TY - GEN
T1 - Heart rate variability biomarkers of leucine-rich repeat kinase 2-associated Parkinson's disease
AU - Naranjo, Claudia Carricarte
AU - Marras, Connie
AU - Visanji, Naomi P.
AU - Cornforth, David J.
AU - Sanchez-Rodriguez, Lazaro
AU - Schule, Birgitt
AU - Goldman, Samuel M.
AU - Estevez, Mario
AU - Stein, Phyllis K.
AU - Lang, Anthony E.
AU - Machado, Andres
AU - Jelinek, Herbert F.
N1 - Funding Information:
*Study supported by an International Movement Disorder Society travel grant to CCN, and a Michael J. Fox Foundation research grant to CM and BS. H. F. Jelinek is with the Khalifa University, Abu Dhabi, UAE (e-mail: [email protected]).
Funding Information:
Study supported by an International Movement Disorder Society travel grant to CCN, and a Michael J. Fox Foundation research grant to CM and BS.
Publisher Copyright:
© 2020 IEEE.
PY - 2020/7
Y1 - 2020/7
N2 - Leucine-rich repeat kinase 2 (LRRK2) mutations are the most common known cause of both familial and sporadic Parkinson's disease (PD). On a single patient basis, LRRK2-associated PD (LRRK2-PD) and idiopathic PD (iPD) are indistinguishable. Recent evidence suggests that LRRK2-PD may be related to greater vagal activity. This study aimed to explore the potential of standard and novel heart rate variability (HRV) measures to distinguish LRRK2-PD from iPD patients. Support vector machine classifiers, based on HRV features, were used to discriminate between PD types. The combination of two classifiers reached 79% sensitivity and 86% specificity. Cardiac autonomic biomarkers may be useful to accurately distinguish individuals with LRRK2-PD from iPD.
AB - Leucine-rich repeat kinase 2 (LRRK2) mutations are the most common known cause of both familial and sporadic Parkinson's disease (PD). On a single patient basis, LRRK2-associated PD (LRRK2-PD) and idiopathic PD (iPD) are indistinguishable. Recent evidence suggests that LRRK2-PD may be related to greater vagal activity. This study aimed to explore the potential of standard and novel heart rate variability (HRV) measures to distinguish LRRK2-PD from iPD patients. Support vector machine classifiers, based on HRV features, were used to discriminate between PD types. The combination of two classifiers reached 79% sensitivity and 86% specificity. Cardiac autonomic biomarkers may be useful to accurately distinguish individuals with LRRK2-PD from iPD.
UR - http://www.scopus.com/inward/record.url?scp=85091056914&partnerID=8YFLogxK
U2 - 10.1109/ESGCO49734.2020.9158194
DO - 10.1109/ESGCO49734.2020.9158194
M3 - Conference contribution
AN - SCOPUS:85091056914
T3 - 2020 11th Conference of the European Study Group on Cardiovascular Oscillations: Computation and Modelling in Physiology: New Challenges and Opportunities, ESGCO 2020
BT - 2020 11th Conference of the European Study Group on Cardiovascular Oscillations
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 11th Conference of the European Study Group on Cardiovascular Oscillations, ESGCO 2020
Y2 - 15 July 2020
ER -