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Nair KS, Lott DJ, Forbes SC, Barnard AM, Willcocks RJ, Senesac CR, Daniels MJ, Harrington AT, Tennekoon GI, Zilke K, Finanger EL, Finkel RS, Rooney WD, Walter GA, Vandenborne K. Step Activity Monitoring in Boys with Duchenne Muscular Dystrophy and its Correlation with Magnetic Resonance Measures and Functional Performance. J Neuromuscul Dis 2022; 9:423-436. [PMID: 35466946 PMCID: PMC9257666 DOI: 10.3233/jnd-210746] [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] [Indexed: 01/03/2023]
Abstract
BACKGROUND Muscles of boys with Duchenne muscular dystrophy (DMD) are progressively replaced by fatty fibrous tissues, and weakness leads to loss of ambulation (LoA). Step activity (SA) monitoring is a quantitative measure of real-world ambulatory function. The relationship between quality of muscle health and SA is unknown in DMD. OBJECTIVE To determine SA in steroid treated boys with DMD across various age groups, and to evaluate the association of SA with quality of muscle health and ambulatory function. METHODS Quality of muscle health was measured by magnetic resonance (MR) imaging transverse magnetization relaxation time constant (MRI-T2) and MR spectroscopy fat fraction (MRS-FF). SA was assessed via accelerometry, and functional abilities were assessed through clinical walking tests. Correlations between SA, MR, and functional measures were determined. A threshold value of SA was determined to predict the future LoA. RESULTS The greatest reduction in SA was observed in the 9- < 11years age group. SA correlated with all functional and MR measures.10m walk/run test had the highest correlation with SA. An increase in muscle MRI-T2 and MRS-FF was associated with a decline in SA. Two years prior to LoA, SA in boys with DMD was 32% lower than age matched boys with DMD who maintained ambulation for more than two-year period. SA monitoring can predict subsequent LoA in Duchenne, as a daily step count of 3200 at baseline was associated with LoA over the next two-years. CONCLUSION SA monitoring is a feasible and accessible tool to measure functional capacity in the real-world environment.
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Affiliation(s)
- Kavya S. Nair
- Department of Physical Therapy, University of Florida, Gainesville, Florida, USA
| | - Donovan J. Lott
- Department of Physical Therapy, University of Florida, Gainesville, Florida, USA
| | - Sean C. Forbes
- Department of Physical Therapy, University of Florida, Gainesville, Florida, USA
| | - Alison M. Barnard
- Department of Physical Therapy, University of Florida, Gainesville, Florida, USA
| | - Rebecca J. Willcocks
- Department of Physical Therapy, University of Florida, Gainesville, Florida, USA
| | - Claudia R. Senesac
- Department of Physical Therapy, University of Florida, Gainesville, Florida, USA
| | - Michael J. Daniels
- Department of Statistics, University of Florida, Gainesville, Florida, USA
| | - Ann T. Harrington
- Center for Rehabilitation, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Gihan I. Tennekoon
- Department of Neurology and Pediatrics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Kirsten Zilke
- Department of Pediatrics and Neurology, Oregon Health & Science University, Portland, Oregon, USA
| | - Erika L. Finanger
- Department of Pediatrics and Neurology, Oregon Health & Science University, Portland, Oregon, USA
| | - Richard S. Finkel
- Center for Experimental Neurotherapeutics, St. Jude Children’s Research Hospital, Memphis, Tennessee, USA
| | - William D. Rooney
- Advanced Imaging Research Center, Oregon Health & Science University, Portland, Oregon, USA
| | - Glenn A. Walter
- Department of Physiology and Functional Genomics, University of Florida, Gainesville, Florida, USA
| | - Krista Vandenborne
- Department of Physical Therapy, University of Florida, Gainesville, Florida, USA
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Bortolani S, Brusa C, Rolle E, Monforte M, De Arcangelis V, Ricci E, Mongini TE, Tasca G. Technology-outcome measures in neuromuscular disorders: a systematic review. Eur J Neurol 2021; 29:1266-1278. [PMID: 34962693 DOI: 10.1111/ene.15235] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Accepted: 12/20/2021] [Indexed: 11/30/2022]
Abstract
BACKGROUND Portable and wearable devices can monitor a number of physical performances and have been lately applied to patients with neuromuscular disorders (NMD). METHODS We performed a systematic search of literature databases following PRISMA principles, including all studies reporting the use of technological devices for motor function assessment in NMDs from 2000 to 2021. We also summarized the evidence on measurement properties (validity, reliability, responsiveness) of the analyzed technological outcome measures. RESULTS One-hundred studies fulfilled the selection criteria, most of them published in the last ten years. We defined four categories that gathered similar technologies: gait analysis tools, for clinical assessment of pace and posture; continuous monitoring of physical activity with inertial sensors, that allow "unsupervised" activity assessment; upper limb evaluation tools, including Kinect-based outcome measures to assess the reachable workspace; and new muscle strength assessment tools, such as Myotools. Inertial sensors have the evident advantage of being applied in the "in-home" setting, which has become especially appealing with the Covid-19 pandemic, although poor evidence from psychometric property assessment and results of the analyzed studies may limit their research application. Both Kinect-based outcome measures and Myotools have been already validated in multicenter studies and different NMDs, showing excellent characteristics for application in clinical trials. CONCLUSION This overview is intended to raise awareness on the potential of the different TOMs in the neuromuscular field and be an informative source for the design of future clinical trials, particularly in the era of telemedicine.
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Affiliation(s)
- Sara Bortolani
- Department of Neuroscience, Rita Levi Montalcini", University of Turin, Via Cherasco 15, 10126, Turin, Italy.,Unità Operativa Complessa di Neurologia, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
| | - Chiara Brusa
- Department of Neuroscience, Rita Levi Montalcini", University of Turin, Via Cherasco 15, 10126, Turin, Italy
| | - Enrica Rolle
- Department of Neuroscience, Rita Levi Montalcini", University of Turin, Via Cherasco 15, 10126, Turin, Italy
| | - Mauro Monforte
- Unità Operativa Complessa di Neurologia, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
| | - Valeria De Arcangelis
- Unità Operativa Complessa di Neurologia, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
| | - Enzo Ricci
- Unità Operativa Complessa di Neurologia, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy.,Istituto di Neurologia, Università Cattolica del Sacro Cuore, Rome, Italy
| | - Tiziana Enrica Mongini
- Department of Neuroscience, Rita Levi Montalcini", University of Turin, Via Cherasco 15, 10126, Turin, Italy
| | - Giorgio Tasca
- Unità Operativa Complessa di Neurologia, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
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