Large gait study of HSP, CA and PD

Posted - December 2017 in Living with HSP - Management & Treatment News

Confirms HSP gait as highly variable

 

This study measured a number of gait variables in people with HSP, cerebellar ataxia and Parkinson’s disease and compared them with healthy controls. Despite the significant number of HSPers in the study – 31 – no single variable or any of the variables in combination could distinguish an HSP gait pattern from the other conditions.

 

While this does not rule out gait measurements as a potential tool for evaluating the effect of treatments for HSP by comparing ‘before and after treatment’ measurements on an individual basis, it does highlight the high variability in HSP gait and the challenges that represents in developing gait measurements as a reliable tool.

 

Abstract

Patients with degenerative neurological diseases such as cerebellar ataxia, spastic paraplegia, and Parkinson’s disease often display progressive gait function decline that inexorably impacts their autonomy and quality of life. Therefore, considering the related social and economic costs, one of the most important areas of intervention in neurorehabilitation should be the treatment of gait abnormalities.

 

This study aims to determine whether an entire dataset of gait parameters recorded in patients with degenerative neurological diseases can be clustered into homogeneous groups distinct from each other and from healthy subjects. Patients affected by three different types of primary degenerative neurological diseases were studied. These diseases were: i) cerebellar ataxia (28 patients), ii) hereditary spastic paraplegia (31 patients), and iii) Parkinson’s disease (70 patients). Sixty-five gender-age-matched healthy subjects were enrolled as a control group. An optoelectronic motion analysis system was used to measure time-distance parameters and lower limb joint kinematics during gait in both patients and healthy controls.

 

When clustering single parameters, step width and ankle joint range of motion (RoM) in the sagittal plane differentiated cerebellar ataxia group from the other groups. When clustering sets of two, three, or four parameters, several pairs, triples, and quadruples of clusters differentiated the cerebellar ataxia group from the other groups. Interestingly, the ankle joint RoM parameter was present in 100% of the clusters and the step width in approximately 50% of clusters. In addition, in almost all clusters, patients with cerebellar ataxia showed the lowest ankle joint RoM and the largest step width values compared to healthy controls, patients with hereditary spastic paraplegia, and Parkinson’s disease subjects.

The red squares are HSP. Their large spread means high variability.

 

This study identified several clusters reflecting specific gait patterns in patients with degenerative neurological diseases. In particular, the specific gait pattern formed by the increased step width, reduced ankle joint RoM, and increased gait variability, can differentiate patients with cerebellar ataxia from healthy subjects and patients with spastic paraplegia or Parkinson’s disease. These abnormal parameters may be adopted as sensitive tools for evaluating the effect of pharmacological and rehabilitative treatments.

 

SOURCE: Hum Mov Sci. 2017 Sep 26. pii: S0167-9457(17)30089-1. doi: 10.1016/j.humov.2017.09.005. [Epub ahead of print] PMID: 28967438

 

Identification of specific gait patterns in patients with cerebellar ataxia, spastic paraplegia, and Parkinson’s disease: A non-hierarchical cluster analysis.

 

Serrao M1, Chini G2, Bergantino M3, Sarnari D3, Casali C4, Conte C5, Ranavolo A6, Marcotulli C4, Rinaldi M2, Coppola G7, Bini F3, Pierelli F8, Marinozzi F3.

 

1 Department of Medical and Surgical Sciences and Biotechnologies, Sapienza University of Rome, Corso della Repubblica 79, Latina 40100, Italy; Movement Analysis LAB, Rehabilitation Centre Policlinico Italia, Piazza del Campidano 6, 00162 Rome, Italy. Electronic address: [email protected]

2 Movement Analysis LAB, Rehabilitation Centre Policlinico Italia, Piazza del Campidano 6, 00162 Rome, Italy; Biolab3, Department of Engineering, Roma TRE University, Via Vito Volterra 62, 00149 Roma, Italy.

3 Department of Mechanical and Aerospace Engineering, “Sapienza” University of Rome, Via Eudossiana 18, 00184 Roma, Italy.

4 Department of Medical and Surgical Sciences and Biotechnologies, Sapienza University of Rome, Corso della Repubblica 79, Latina 40100, Italy.

5 Fondazione Don Gnocchi Foundation, Milan, Italy.

6 INAIL, Department of Occupational and Environmental Medicine, Epidemiology and Hygiene, Via Fontana Candida 1, 00040 Monte Porzio Catone, Italy.

7 G.B. Bietti Foundation-IRCCS, Department of Neurophysiology of Vision and Neurophthalmology, Via Livenza 3, 00198 Rome, Italy.

8 Department of Medical and Surgical Sciences and Biotechnologies, Sapienza University of Rome, Corso della Repubblica 79, Latina 40100, Italy; IRCCS Neuromed, Pozzilli (IS), Italy.

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