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Ilg W, Milne S, Schmitz-Hübsch T, Alcock L, Beichert L, Bertini E, Mohamed Ibrahim N, Dawes H, Gomez CM, Hanagasi H, Kinnunen KM, Minnerop M, Németh AH, Newman J, Ng YS, Rentz C, Samanci B, Shah VV, Summa S, Vasco G, McNames J, Horak FB. Quantitative Gait and Balance Outcomes for Ataxia Trials: Consensus Recommendations by the Ataxia Global Initiative Working Group on Digital-Motor Biomarkers. CEREBELLUM (LONDON, ENGLAND) 2024; 23:1566-1592. [PMID: 37955812 PMCID: PMC11269489 DOI: 10.1007/s12311-023-01625-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 10/20/2023] [Indexed: 11/14/2023]
Abstract
With disease-modifying drugs on the horizon for degenerative ataxias, ecologically valid, finely granulated, digital health measures are highly warranted to augment clinical and patient-reported outcome measures. Gait and balance disturbances most often present as the first signs of degenerative cerebellar ataxia and are the most reported disabling features in disease progression. Thus, digital gait and balance measures constitute promising and relevant performance outcomes for clinical trials.This narrative review with embedded consensus will describe evidence for the sensitivity of digital gait and balance measures for evaluating ataxia severity and progression, propose a consensus protocol for establishing gait and balance metrics in natural history studies and clinical trials, and discuss relevant issues for their use as performance outcomes.
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Affiliation(s)
- Winfried Ilg
- Section Computational Sensomotorics, Hertie Institute for Clinical Brain Research, Otfried-Müller-Straße 25, 72076, Tübingen, Germany.
- Centre for Integrative Neuroscience (CIN), Tübingen, Germany.
| | - Sarah Milne
- Bruce Lefroy Centre for Genetic Health Research, Murdoch Children's Research Institute, Parkville, VIC, Australia
- Department of Paediatrics, Melbourne University, Melbourne, VIC, Australia
- Physiotherapy Department, Monash Health, Clayton, VIC, Australia
- School of Primary and Allied Health Care, Monash University, Frankston, VIC, Australia
| | - Tanja Schmitz-Hübsch
- Experimental and Clinical Research Center, a cooperation of Max-Delbrueck Center for Molecular Medicine and Charité, Universitätsmedizin Berlin, Berlin, Germany
- Neuroscience Clinical Research Center, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Lisa Alcock
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK
- NIHR Newcastle Biomedical Research Centre, Newcastle University, Newcastle upon Tyne, UK
| | - Lukas Beichert
- Department of Neurodegenerative Diseases and Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Enrico Bertini
- Research Unit of Neuromuscular and Neurodegenerative Disorders, Bambino Gesu' Children's Research Hospital, IRCCS, Rome, Italy
| | | | - Helen Dawes
- NIHR Exeter BRC, College of Medicine and Health, University of Exeter, Exeter, UK
| | | | - Hasmet Hanagasi
- Behavioral Neurology and Movement Disorders Unit, Department of Neurology, Istanbul Faculty of Medicine, Istanbul University, Istanbul, Turkey
| | | | - Martina Minnerop
- Institute of Neuroscience and Medicine (INM-1)), Research Centre Juelich, Juelich, Germany
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty & University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Department of Neurology, Center for Movement Disorders and Neuromodulation, Medical Faculty & University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Andrea H Németh
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Jane Newman
- NIHR Newcastle Biomedical Research Centre, Newcastle University, Newcastle upon Tyne, UK
- Wellcome Centre for Mitochondrial Research, Newcastle University, Newcastle upon Tyne, UK
| | - Yi Shiau Ng
- Wellcome Centre for Mitochondrial Research, Newcastle University, Newcastle upon Tyne, UK
| | - Clara Rentz
- Institute of Neuroscience and Medicine (INM-1)), Research Centre Juelich, Juelich, Germany
| | - Bedia Samanci
- Behavioral Neurology and Movement Disorders Unit, Department of Neurology, Istanbul Faculty of Medicine, Istanbul University, Istanbul, Turkey
| | - Vrutangkumar V Shah
- Department of Neurology, Oregon Health & Science University, Portland, OR, USA
- APDM Precision Motion, Clario, Portland, OR, USA
| | - Susanna Summa
- Movement Analysis and Robotics Laboratory (MARLab), Neurorehabilitation Unit, Neurological Science and Neurorehabilitation Area, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy
| | - Gessica Vasco
- Movement Analysis and Robotics Laboratory (MARLab), Neurorehabilitation Unit, Neurological Science and Neurorehabilitation Area, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy
| | - James McNames
- APDM Precision Motion, Clario, Portland, OR, USA
- Department of Electrical and Computer Engineering, Portland State University, Portland, OR, USA
| | - Fay B Horak
- Department of Neurology, Oregon Health & Science University, Portland, OR, USA
- APDM Precision Motion, Clario, Portland, OR, USA
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Klockgether T, Synofzik M. Consensus Recommendations for Clinical Outcome Assessments and Registry Development in Ataxias: Ataxia Global Initiative (AGI) Working Group Expert Guidance. CEREBELLUM (LONDON, ENGLAND) 2024; 23:924-930. [PMID: 37020147 PMCID: PMC11102398 DOI: 10.1007/s12311-023-01547-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 03/13/2023] [Indexed: 04/07/2023]
Abstract
To accelerate and facilitate clinical trials, the Ataxia Global Initiative (AGI) was established as a worldwide research platform for trial readiness in ataxias. One of AGI's major goals is the harmonization and standardization of outcome assessments. Clinical outcome assessments (COAs) that describe or reflect how a patient feels or functions are indispensable for clinical trials, but similarly important for observational studies and in routine patient care. The AGI working group on COAs has defined a set of data including a graded catalog of COAs that are recommended as a standard for future assessment and sharing of clinical data and joint clinical studies. Two datasets were defined: a mandatory dataset (minimal dataset) that can ideally be obtained during a routine clinical consultation and a more demanding extended dataset that is useful for research purposes. In the future, the currently most widely used clinician-reported outcome measure (ClinRO) in ataxia, the scale for the assessment and rating of ataxia (SARA), should be developed into a generally accepted instrument that can be used in upcoming clinical trials. Furthermore, there is an urgent need (i) to obtain more data on ataxia-specific, patient-reported outcome measures (PROs), (ii) to demonstrate and optimize sensitivity to change of many COAs, and (iii) to establish methods and evidence of anchoring change in COAs in patient meaningfulness, e.g., by determining patient-derived minimally meaningful thresholds of change.
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Affiliation(s)
- Thomas Klockgether
- Department of Neurology, University Hospital Bonn, Bonn, Germany.
- German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus, 53127, Bonn, Germany.
- Division Translational Genomics of Neurodegenerative Diseases, Center for Neurology, Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany.
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany.
| | - Matthis Synofzik
- German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus, 53127, Bonn, Germany
- Division Translational Genomics of Neurodegenerative Diseases, Center for Neurology, Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
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3
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Seemann J, Daghsen L, Cazier M, Lamy JC, Welter ML, Giese MA, Synofzik M, Durr A, Ilg W, Coarelli G. Digital Gait Measures Capture 1-Year Progression in Early-Stage Spinocerebellar Ataxia Type 2. Mov Disord 2024; 39:788-797. [PMID: 38419144 DOI: 10.1002/mds.29757] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Revised: 01/29/2024] [Accepted: 02/02/2024] [Indexed: 03/02/2024] Open
Abstract
BACKGROUND With disease-modifying drugs in reach for cerebellar ataxias, fine-grained digital health measures are highly warranted to complement clinical and patient-reported outcome measures in upcoming treatment trials and treatment monitoring. These measures need to demonstrate sensitivity to capture change, in particular in the early stages of the disease. OBJECTIVE Our aim is to unravel gait measures sensitive to longitudinal change in the-particularly trial-relevant-early stage of spinocerebellar ataxia type 2 (SCA2). METHODS We performed a multicenter longitudinal study with combined cross-sectional and 1-year interval longitudinal analysis in early-stage SCA2 participants (n = 23, including nine pre-ataxic expansion carriers; median, ATXN2 CAG repeat expansion 38 ± 2; median, Scale for the Assessment and Rating of Ataxia [SARA] score 4.8 ± 4.3). Gait was assessed using three wearable motion sensors during a 2-minute walk, with analyses focused on gait measures of spatio-temporal variability that have shown sensitivity to ataxia severity (eg, lateral step deviation). RESULTS We found significant changes for gait measures between baseline and 1-year follow-up with large effect sizes (lateral step deviation P = 0.0001, effect size rprb = 0.78), whereas the SARA score showed no change (P = 0.67). Sample size estimation indicates a required cohort size of n = 43 to detect a 50% reduction in natural progression. Test-retest reliability and minimal detectable change analysis confirm the accuracy of detecting 50% of the identified 1-year change. CONCLUSIONS Gait measures assessed by wearable sensors can capture natural progression in early-stage SCA2 within just 1 year-in contrast to a clinical ataxia outcome. Lateral step deviation represents a promising outcome measure for upcoming multicenter interventional trials, particularly in the early stages of cerebellar ataxia. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Jens Seemann
- Section Computational Sensomotorics, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
- Centre for Integrative Neuroscience (CIN), Tübingen, Germany
| | - Lina Daghsen
- Sorbonne Université, Paris Brain Institute-ICM, Inserm, CNRS, AP-HP, Paris, France
| | - Matthieu Cazier
- Sorbonne Université, Paris Brain Institute-ICM, Inserm, CNRS, AP-HP, Paris, France
| | - Jean-Charles Lamy
- Sorbonne Université, Paris Brain Institute-ICM, Inserm, CNRS, AP-HP, Paris, France
| | - Marie-Laure Welter
- Sorbonne Université, Paris Brain Institute-ICM, Inserm, CNRS, AP-HP, Paris, France
| | - Martin A Giese
- Section Computational Sensomotorics, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
- Centre for Integrative Neuroscience (CIN), Tübingen, Germany
| | - Matthis Synofzik
- Division Translational Genomics of Neurodegenerative Diseases, Hertie-Institute for Clinical Brain Research and Center of Neurology, University of Tübingen, Tübingen, Germany
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
| | - Alexandra Durr
- Sorbonne Université, Paris Brain Institute-ICM, Inserm, CNRS, AP-HP, Paris, France
| | - Winfried Ilg
- Section Computational Sensomotorics, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
- Centre for Integrative Neuroscience (CIN), Tübingen, Germany
| | - Giulia Coarelli
- Sorbonne Université, Paris Brain Institute-ICM, Inserm, CNRS, AP-HP, Paris, France
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4
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Milne SC, Kim SH, Murphy A, Larkindale J, Farmer J, Malapira R, Danoudis M, Shaw J, Ramakrishnan T, Rasouli F, Yiu EM, Georgiou-Karistianis N, Tai G, Zesiewicz T, Delatycki MB, Corben LA. The Responsiveness of Gait and Balance Outcomes to Disease Progression in Friedreich Ataxia. CEREBELLUM (LONDON, ENGLAND) 2022; 21:963-975. [PMID: 34855135 DOI: 10.1007/s12311-021-01348-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 11/17/2021] [Indexed: 06/13/2023]
Abstract
To identify gait and balance measures that are responsive to change during the timeline of a clinical trial in Friedreich ataxia (FRDA), we administered a battery of potential measures three times over a 12-month period. Sixty-one ambulant individuals with FRDA underwent assessment of gait and balance at baseline, 6 months and 12 months. Outcomes included GAITRite® spatiotemporal gait parameters; Biodex Balance System Postural Stability Test (PST) and Limits of Stability; Berg Balance Scale (BBS); Timed 25-Foot Walk Test; Dynamic Gait Index (DGI); SenseWear MF Armband step and energy activity; and the Friedreich Ataxia Rating Scale Upright Stability Subscale (FARS USS). The standardised response mean (SRM) or correlation coefficients were reported as effect size indices for comparison of internal responsiveness. Internal responsiveness was also analysed in subgroups. SenseWear Armband daily step count had the largest effect size of all the variables over 6 months (SRM = -0.615), while the PST medial-lateral index had the largest effect size (SRM = 0.829) over 12 months. The FARS USS (SRM = 0.824) and BBS (SRM = -0.720) were the only outcomes able to detect change over 12 months in all subgroups. The DGI was the most responsive outcome in children, detecting a mean change of -2.59 (95% CI -3.52 to -1.66, p < 0.001, SRM = -1.429). In conclusion, the FARS USS and BBS are highly responsive and can detect change in a wide range of ambulant individuals with FRDA. However, therapeutic effects in children may be best measured by the DGI.
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Affiliation(s)
- Sarah C Milne
- Bruce Lefroy Centre, Murdoch Children's Research Institute, Melbourne,, Australia.
- Physiotherapy Department, Monash Health, Melbourne, Australia.
- Monash Institute of Cognitive and Clinical Neurosciences, Monash University, Melbourne, Australia.
- Department of Paediatrics, The University of Melbourne, Melbourne, Australia.
- School of Primary and Allied Health Care, Monash University, Melbourne, Australia.
| | | | - Anna Murphy
- MonARC, Monash Health, Melbourne, Australia
- School of Public Health and Preventative Medicine, Monash University, Melbourne, Australia
| | | | | | | | - Mary Danoudis
- MonARC, Monash Health, Melbourne, Australia
- School of Public Health and Preventative Medicine, Monash University, Melbourne, Australia
| | | | | | | | - Eppie M Yiu
- Bruce Lefroy Centre, Murdoch Children's Research Institute, Melbourne,, Australia
- Department of Paediatrics, The University of Melbourne, Melbourne, Australia
- Department of Neurology, The Royal Children's Hospital Melbourne, Melbourne, Australia
| | - Nellie Georgiou-Karistianis
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Australia
| | - Geneieve Tai
- Bruce Lefroy Centre, Murdoch Children's Research Institute, Melbourne,, Australia
| | | | - Martin B Delatycki
- Bruce Lefroy Centre, Murdoch Children's Research Institute, Melbourne,, Australia
- Department of Paediatrics, The University of Melbourne, Melbourne, Australia
- Victorian Clinical Genetics Services, Melbourne, Australia
| | - Louise A Corben
- Bruce Lefroy Centre, Murdoch Children's Research Institute, Melbourne,, Australia
- Department of Paediatrics, The University of Melbourne, Melbourne, Australia
- School of Primary and Allied Health Care, Monash University, Melbourne, Australia
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5
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Cabaraux P, Agrawal SK, Cai H, Calabro RS, Casali C, Damm L, Doss S, Habas C, Horn AKE, Ilg W, Louis ED, Mitoma H, Monaco V, Petracca M, Ranavolo A, Rao AK, Ruggieri S, Schirinzi T, Serrao M, Summa S, Strupp M, Surgent O, Synofzik M, Tao S, Terasi H, Torres-Russotto D, Travers B, Roper JA, Manto M. Consensus Paper: Ataxic Gait. CEREBELLUM (LONDON, ENGLAND) 2022; 22:394-430. [PMID: 35414041 DOI: 10.1007/s12311-022-01373-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 01/20/2022] [Indexed: 12/19/2022]
Abstract
The aim of this consensus paper is to discuss the roles of the cerebellum in human gait, as well as its assessment and therapy. Cerebellar vermis is critical for postural control. The cerebellum ensures the mapping of sensory information into temporally relevant motor commands. Mental imagery of gait involves intrinsically connected fronto-parietal networks comprising the cerebellum. Muscular activities in cerebellar patients show impaired timing of discharges, affecting the patterning of the synergies subserving locomotion. Ataxia of stance/gait is amongst the first cerebellar deficits in cerebellar disorders such as degenerative ataxias and is a disabling symptom with a high risk of falls. Prolonged discharges and increased muscle coactivation may be related to compensatory mechanisms and enhanced body sway, respectively. Essential tremor is frequently associated with mild gait ataxia. There is growing evidence for an important role of the cerebellar cortex in the pathogenesis of essential tremor. In multiple sclerosis, balance and gait are affected due to cerebellar and spinal cord involvement, as a result of disseminated demyelination and neurodegeneration impairing proprioception. In orthostatic tremor, patients often show mild-to-moderate limb and gait ataxia. The tremor generator is likely located in the posterior fossa. Tandem gait is impaired in the early stages of cerebellar disorders and may be particularly useful in the evaluation of pre-ataxic stages of progressive ataxias. Impaired inter-joint coordination and enhanced variability of gait temporal and kinetic parameters can be grasped by wearable devices such as accelerometers. Kinect is a promising low cost technology to obtain reliable measurements and remote assessments of gait. Deep learning methods are being developed in order to help clinicians in the diagnosis and decision-making process. Locomotor adaptation is impaired in cerebellar patients. Coordinative training aims to improve the coordinative strategy and foot placements across strides, cerebellar patients benefiting from intense rehabilitation therapies. Robotic training is a promising approach to complement conventional rehabilitation and neuromodulation of the cerebellum. Wearable dynamic orthoses represent a potential aid to assist gait. The panel of experts agree that the understanding of the cerebellar contribution to gait control will lead to a better management of cerebellar ataxias in general and will likely contribute to use gait parameters as robust biomarkers of future clinical trials.
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Affiliation(s)
- Pierre Cabaraux
- Unité Des Ataxies Cérébelleuses, Department of Neurology, CHU de Charleroi, Charleroi, Belgium.
| | | | - Huaying Cai
- Department of Neurology, Neuroscience Center, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, 310016, China
| | | | - Carlo Casali
- Department of Medico-Surgical Sciences and Biotechnologies, University of Rome Sapienza, Latina, Italy
| | - Loic Damm
- EuroMov Digital Health in Motion, Univ Montpellier, IMT Mines Ales, Montpellier, France
| | - Sarah Doss
- Department of Neurological Sciences, University of Nebraska Medical Center, Omaha, USA
| | - Christophe Habas
- Université Versailles Saint-Quentin, Versailles, France.,Service de NeuroImagerie, Centre Hospitalier National des 15-20, Paris, France
| | - Anja K E Horn
- Institute of Anatomy and Cell Biology I, Ludwig Maximilians-University Munich, Munich, Germany
| | - Winfried Ilg
- Section Computational Sensomotorics, Hertie Institute for Clinical Brain Research, University Tübingen, Tübingen, Germany
| | - Elan D Louis
- Department of Neurology, University of Texas Southwestern, Dallas, TX, USA
| | - Hiroshi Mitoma
- Department of Medical Education, Tokyo Medical University, Tokyo, Japan
| | - Vito Monaco
- The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Maria Petracca
- Department of Human Neurosciences, University of Rome Sapienza, Rome, Italy
| | - Alberto Ranavolo
- Department of Occupational and Environmental Medicine, Epidemiology and Hygiene, INAIL, Monte Porzio Catone, Rome, Italy
| | - Ashwini K Rao
- Department of Rehabilitation & Regenerative Medicine (Programs in Physical Therapy), Gertrude H. Sergievsky Center, College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Serena Ruggieri
- Department of Human Neurosciences, University of Rome Sapienza, Rome, Italy.,Neuroimmunology Unit, IRCSS Fondazione Santa Lucia, Rome, Italy
| | - Tommaso Schirinzi
- Department of Systems Medicine, University of Roma Tor Vergata, Rome, Italy
| | - Mariano Serrao
- Department of Medico-Surgical Sciences and Biotechnologies, University of Rome Sapienza, Latina, Italy.,Movement Analysis LAB, Policlinico Italia, Rome, Italy
| | - Susanna Summa
- MARlab, Neuroscience and Neurorehabilitation Department, Bambino Gesù Children's Hospital - IRCCS, Rome, Italy
| | - Michael Strupp
- Department of Neurology and German Center for Vertigo and Balance Disorders, Hospital of the Ludwig Maximilians-University Munich, Munich, Germany
| | - Olivia Surgent
- Neuroscience Training Program and Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - Matthis Synofzik
- Department of Neurodegeneration, Hertie Institute for Clinical Brain Research and Centre of Neurology, Tübingen, Germany
| | - Shuai Tao
- Dalian Key Laboratory of Smart Medical and Health, Dalian University, Dalian, 116622, China
| | - Hiroo Terasi
- Department of Neurology, Tokyo Medical University, Tokyo, Japan
| | - Diego Torres-Russotto
- Department of Neurological Sciences, University of Nebraska Medical Center, Omaha, USA
| | - Brittany Travers
- Department of Kinesiology and Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - Jaimie A Roper
- School of Kinesiology, Auburn University, Auburn, AL, USA
| | - Mario Manto
- Unité Des Ataxies Cérébelleuses, Department of Neurology, CHU de Charleroi, Charleroi, Belgium.,Service Des Neurosciences, University of Mons, UMons, Mons, Belgium
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Shah VV, Rodriguez-Labrada R, Horak FB, McNames J, Casey H, Hansson Floyd K, El-Gohary M, Schmahmann JD, Rosenthal LS, Perlman S, Velázquez-Pérez L, Gomez CM. Gait Variability in Spinocerebellar Ataxia Assessed Using Wearable Inertial Sensors. Mov Disord 2021; 36:2922-2931. [PMID: 34424581 DOI: 10.1002/mds.28740] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 07/13/2021] [Accepted: 07/14/2021] [Indexed: 01/07/2023] Open
Abstract
BACKGROUND Quantitative assessment of severity of ataxia-specific gait impairments from wearable technology could provide sensitive performance outcome measures with high face validity to power clinical trials. OBJECTIVES The aim of this study was to identify a set of gait measures from body-worn inertial sensors that best discriminate between people with prodromal or manifest spinocerebellar ataxia (SCA) and age-matched, healthy control subjects (HC) and determine how these measures relate to disease severity. METHODS One hundred and sixty-three people with SCA (subtypes 1, 2, 3, and 6), 42 people with prodromal SCA, and 96 HC wore 6 inertial sensors while performing a natural pace, 2-minute walk. Areas under the receiver operating characteristic curves (AUC) were compared for 25 gait measures, including standard deviations as variability, to discriminate between ataxic and normal gait. Pearson's correlation coefficient assessed the relationships between the gait measures and severity of ataxia. RESULTS Increased gait variability was the most discriminative gait feature of SCA; toe-out angle variability (AUC = 0.936; sensitivity = 0.871; specificity = 0.896) and double-support time variability (AUC = 0.932; sensitivity = 0.834; specificity = 0.865) were the most sensitive and specific measures. These variability measures were also significantly correlated with the scale for the assessment and rating of ataxia (SARA) and disease duration. The same gait measures discriminated gait of people with prodromal SCA from the gait of HC (AUC = 0.610, and 0.670, respectively). CONCLUSIONS Wearable inertial sensors provide sensitive and specific measures of excessive gait variability in both manifest and prodromal SCAs that are reliable and related to the severity of the disease, suggesting they may be useful as clinical trial performance outcome measures. © 2021 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Vrutangkumar V Shah
- Department of Neurology, Oregon Health & Science University, Portland, Oregon, USA
| | - Roberto Rodriguez-Labrada
- Centre for the Research and Rehabilitation of Hereditary Ataxias, Holguín, Cuba.,Cuban Center for Neuroscience, Havana, Cuba
| | - Fay B Horak
- Department of Neurology, Oregon Health & Science University, Portland, Oregon, USA.,APDM Wearable Technologies, an ERT company, Portland, Oregon, USA
| | - James McNames
- APDM Wearable Technologies, an ERT company, Portland, Oregon, USA.,Department of Electrical and Computer Engineering, Portland State University, Portland, Oregon, USA
| | - Hannah Casey
- The University of Chicago, Chicago, Illinois, USA
| | | | | | - Jeremy D Schmahmann
- Department of Neurology, Ataxia Center, Laboratory for Neuroanatomy and Cerebellar Neurobiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Liana S Rosenthal
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Susan Perlman
- Department of Neurology, University of California, Los Angeles, California, USA
| | - Luis Velázquez-Pérez
- Centre for the Research and Rehabilitation of Hereditary Ataxias, Holguín, Cuba.,Cuban Academy of Sciences, La Habana, Cuba
| | - Christopher M Gomez
- Department of Neurology, Oregon Health & Science University, Portland, Oregon, USA.,The University of Chicago, Chicago, Illinois, USA
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7
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Mueller A, Paterson E, McIntosh A, Praestgaard J, Bylo M, Hoefling H, Wells M, Lynch DR, Rummey C, Krishnan ML, Schultz M, Malanga CJ. Digital endpoints for self-administered home-based functional assessment in pediatric Friedreich's ataxia. Ann Clin Transl Neurol 2021; 8:1845-1856. [PMID: 34355532 PMCID: PMC8419399 DOI: 10.1002/acn3.51438] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Revised: 07/16/2021] [Accepted: 07/17/2021] [Indexed: 01/18/2023] Open
Abstract
Background Friedreich’s ataxia is an inherited, progressive, neurodegenerative disease that typically begins in childhood. Disease severity is commonly assessed with rating scales, such as the modified Friedreich’s Ataxia Rating Scale, which are usually administered in the clinic by a neurology specialist. Objective This study evaluated the utility of home‐based, self‐administered digital endpoints in children with Friedreich’s ataxia and unaffected controls and their relationship to standard clinical rating scales. Methods In a cross‐sectional study with 25 participants (13 with Friedreich’s ataxia and 12 unaffected controls, aged 6–15 years), home‐based digital endpoints that reflect activities of daily living were recorded over 1 week. Domains analyzed were hand motor function with a digitized drawing, automated analysis of speech with a recorded oral diadochokinesis test, and gait and balance with wearable sensors. Results Hand‐drawing and speech tests were easy to conduct and generated high‐quality data. The sensor‐based gait and balance tests suffered from technical limitations in this study setup. Several parameters discriminated between groups or correlated strongly with modified Friedreich’s Ataxia Rating Scale total score and activities of daily living total score in the Friedreich’s ataxia group. Hand‐drawing parameters also strongly correlated with standard 9‐hole peg test scores. Interpretation Deploying digital endpoints in home settings is feasible in this population, results in meaningful and robust data collection, and may allow for frequent sampling over longer periods of time to track disease progression. Care must be taken when training participants, and investigators should consider the complexity of the tasks and equipment used.
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Affiliation(s)
- Arne Mueller
- Translational Medicine, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - Elaine Paterson
- Translational Medicine, Novartis Institutes for BioMedical Research, Cambridge, Massachusetts, USA
| | | | | | - Mary Bylo
- Translational Medicine, Novartis Institutes for BioMedical Research, Cambridge, Massachusetts, USA
| | - Holger Hoefling
- NIBR Informatics, Novartis Institute of Biomedical Research, Basel, Switzerland
| | - McKenzie Wells
- Division of Neurology, Departments of Neurology and Pediatrics, Children's Hospital of Philadelphia, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, USA
| | - David R Lynch
- Division of Neurology, Departments of Neurology and Pediatrics, Children's Hospital of Philadelphia, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, USA
| | | | - Michelle L Krishnan
- Translational Medicine, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - Meredith Schultz
- Translational Medicine, Novartis Institutes for BioMedical Research, Cambridge, Massachusetts, USA
| | - C J Malanga
- Translational Medicine, Novartis Institutes for BioMedical Research, Cambridge, Massachusetts, USA
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Ilg W, Seemann J, Giese M, Traschütz A, Schöls L, Timmann D, Synofzik M. Real-life gait assessment in degenerative cerebellar ataxia. Neurology 2020; 95:e1199-e1210. [DOI: 10.1212/wnl.0000000000010176] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2019] [Accepted: 03/02/2020] [Indexed: 01/01/2023] Open
Abstract
ObjectivesWith disease-modifying drugs on the horizon for degenerative ataxias, ecologically valid motor biomarkers are highly warranted. In this observational study, we aimed to unravel and validate markers of ataxic gait in real life by using wearable sensors.MethodsWe assessed gait characteristics of 43 patients with degenerative cerebellar disease (Scale for the Assessment and Rating of Ataxia [SARA] 9.4 ± 3.9) compared with 35 controls by 3 body-worn inertial sensors in 3 conditions: (1) laboratory-based walking; (2) supervised free walking; (3) real-life walking during everyday living (subgroup n = 21). Movement analysis focused on measures of spatiotemporal step variability and movement smoothness.ResultsA set of gait variability measures was identified that allowed us to consistently identify ataxic gait changes in all 3 conditions. Lateral step deviation and a compound measure of spatial step variability categorized patients vs controls with a discrimination accuracy of 0.86 in real life. Both were highly correlated with clinical ataxia severity (effect size ρ = 0.76). These measures allowed detecting group differences even for patients who differed only 1 point in the clinical SARAposture&gait subscore, with highest effect sizes for real-life walking (d = 0.67).ConclusionsWe identified measures of ataxic gait that allowed us not only to capture the gait variability inherent in ataxic gait in real life, but also to demonstrate high sensitivity to small differences in disease severity, with the highest effect sizes in real-life walking. They thus represent promising candidates for motor markers for natural history and treatment trials in ecologically valid contexts.Classification of evidenceThis study provides Class I evidence that a set of gait variability measures, even if accessed in real life, correlated with the clinical severity of ataxia in patients with degenerative cerebellar disease.
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Developing a smartphone application, triaxial accelerometer-based, to quantify static and dynamic balance deficits in patients with cerebellar ataxias. J Neurol 2019; 267:625-639. [PMID: 31713101 DOI: 10.1007/s00415-019-09570-z] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2019] [Revised: 10/03/2019] [Accepted: 10/09/2019] [Indexed: 12/22/2022]
Abstract
BACKGROUND Cerebellar ataxia is characterized by difficulty in the planning of movement and lack of anticipatory postural adjustments, which can result in deficits of balance. Being able to have quantitative measurements in clinical practice, to detect any improvements on balance resulting from new rehabilitation treatments or experimental drugs is very important. AIM The purpose of this study was to develop an application (APP) able to assess static and dynamic balance in patients with cerebellar ataxias (CA). The APP that works by a wearable device (smartphone) placed at the breastbone level and immobilized by an elastic band, measures the body sway by means of a triaxial accelerometer. METHODS We investigated 40 CA patients and 80 healthy subjects. All patients were clinically evaluated using the "Berg Balance Scale" (BBS) and the "Scale for the Assessment and Rating of Ataxia" (SARA). Balance impairment was quantitatively assessed using a validated static balance evaluating systems, i.e., Techno-body Pro-Kin footboard. All participants underwent static and dynamic balance assessments using the new APP. RESULTS We observed a strong correlation between the APP measurements and the score obtained with the BBS, SARA, and Pro-Kin footboard. The intra-rater reliability and the test-retest reliability of the APP measurements, estimated by intraclass correlation coefficient, were excellent. The standard error of measurement and the minimal detectable change were small. No learning effect was observed. CONCLUSIONS We can state that the APP is an easy, reliable, and valid evaluating system to quantify the trunk sway in a static position and during the gait.
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Rummey C, Corben LA, Delatycki MB, Subramony SH, Bushara K, Gomez CM, Hoyle JC, Yoon G, Ravina B, Mathews KD, Wilmot G, Zesiewicz T, Perlman S, Farmer JM, Lynch DR. Psychometric properties of the Friedreich Ataxia Rating Scale. NEUROLOGY-GENETICS 2019; 5:371. [PMID: 32042904 PMCID: PMC6927357 DOI: 10.1212/nxg.0000000000000371] [Citation(s) in RCA: 48] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/07/2019] [Accepted: 09/23/2019] [Indexed: 11/18/2022]
Abstract
Objective To investigate the psychometric properties of the Friedreich Ataxia Rating Scale neurologic examination (FARSn) and its subscores, as well as the influence of the modifications resulting in the now widely used modified FARS (mFARS) examination. Methods Based on cross-sectional FARS data from the FA–Clinical Outcome Measures cohort, we conducted correlation-based psychometric analyses to investigate the interplay of items and subscores within the FARSn/mFARS constructs. Results The results provide support for both the FARSn and the mFARS constructs, as well as individually for their upper limb and lower limb coordination components. The omission of the peripheral nervous system subscore (D) and 2 items of the bulbar subscore (A) in the mFARS strengthens the overall construct compared with the complete FARS. Conclusions A correlation-based psychometric analysis of the neurologic FARSn score justifies the overall validity of the scale. In addition, omission of items of limited functional significance as created in the mFARS improves the features of the measures. Such information is crucial to the ongoing application of the mFARS in natural history studies and clinical trials. Additional analyses of longitudinal changes will be necessary to fully ascertain its utility, especially in nonambulant patients.
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Affiliation(s)
- Christian Rummey
- Clinical Data Science GmbH (C.R.), Basel, Switzerland; Bruce Lefroy Centre for Genetic Health Research (L.A.C., M.B.D.), Murdoch Children's Research Institute, Parkville, Victoria, Australia; Department of Paediatrics (L.A.C., M.B.D.), University of Melbourne, Parkville, Victoria, Australia; Department of Neurology (S.H.S.), McKnight Brain Institute, Room, Gainesville, FL; University of Minnesota (K.B.); University of Chicago (C.M.G.); Ohio State University (J.C.H.); Divisions of Neurology and Clinical and Metabolic Genetics (G.Y.), Department of Paediatrics, the Hospital for Sick Children, University of Toronto, Ontario, Canada Hospital; University of Rochester (B.R.); University of Iowa (K.D.M.); Emory University (G.W.); University of South Florida (T.Z.); Friedreich's Ataxia Research Alliance (S.P.), Downingtown, PA; and Division of Neurology (D.R.L.), Children's Hospital of Philadelphia
| | - Louise A Corben
- Clinical Data Science GmbH (C.R.), Basel, Switzerland; Bruce Lefroy Centre for Genetic Health Research (L.A.C., M.B.D.), Murdoch Children's Research Institute, Parkville, Victoria, Australia; Department of Paediatrics (L.A.C., M.B.D.), University of Melbourne, Parkville, Victoria, Australia; Department of Neurology (S.H.S.), McKnight Brain Institute, Room, Gainesville, FL; University of Minnesota (K.B.); University of Chicago (C.M.G.); Ohio State University (J.C.H.); Divisions of Neurology and Clinical and Metabolic Genetics (G.Y.), Department of Paediatrics, the Hospital for Sick Children, University of Toronto, Ontario, Canada Hospital; University of Rochester (B.R.); University of Iowa (K.D.M.); Emory University (G.W.); University of South Florida (T.Z.); Friedreich's Ataxia Research Alliance (S.P.), Downingtown, PA; and Division of Neurology (D.R.L.), Children's Hospital of Philadelphia
| | - Martin B Delatycki
- Clinical Data Science GmbH (C.R.), Basel, Switzerland; Bruce Lefroy Centre for Genetic Health Research (L.A.C., M.B.D.), Murdoch Children's Research Institute, Parkville, Victoria, Australia; Department of Paediatrics (L.A.C., M.B.D.), University of Melbourne, Parkville, Victoria, Australia; Department of Neurology (S.H.S.), McKnight Brain Institute, Room, Gainesville, FL; University of Minnesota (K.B.); University of Chicago (C.M.G.); Ohio State University (J.C.H.); Divisions of Neurology and Clinical and Metabolic Genetics (G.Y.), Department of Paediatrics, the Hospital for Sick Children, University of Toronto, Ontario, Canada Hospital; University of Rochester (B.R.); University of Iowa (K.D.M.); Emory University (G.W.); University of South Florida (T.Z.); Friedreich's Ataxia Research Alliance (S.P.), Downingtown, PA; and Division of Neurology (D.R.L.), Children's Hospital of Philadelphia
| | - S H Subramony
- Clinical Data Science GmbH (C.R.), Basel, Switzerland; Bruce Lefroy Centre for Genetic Health Research (L.A.C., M.B.D.), Murdoch Children's Research Institute, Parkville, Victoria, Australia; Department of Paediatrics (L.A.C., M.B.D.), University of Melbourne, Parkville, Victoria, Australia; Department of Neurology (S.H.S.), McKnight Brain Institute, Room, Gainesville, FL; University of Minnesota (K.B.); University of Chicago (C.M.G.); Ohio State University (J.C.H.); Divisions of Neurology and Clinical and Metabolic Genetics (G.Y.), Department of Paediatrics, the Hospital for Sick Children, University of Toronto, Ontario, Canada Hospital; University of Rochester (B.R.); University of Iowa (K.D.M.); Emory University (G.W.); University of South Florida (T.Z.); Friedreich's Ataxia Research Alliance (S.P.), Downingtown, PA; and Division of Neurology (D.R.L.), Children's Hospital of Philadelphia
| | - Khalaf Bushara
- Clinical Data Science GmbH (C.R.), Basel, Switzerland; Bruce Lefroy Centre for Genetic Health Research (L.A.C., M.B.D.), Murdoch Children's Research Institute, Parkville, Victoria, Australia; Department of Paediatrics (L.A.C., M.B.D.), University of Melbourne, Parkville, Victoria, Australia; Department of Neurology (S.H.S.), McKnight Brain Institute, Room, Gainesville, FL; University of Minnesota (K.B.); University of Chicago (C.M.G.); Ohio State University (J.C.H.); Divisions of Neurology and Clinical and Metabolic Genetics (G.Y.), Department of Paediatrics, the Hospital for Sick Children, University of Toronto, Ontario, Canada Hospital; University of Rochester (B.R.); University of Iowa (K.D.M.); Emory University (G.W.); University of South Florida (T.Z.); Friedreich's Ataxia Research Alliance (S.P.), Downingtown, PA; and Division of Neurology (D.R.L.), Children's Hospital of Philadelphia
| | - Christopher M Gomez
- Clinical Data Science GmbH (C.R.), Basel, Switzerland; Bruce Lefroy Centre for Genetic Health Research (L.A.C., M.B.D.), Murdoch Children's Research Institute, Parkville, Victoria, Australia; Department of Paediatrics (L.A.C., M.B.D.), University of Melbourne, Parkville, Victoria, Australia; Department of Neurology (S.H.S.), McKnight Brain Institute, Room, Gainesville, FL; University of Minnesota (K.B.); University of Chicago (C.M.G.); Ohio State University (J.C.H.); Divisions of Neurology and Clinical and Metabolic Genetics (G.Y.), Department of Paediatrics, the Hospital for Sick Children, University of Toronto, Ontario, Canada Hospital; University of Rochester (B.R.); University of Iowa (K.D.M.); Emory University (G.W.); University of South Florida (T.Z.); Friedreich's Ataxia Research Alliance (S.P.), Downingtown, PA; and Division of Neurology (D.R.L.), Children's Hospital of Philadelphia
| | - Joseph Chad Hoyle
- Clinical Data Science GmbH (C.R.), Basel, Switzerland; Bruce Lefroy Centre for Genetic Health Research (L.A.C., M.B.D.), Murdoch Children's Research Institute, Parkville, Victoria, Australia; Department of Paediatrics (L.A.C., M.B.D.), University of Melbourne, Parkville, Victoria, Australia; Department of Neurology (S.H.S.), McKnight Brain Institute, Room, Gainesville, FL; University of Minnesota (K.B.); University of Chicago (C.M.G.); Ohio State University (J.C.H.); Divisions of Neurology and Clinical and Metabolic Genetics (G.Y.), Department of Paediatrics, the Hospital for Sick Children, University of Toronto, Ontario, Canada Hospital; University of Rochester (B.R.); University of Iowa (K.D.M.); Emory University (G.W.); University of South Florida (T.Z.); Friedreich's Ataxia Research Alliance (S.P.), Downingtown, PA; and Division of Neurology (D.R.L.), Children's Hospital of Philadelphia
| | - Grace Yoon
- Clinical Data Science GmbH (C.R.), Basel, Switzerland; Bruce Lefroy Centre for Genetic Health Research (L.A.C., M.B.D.), Murdoch Children's Research Institute, Parkville, Victoria, Australia; Department of Paediatrics (L.A.C., M.B.D.), University of Melbourne, Parkville, Victoria, Australia; Department of Neurology (S.H.S.), McKnight Brain Institute, Room, Gainesville, FL; University of Minnesota (K.B.); University of Chicago (C.M.G.); Ohio State University (J.C.H.); Divisions of Neurology and Clinical and Metabolic Genetics (G.Y.), Department of Paediatrics, the Hospital for Sick Children, University of Toronto, Ontario, Canada Hospital; University of Rochester (B.R.); University of Iowa (K.D.M.); Emory University (G.W.); University of South Florida (T.Z.); Friedreich's Ataxia Research Alliance (S.P.), Downingtown, PA; and Division of Neurology (D.R.L.), Children's Hospital of Philadelphia
| | - Bernard Ravina
- Clinical Data Science GmbH (C.R.), Basel, Switzerland; Bruce Lefroy Centre for Genetic Health Research (L.A.C., M.B.D.), Murdoch Children's Research Institute, Parkville, Victoria, Australia; Department of Paediatrics (L.A.C., M.B.D.), University of Melbourne, Parkville, Victoria, Australia; Department of Neurology (S.H.S.), McKnight Brain Institute, Room, Gainesville, FL; University of Minnesota (K.B.); University of Chicago (C.M.G.); Ohio State University (J.C.H.); Divisions of Neurology and Clinical and Metabolic Genetics (G.Y.), Department of Paediatrics, the Hospital for Sick Children, University of Toronto, Ontario, Canada Hospital; University of Rochester (B.R.); University of Iowa (K.D.M.); Emory University (G.W.); University of South Florida (T.Z.); Friedreich's Ataxia Research Alliance (S.P.), Downingtown, PA; and Division of Neurology (D.R.L.), Children's Hospital of Philadelphia
| | - Katherine D Mathews
- Clinical Data Science GmbH (C.R.), Basel, Switzerland; Bruce Lefroy Centre for Genetic Health Research (L.A.C., M.B.D.), Murdoch Children's Research Institute, Parkville, Victoria, Australia; Department of Paediatrics (L.A.C., M.B.D.), University of Melbourne, Parkville, Victoria, Australia; Department of Neurology (S.H.S.), McKnight Brain Institute, Room, Gainesville, FL; University of Minnesota (K.B.); University of Chicago (C.M.G.); Ohio State University (J.C.H.); Divisions of Neurology and Clinical and Metabolic Genetics (G.Y.), Department of Paediatrics, the Hospital for Sick Children, University of Toronto, Ontario, Canada Hospital; University of Rochester (B.R.); University of Iowa (K.D.M.); Emory University (G.W.); University of South Florida (T.Z.); Friedreich's Ataxia Research Alliance (S.P.), Downingtown, PA; and Division of Neurology (D.R.L.), Children's Hospital of Philadelphia
| | - George Wilmot
- Clinical Data Science GmbH (C.R.), Basel, Switzerland; Bruce Lefroy Centre for Genetic Health Research (L.A.C., M.B.D.), Murdoch Children's Research Institute, Parkville, Victoria, Australia; Department of Paediatrics (L.A.C., M.B.D.), University of Melbourne, Parkville, Victoria, Australia; Department of Neurology (S.H.S.), McKnight Brain Institute, Room, Gainesville, FL; University of Minnesota (K.B.); University of Chicago (C.M.G.); Ohio State University (J.C.H.); Divisions of Neurology and Clinical and Metabolic Genetics (G.Y.), Department of Paediatrics, the Hospital for Sick Children, University of Toronto, Ontario, Canada Hospital; University of Rochester (B.R.); University of Iowa (K.D.M.); Emory University (G.W.); University of South Florida (T.Z.); Friedreich's Ataxia Research Alliance (S.P.), Downingtown, PA; and Division of Neurology (D.R.L.), Children's Hospital of Philadelphia
| | - Theresa Zesiewicz
- Clinical Data Science GmbH (C.R.), Basel, Switzerland; Bruce Lefroy Centre for Genetic Health Research (L.A.C., M.B.D.), Murdoch Children's Research Institute, Parkville, Victoria, Australia; Department of Paediatrics (L.A.C., M.B.D.), University of Melbourne, Parkville, Victoria, Australia; Department of Neurology (S.H.S.), McKnight Brain Institute, Room, Gainesville, FL; University of Minnesota (K.B.); University of Chicago (C.M.G.); Ohio State University (J.C.H.); Divisions of Neurology and Clinical and Metabolic Genetics (G.Y.), Department of Paediatrics, the Hospital for Sick Children, University of Toronto, Ontario, Canada Hospital; University of Rochester (B.R.); University of Iowa (K.D.M.); Emory University (G.W.); University of South Florida (T.Z.); Friedreich's Ataxia Research Alliance (S.P.), Downingtown, PA; and Division of Neurology (D.R.L.), Children's Hospital of Philadelphia
| | - Susan Perlman
- Clinical Data Science GmbH (C.R.), Basel, Switzerland; Bruce Lefroy Centre for Genetic Health Research (L.A.C., M.B.D.), Murdoch Children's Research Institute, Parkville, Victoria, Australia; Department of Paediatrics (L.A.C., M.B.D.), University of Melbourne, Parkville, Victoria, Australia; Department of Neurology (S.H.S.), McKnight Brain Institute, Room, Gainesville, FL; University of Minnesota (K.B.); University of Chicago (C.M.G.); Ohio State University (J.C.H.); Divisions of Neurology and Clinical and Metabolic Genetics (G.Y.), Department of Paediatrics, the Hospital for Sick Children, University of Toronto, Ontario, Canada Hospital; University of Rochester (B.R.); University of Iowa (K.D.M.); Emory University (G.W.); University of South Florida (T.Z.); Friedreich's Ataxia Research Alliance (S.P.), Downingtown, PA; and Division of Neurology (D.R.L.), Children's Hospital of Philadelphia
| | - Jennifer M Farmer
- Clinical Data Science GmbH (C.R.), Basel, Switzerland; Bruce Lefroy Centre for Genetic Health Research (L.A.C., M.B.D.), Murdoch Children's Research Institute, Parkville, Victoria, Australia; Department of Paediatrics (L.A.C., M.B.D.), University of Melbourne, Parkville, Victoria, Australia; Department of Neurology (S.H.S.), McKnight Brain Institute, Room, Gainesville, FL; University of Minnesota (K.B.); University of Chicago (C.M.G.); Ohio State University (J.C.H.); Divisions of Neurology and Clinical and Metabolic Genetics (G.Y.), Department of Paediatrics, the Hospital for Sick Children, University of Toronto, Ontario, Canada Hospital; University of Rochester (B.R.); University of Iowa (K.D.M.); Emory University (G.W.); University of South Florida (T.Z.); Friedreich's Ataxia Research Alliance (S.P.), Downingtown, PA; and Division of Neurology (D.R.L.), Children's Hospital of Philadelphia
| | - David R Lynch
- Clinical Data Science GmbH (C.R.), Basel, Switzerland; Bruce Lefroy Centre for Genetic Health Research (L.A.C., M.B.D.), Murdoch Children's Research Institute, Parkville, Victoria, Australia; Department of Paediatrics (L.A.C., M.B.D.), University of Melbourne, Parkville, Victoria, Australia; Department of Neurology (S.H.S.), McKnight Brain Institute, Room, Gainesville, FL; University of Minnesota (K.B.); University of Chicago (C.M.G.); Ohio State University (J.C.H.); Divisions of Neurology and Clinical and Metabolic Genetics (G.Y.), Department of Paediatrics, the Hospital for Sick Children, University of Toronto, Ontario, Canada Hospital; University of Rochester (B.R.); University of Iowa (K.D.M.); Emory University (G.W.); University of South Florida (T.Z.); Friedreich's Ataxia Research Alliance (S.P.), Downingtown, PA; and Division of Neurology (D.R.L.), Children's Hospital of Philadelphia
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Manor B, Greenstein PE, Davila-Perez P, Wakefield S, Zhou J, Pascual-Leone A. Repetitive Transcranial Magnetic Stimulation in Spinocerebellar Ataxia: A Pilot Randomized Controlled Trial. Front Neurol 2019; 10:73. [PMID: 30809184 PMCID: PMC6380199 DOI: 10.3389/fneur.2019.00073] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2018] [Accepted: 01/18/2019] [Indexed: 11/13/2022] Open
Abstract
Spinocerebellar ataxia (SCA) is a neurodegenerative disorder caused by dysfunction of the cerebellum and its connected neural networks. There is currently no cure for SCA and symptomatic treatment remains limited. We aimed here to examine the effects of a repetitive transcranial magnetic stimulation (rTMS) targeting the cerebellum on clinical impression, postural control and gait in patients with SCA. In this randomized, double-blinded and sham-controlled study, 20 individuals aged 18-75 years with SCA confirmed by genetic testing completed rTMS or sham intervention comprising 20 sessions of MRI-guided stimulation over the cerebellum. Baseline assessments included the Standard Ataxia Rating Assessment (SARA), the 9-hole peg test of manual dexterity, the Timed Up-and-Go (TUG) test, standing postural control with eyes-open and eyes-closed, and gait. Immediate (within 1-week) and 1-month follow-ups were completed. Intervention compliance was high (19 ± 2 of 20 sessions) and no rTMS-related adverse events were reported. rTMS, compared to sham, was associated with greater percent improvement in SARA total score from baseline to the 1-month follow-up (p = 0.008). Secondary analyses of individual SARA items revealed that rTMS improved performance within the "stance" sub-score only (p = 0.002). This functional change was accompanied by improvement to several objective metrics of postural sway during eyes-open and eyes-closed standing (p < 0.008). rTMS did not influence the 9-hole peg test, TUG, or gait kinematics. A 20-session rTMS intervention is safe and feasible for those with SCA. Additional research is warranted to confirm the observed longer-term benefits of this intervention on standing postural control. Clinical Trial Registration: www.ClinicalTrials.gov, identifier: NCT01975909.
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Affiliation(s)
- Brad Manor
- Berenson-Allen Center for Noninvasive Brain Stimulation and Division for Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
- Hinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, Roslindale, MA, United States
| | - Patricia E Greenstein
- Berenson-Allen Center for Noninvasive Brain Stimulation and Division for Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
| | - Paula Davila-Perez
- Berenson-Allen Center for Noninvasive Brain Stimulation and Division for Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
| | - Seth Wakefield
- Berenson-Allen Center for Noninvasive Brain Stimulation and Division for Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
| | - Junhong Zhou
- Harvard Medical School, Boston, MA, United States
- Hinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, Roslindale, MA, United States
| | - Alvaro Pascual-Leone
- Berenson-Allen Center for Noninvasive Brain Stimulation and Division for Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
- Institut Guttman de Neurorehabilitació, Universitat Autonoma de Barcelona, Barcelona, Spain
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12
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Buckley C, Alcock L, McArdle R, Rehman RZU, Del Din S, Mazzà C, Yarnall AJ, Rochester L. The Role of Movement Analysis in Diagnosing and Monitoring Neurodegenerative Conditions: Insights from Gait and Postural Control. Brain Sci 2019; 9:E34. [PMID: 30736374 PMCID: PMC6406749 DOI: 10.3390/brainsci9020034] [Citation(s) in RCA: 76] [Impact Index Per Article: 15.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2019] [Accepted: 01/31/2019] [Indexed: 12/22/2022] Open
Abstract
Quantifying gait and postural control adds valuable information that aids in understanding neurological conditions where motor symptoms predominate and cause considerable functional impairment. Disease-specific clinical scales exist; however, they are often susceptible to subjectivity, and can lack sensitivity when identifying subtle gait and postural impairments in prodromal cohorts and longitudinally to document disease progression. Numerous devices are available to objectively quantify a range of measurement outcomes pertaining to gait and postural control; however, efforts are required to standardise and harmonise approaches that are specific to the neurological condition and clinical assessment. Tools are urgently needed that address a number of unmet needs in neurological practice. Namely, these include timely and accurate diagnosis; disease stratification; risk prediction; tracking disease progression; and decision making for intervention optimisation and maximising therapeutic response (such as medication selection, disease staging, and targeted support). Using some recent examples of research across a range of relevant neurological conditions-including Parkinson's disease, ataxia, and dementia-we will illustrate evidence that supports progress against these unmet clinical needs. We summarise the novel 'big data' approaches that utilise data mining and machine learning techniques to improve disease classification and risk prediction, and conclude with recommendations for future direction.
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Affiliation(s)
- Christopher Buckley
- Institute of Neuroscience/ Institute for Ageing, Newcastle University, Newcastle Upon Tyne NE4 5PL, UK.
| | - Lisa Alcock
- Institute of Neuroscience/ Institute for Ageing, Newcastle University, Newcastle Upon Tyne NE4 5PL, UK.
| | - Ríona McArdle
- Institute of Neuroscience/ Institute for Ageing, Newcastle University, Newcastle Upon Tyne NE4 5PL, UK.
| | - Rana Zia Ur Rehman
- Institute of Neuroscience/ Institute for Ageing, Newcastle University, Newcastle Upon Tyne NE4 5PL, UK.
| | - Silvia Del Din
- Institute of Neuroscience/ Institute for Ageing, Newcastle University, Newcastle Upon Tyne NE4 5PL, UK.
| | - Claudia Mazzà
- Department of Mechanical Engineering, Sheffield University, Sheffield S1 3JD, UK.
| | - Alison J Yarnall
- Institute of Neuroscience/ Institute for Ageing, Newcastle University, Newcastle Upon Tyne NE4 5PL, UK.
- The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle Upon Tyne NE7 7DN, UK.
| | - Lynn Rochester
- Institute of Neuroscience/ Institute for Ageing, Newcastle University, Newcastle Upon Tyne NE4 5PL, UK.
- The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle Upon Tyne NE7 7DN, UK.
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