Heart rate circadian profile in the differential diagnosis between Parkinson disease and multiple system atrophy

Pilleri, Manuela; Levedianos, Giorgio; Weis, Luca; Gasparoli, Elisabetta; Facchini, Silvia; Biundo, Roberta; Formento-Dojot, Patrizia; Antonini, Angelo

doi:10.1016/j.parkreldis.2013.11.006

Cited by 25 publications

(21 citation statements)

References 36 publications

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“…In particular, they observed that multiple system atrophy presented a higher HR during sleep and a lower nocturnal decline of HR compared to Parkinson disease. They concluded that night-time HR assessment was able to discriminate between the two diseases with acceptable accuracy [sensitivity of 84.2 % (95 % CI 60.5-96.6) specificity of 62.3 % (95 % CI 49.0-74.4)] [24]. The importance of ambulatory HR was also demonstrated in a large Registry (ABP International Study) of hypertensive patients.…”

Section: Characteristics Of Cardiovascular Autonomic Dysfunction Detementioning

confidence: 96%

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Autonomic Dysfunction: How to Identify and When to Treat?

Saladini

Marco²,

Palatini

2016

High Blood Press Cardiovasc Prev

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Cardiovascular autonomic dysfunction (AD) is a particular condition that can be detected by means of ambulatory blood pressure monitoring (ABPM). ABPM is helpful to identify some specific characteristics of haemodynamic AD, including non-dipping/reverse-dipping pattern, orthostatic and post-prandial hypotension and elevated blood pressure variability. These characteristics may be misdiagnosed with traditional, clinic blood pressure measurements. AD is relatively common in the real world. By analysing about 1000 recordings in a Cardiology unit, AD was found in 6.8 % of the exams. Several diseases may be the underlying causes of AD. In our sample half of the subjects were diabetic (54.4 %), 17.7 % were patients with alpha-synucleinopathy (Parkinson disease or multiple system atrophy), and 27.9 % had other underlying causes of AD including chronic kidney disease, α-lytic drug assumption and AD from unknown causes. According to the different aetiology, different clinical characteristics can be found, in particular in diabetics these peculiar aspects are less pronounced compared to the other subgroups. These characteristics have been found to be predictors of cardiovascular events, organ damage, and mortality. For these reasons, early identification of these behaviours is important, in order to better define patient's cardiovascular risk profile. As regard treatment of AD, several drugs have been tested, however none of this showed efficacy in all kinds of patients. Another open aspect is "safe" reference values for supine hypertension.

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Section: Characteristics Of Cardiovascular Autonomic Dysfunction Detementioning

confidence: 96%

“…24-h intra-arterial recording in a 74-year patient with multiple system atrophy. The arrows indicate the episodes of post-prandial hypotension or orthostatic hypotension and the reduced dipping pattern during sleeping time.…”

mentioning

confidence: 99%

Autonomic Dysfunction: How to Identify and When to Treat?

Saladini

Marco²,

Palatini

2016

High Blood Press Cardiovasc Prev

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“…However, only three of the 65 PD patients had OH, its performance between PD with OH and MSA need to be confirmed [60]. Pilleri et al demonstrated that the heart rate circadian profile might be a tool to distinguish PD from MSA [61]. Furthermore, imaging tools for the cardiac sympathetic system provide a more consistent conclusion.…”

Section: Impairments Of Cardiovascular Autonomic System In Pdmentioning

confidence: 99%

Recognition and treatment of autonomic disturbances in Parkinson’s disease

Reichmann

Ziemssen

2015

Expert Review of Neurotherapeutics

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Symptoms of dysautonomia are common in Parkinson's disease (PD), and almost all the functional autonomic subsystems can be involved in PD. However, they are still under-recognized in everyday clinical practice. Autonomic dysfunction can be observed in the early stages of PD, affect a substantial proportion of patients, impact quality of life and can also help in differential diagnosis. This review aims to provide an overview of the pathophysiology, clinical manifestations, relevant examination and treatment of cardiovascular, gastrointestinal, urogenital, thermoregulatory and pupil autonomic dysfunctions in Parkinson's disease.

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“…Lee et al (2014) analyze videos showing gait and posture characteristics of patients with PD to differentiate tem from Progressive Supranuclear Palsy (PSP) and Multiple System Atrophy (MSA) [12]. Pilleri et al (2014) use heart rate and circadian rhythm of patients with PD and MSA for differential diagnosis. They then put the data to t-test and ANCOVA test to compare the two groups [13].…”

Section: Introductionmentioning

confidence: 99%

“…Pilleri et al (2014) use heart rate and circadian rhythm of patients with PD and MSA for differential diagnosis. They then put the data to t-test and ANCOVA test to compare the two groups [13]. Navarro-Otano et al (2014) study 123I-metaiodobenzylguanidine (123I-MIBG), heart rate, odor recognition, and [123I]FP-CIT (DaTscan) SPECT to differentiate PD from Vascular Parkinsonism (VP).…”

Section: Introductionmentioning

confidence: 99%

Classification of Neurodegenerative Diseases using Machine Learning Methods

Aydın¹,

Aslan

2017

ijisae

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In this study, neurodegenerative diseases (Amyotrophic Lateral Sclerosis, Huntington's disease, and Parkinson's disease) were diagnosed and classified using force signals. In the classification, five machine learning algorithms Averaged 2-Dependence Estimators (A2DE), K star (K*), Multilayer Perceptron (MLP), Diverse Ensemble Creation by Oppositional Relabeling of Artificial Training Examples (DECORATE), Random Forest) were compared by the 10-fold Cross Validation method. K* classifier gave the best outcome among these algorithms. As a result of quad classification of the K* classifier, the best classification accuracy was 99.17%. According to the first three and five principal component qualifications which are created from these 19 features, the best classification accuracies of K* classifier were 95.44% and 96.68% respectively

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Heart rate circadian profile in the differential diagnosis between Parkinson disease and multiple system atrophy

Cited by 25 publications

References 36 publications

Autonomic Dysfunction: How to Identify and When to Treat?

Autonomic Dysfunction: How to Identify and When to Treat?

Recognition and treatment of autonomic disturbances in Parkinson’s disease

Classification of Neurodegenerative Diseases using Machine Learning Methods

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