Mobile digital gait analysis captures effects of botulinum toxin in hereditary spastic paraplegia

Author:

Ibrahim Alzhraa A.123,Ollenschläger Malte12,Klebe Stephan4,Schüle Rebecca567,Jeschonneck Nicole4,Kellner Melanie56,Loris Evelyn1,Greinwalder Teresa1,Eskofier Bjoern M.2,Winkler Jürgen18,Gaßner Heiko19ORCID,Regensburger Martin1810ORCID

Affiliation:

1. Department of Molecular Neurology Friedrich‐Alexander‐Universität Erlangen‐Nürnberg Erlangen Germany

2. Machine Learning and Data Analytics Lab, Department of Artificial Intelligence in Biomedical Engineering Friedrich‐Alexander‐Universität Erlangen‐Nürnberg Erlangen Germany

3. Computer Science Department, Faculty of Computers and Information Assiut University Assiut Egypt

4. Department of Neurology University Hospital Essen Essen Germany

5. Department of Neurodegenerative Diseases, Hertie Institute for Clinical Brain Research and Center of Neurology University of Tübingen Tübingen Germany

6. German Center for Neurodegenerative Diseases Tübingen Germany

7. Division of Neurodegenerative Diseases, Department of Neurology, Faculty of Medicine Heidelberg University Hospital Heidelberg Germany

8. Center for Rare Diseases Erlangen Universitätsklinikum Erlangen Erlangen Germany

9. Fraunhofer Institute for Integrated Circuits IIS Erlangen Germany

10. Deutsches Zentrum Immuntherapie University Hospital Erlangen Erlangen Germany

Abstract

AbstractBackground and purposeHereditary spastic paraplegias (HSPs) comprise a group of inherited neurodegenerative disorders characterized by progressive spasticity and weakness. Botulinum toxin has been approved for lower limb spasticity following stroke and cerebral palsy, but its effects in HSPs remain underexplored. We aimed to characterize the effects of botulinum toxin on clinical, gait, and patient‐reported outcomes in HSP patients and explore the potential of mobile digital gait analysis to monitor treatment effects and predict treatment response.MethodsWe conducted a prospective, observational, multicenter study involving ambulatory HSP patients treated with botulinum toxin tailored to individual goals. Comparing data at baseline, after 1 month, and after 3 months, treatment response was assessed using clinical parameters, goal attainment scaling, and mobile digital gait analysis. Machine learning algorithms were used for predicting individual goal attainment based on baseline parameters.ResultsA total of 56 patients were enrolled. Despite the heterogeneity of treatment goals and targeted muscles, botulinum toxin led to a significant improvement in specific clinical parameters and an improvement in specific gait characteristics, peaking at the 1‐month and declining by the 3‐month follow‐up. Significant correlations were identified between gait parameters and clinical scores. With a mean balanced accuracy of 66%, machine learning algorithms identified important denominators to predict treatment response.ConclusionsOur study provides evidence supporting the beneficial effects of botulinum toxin in HSP when applied according to individual treatment goals. The use of mobile digital gait analysis and machine learning represents a novel approach for monitoring treatment effects and predicting treatment response.

Funder

Deutsche Forschungsgemeinschaft

Bundesministerium für Bildung und Forschung

Else Kröner-Fresenius-Stiftung

Forschungsstiftung Medizin am Universitätsklinikum Erlangen

Publisher

Wiley

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