P375 The mathematical approach for diagnosis early stage of Parkinson’s disease - Kačar, Aleksandra; Janković, Marko (Clinical neurophysiology, 2017)
Parkinson’s disease (PD) is a neurodegenerative disorder characterized by a different motor and non-motor signs. Since there is no diagnostic biological marker for Parkinson disease, the diagnosis is based on the results of clinical assessment. From that reason early cases of PD present a diagnostic challenge. We analyzed possibilityof diagnosis of Parkinson’s disease in an early stage, based on characteristics of the input-output curve. Input-output (IO) curve was analyzed in two ways: gain of the curve for low-level transcranial stimulation (110% of motor threshold-MT) and calculation M of the IO curve “quality“, based on the quantum Tsallis entropy E(q): M=∑k=1Kp(xk)q=1-(q-1)E(q) where K is the number of selected points of IO curve, xk are selected points of IO curve and p stands for probability. Healthy subjects with MT<100μV, have significant gain for stimulation at the level of 110% of MT, which is not the case for the unhealthy subjects (100% cases). Healthy subjects with MT >100μV have gain in a limited interval (70% cases), while all unhealthy subjects have gain that is out of that interval. IO curve quality of the healthy subjects is in the limited interval, while 80% of the unhealthy subjects have quality outside of the interval. A thorough understanding of the broad spectrum of clinical manifestations of PD is essential to the proper diagnosis of the disease. It seems that unhealthy subjects on the lower level of stimulation (110% of MT) have bigger increase of the MEP, which means that in the early stage of illness they have compromised inhibitive regulatory mechanisms.