intractable epilepsy. The study lacked the precision to exclude a benefit from sirolimus.