We invite you to attend the Thesis Presentation of Alexandra Gramotnev, a Master of Arts candidate within the School of Social Sciences, in the Faculty of Arts, Business and Law.
Title: Statistical modelling of cognitive function at early stages of Parkinson’s disease
Presenter: Alexandra Gramotnev
When: Thursday 20th September, 12nn-1pm
Where: Thompson Institute 1.02
Cognitive deficit is a common non-motor manifestation of Parkinson's disease (PD), even at its early stages. Although links between some clinical or pathological measures and cognition in early PD have been established, a comprehensive understanding of parameters which could accurately predict cognitive deficits or cognitive decline still does not exist. The aim of this work was to identify and characterize a network of direct and indirect effects of multiple clinical and pathological parameters on cognitive deficits in early PD.
Receiver Operating Characteristic regression analysis was first used to inform the most accurate cognitive measures in discriminating PD patients from controls, and Generalized Structural Equation Modelling - to establish networks of clinical and pathological parameters on cognition. The sample involved 419 drug-naïve PD patients and 196 controls from the Parkinson's Progression Markers Initiative.
The Montreal Cognitive Assessment (MoCA) and Symbol Digit Modalities Test (SDMT) were identified as the most effective cognitive measures in distinguishing PD patients. The network of significant effects of demographic factors, dopaminergic deficits, disease severity, non-motor symptoms, blood parameters, and amyloid plaque pathology were established and characterized, including the description of significant non-linear dependency of the MoCA score on age of PD patients.
The obtained outcomes will be important for the development of a consistent approach to clinical evaluation of cognitive deficits in early PD, and for identification and characterisation of new multivariate PD progression biomarkers predicting cognitive decline on the basis of the significant clinical and pathological measures.
Teaching has been a great part of Alexandra Gramotnev's life, and she has worked in mathematics and science education for over a decade. More recently, Alexandra has been involved in education (and other social sciences) research, before finally pursuing her great interest in neurodegenerative diseases. Her specific research interests are in cognition and progression of Parkinson's disease and Multiple Systems Atrophy.
Should you have any queries about this event please email FABLHDR@usc.edu.au.
We look forward to seeing you there.