45 research outputs found
"A lady of few words": Review of literature and report of a case of progressive nonfluent aphasia type of frontotemporal dementia
No full textFrontotemporal dementia (FTD) is a clinically and pathologically heterogeneous syndrome. It can be classified into three clinical syndromes depending on the early and predominant symptoms: A behavioral variant FTD and two language variants namely, semantic dementia, and progressive nonfluent aphasia (PNFA) which are very rare and elude diagnosis. We report the case of an elderly homemaker who came to our institute with features of cognitive decline and behavioral problems with language deficits in the form of nonfluent speech, impaired vocabulary to three pairs of words, agrammatism, and impaired single sentence comprehension with corroborative magnetic resonance imaging findings. PNFA is a rare clinical variant of FTD and often underdiagnosed. It should be considered in elderly patients who apart from having cognitive decline, behavioral problems, and absent insight also develop limited vocabulary, especially using a set of nouns to express themselves. Speech therapy and behavioral therapy in the initial stages can be of utility
Transcranial magnetic stimulation in patients with early cortical dementia: A pilot study
No full textContext: The diagnostic accuracy of the currently available tools carries poor sensitivity resulting in significant delay in specific diagnosis of cortical dementias. Considering the properties of default mode networking of the brain it is highly probable that specific changes may be seen in frontotemporal dementias (FTDs) and Alzheimer′s disease sufficiently early. Aim: The aim of this study is to look for changes in Transcranial Magnetic Stimulation (TMS) in cortical dementia. Materials and Methods: Evaluated with a single pulse TMS with the figure of eight coil and recorded from right first dorsal interossei (FDI). Resting Motor Threshold (RMT) was estimated on the opposite motor cortex (T1). Second site of stimulation was cervical spine at C7-T2. Central motor conduction time (CMCT) is equal toT1-T2.Silent Period (SP) identified by applying TMS pulse to contracting FDI. Conclusions: RMT was reduced in seven out of eight Alzheimer′s dementias. CMCT was in the upper limit of normal in both patients with FTD. The most consistent observation was that SP was reduced and there were escape discharges noticed during the SP suggesting increased cortical excitability and decreased cortical inhibition. This suggests probable early asymptomatic changes in the gamma-aminobutyric acid (GABA) nergic and cholinergic system is taking place. This if confirmed may give some insight into early diagnosis and therapeutic role of GABA agonists in these disorders
Demographic features and neuropsychological correlates in a cohort of 200 patients with vascular cognitive decline due to cerebral small vessel disease
No full textIntroduction: Vascular dementia is the second most common form of dementia and is potentially reversible. Small vessel disease (SVD) closely mimics degenerative dementia in view of its sub-acute onset and progressive course. Therefore, unlike large vessel disease, Hachinski Ischemic scale score may not always reflect vascular cognitive decline resulting in diagnostic and therapeutic confusions. Therefore, there is a need for detailed neuropsychological assessment for various cognitive domains for early identification of vascular cognitive decline as it carries a very good long term prognosis for cognitive morbidity, unlike degenerative dementias. Patients and Methods: This prospective study involves thorough domain based neuropsychological assessment of patients with a radiological diagnosis of SVD involving the following parameters-digit forward and backward, category fluency, color trails, stick test, logical memory test, and bender gestalt test. Magnetic resonance imaging scans done using 3-tesla machines and SVD graded using Fazekas visual scale. Results: The mean Hachinskis score was less sensitive for differentiating vascular dementia from degenerative dementia. However, the domain based neuropsychological scores were highly sensitive showing statistically significant impairment in all 6 domains tested and compared with Fazekas 1-3 grades in imaging. Discussion and Conclusion: This study aimed at establishing an early diagnosis of vascular mild cognitive impairment using domain wise neuropsychological testing and correlating it with radiological scores. Hachinskis score is more sensitive for large vessel disease in view of acute onset and step-like progression as against steady progression in SVD. However, domain-wise testing was highly sensitive in identifying early cognitive impairment in patients with SVD, and early therapeutic interventions are highly rewarding
Heart Rate and its Variability from Short-term ECG Recordings as Biomarkers for Detecting Mild Cognitive Impairment in Indian Population
No full textAlterations in Heart Rate (HR) and Heart Rate Variability (HRV) can reflect autonomic dysfunction associated with neurodegeneration. We investigate the influence of Mild Cognitive Impairment (MCI) on HR and its variability measures in the Indian population by designing a complete signal processing pipeline to detect the R-wave peaks and compute HR and HRV features from ECG recordings of 10 seconds, for point-of-care applications. The study cohort involves 297 urban participants, among which 48.48% are male and 51.51% are female. From the Addenbrooke\u27s Cognitive Examination-III (ACE-III), MCI is detected in 19.19% of participants and the rest, 80.8% of them are cognitively healthy. Statistical features like central tendency (mean and root mean square (RMS) of the Normal-to-Normal (NN) intervals) and dispersion (standard deviation (SD) of all NN intervals (SDNN) and root mean square of successive differences of NN intervals (RMSSD)) of beat-to-beat intervals are computed. The Wilcoxon rank sum test reveals that mean of NN intervals (p = 0.0021), the RMS of NN intervals (p = 0.0014), the SDNN (p = 0.0192) and the RMSSD (p = 0.0206) values differ significantly between MCI and non-MCI classes, for a level of significance, 0.05. Machine learning classifiers like, Support Vector Machine (SVM), Discriminant Analysis (DA) and Naive Bayes (NB) driven by mean NN intervals, RMS, SDNN and RMSSD, show a high accuracy of 80.80% on each individual feature input. Individuals with MCI are observed to have comparatively higher HR than healthy subjects. HR and its variability can be considered as potential biomarkers for detecting MCI.Ni
Progressive limbic encephalopathy: Problems and prospects
No full textBackground: It was observed that a good number of patients presenting with psychiatric manifestations when investigated later because of unresponsiveness to treatment or late development of organic features turned out to be treatable limbic syndromes. Introduction: The aim of this study is to assess the patients presenting with new onset neuropsychiatric symptoms satisfying the criteria for probable limbic encephalitis. Patients and Methods: Patients referred to neurology department following a period of treatment for neuropsychiatric symptoms, which did not respond to conventional treatment were analyzed using Electroencephalography (EEG), magnetic resonance imaging, cerebrospinal fluid, screening for malignancy Vasculitic work-up, histopathology and autoantibody done when feasible. Results: There were 22 patients satisfying criteria for probable limbic encephalitis. Their mean age was 34.5 years. Symptoms varied from unexplained anxiety, panic and depression, lack of inhibition, wandering, incontinence, myoclonus, seizures and stroke like episodes. Three had systemic malignancy, 10 had chronic infection, one each with vasculitis, acute disseminated encephalomyelitis, Hashimoto encephalitis and two each with non-convulsive status, cryptogenic and Idiopathic inflammation. Conclusion: All patients who present with new onset neuropsychiatric symptoms need to be evaluated for sub-acute infections, inflammation, autoimmune limbic encephalitis and paraneoplastic syndrome. A repeated 20 minute EEG is a very effective screening tool to detect organicity
Classification of Alzheimer\u27s Dementia vs. Healthy subjects by studying structural disparities in fMRI Time-Series of DMN
No full textTime series from different regions of interest (ROI) of default mode network (DMN) from Functional Magnetic Resonance Imaging (fMRI) can reveal significant differences between healthy and unhealthy people. Here, we propose the utility of an existing metric quantifying the lack/presence of structure in a signal called, deviation from stochasticity (DS) measure to characterize resting-state fMRI time series. The hypothesis is that differences in the level of structure in the time series can lead to discrimination between the subject groups. In this work, an autoencoder-based model is utilized to learn efficient representations of data by training the network to reconstruct its input data. The proposed methodology is applied on fMRI time series of 50 healthy individuals and 50 subjects with Alzheimer\u27s Disease (AD), obtained from publicly available ADNI database. DS measure for healthy fMRI as expected turns out to be different compared to that of AD. Peak classification accuracy of 95% was obtained using Gradient Boosting classifier, using the DS measure applied on 100 subjects
