The Effectiveness of Robot- vs. Virtual Reality-Based Gait Rehabilitation: A Propensity Score Matched Cohort

Emilia Biffi, Elena Beretta, Fabio Alexander Storm, Claudio Corbetta, Sandra Strazzer, Alessandra Pedrocchi, Emilia Ambrosini, Emilia Biffi, Elena Beretta, Fabio Alexander Storm, Claudio Corbetta, Sandra Strazzer, Alessandra Pedrocchi, Emilia Ambrosini

Abstract

Robot assisted gait training (RAGT) and virtual reality plus treadmill training (VRTT) are two technologies that can support locomotion rehabilitation in children and adolescents affected by acquired brain injury (ABI). The literature provides evidence of their effectiveness in this population. However, a comparison between these methods is not available. This study aims at comparing the effectiveness of RAGT and VRTT for the gait rehabilitation of children and adolescents suffering from ABI. This is a prospective cohort study with propensity score matching. Between October 2016 and September 2018, all patients undergoing an intensive gait rehabilitation treatment based on RAGT or VRTT were prospectively observed. To minimize selection bias associated with the study design, patients who underwent RAGT or VRTT were retrospectively matched for age, gender, time elapsed from injury, level of impairment, and motor impairment using propensity score in a matching ratio of 1:1. Outcome measures were Gross Motor Function Mesure-88 (GMFM-88), six-min walking test (6MWT), Gillette Functional Assessment Questionnaire (FAQ), and three-dimensional gait analysis (GA). The FAQ and the GMFM-88 had a statistically significant increase in both groups while the 6MWT improved in the RAGT group only. GA highlighted changes at the proximal level in the RAGT group, and at the distal district in the VRTT group. Although preliminary, this work suggests that RAGT and VRTT protocols foster different motor improvements, thus recommending to couple the two therapies in the paediatric population with ABI.

Keywords: acquired brain injury; children; cohort study; propensity score matching; robot-assisted gait training; virtual reality plus treadmill training.

Conflict of interest statement

The Authors declare no conflict of interest.

Figures

Figure 1
Figure 1
(A) The Lokomat device. (B) The Grail system.
Figure 2
Figure 2
Flowchart of the study. GA: Gait Analysis, N: number of patients.
Figure 3
Figure 3
Standardized Mean Differences in the unmatched cohorts (N = 70, blue dots) and after the matching (N = 30, red dots).
Figure 4
Figure 4
Functional measures of the matched cohorts. * Wilcoxon signed rank test with p < 0.05. (A) GMFM: Gross Motor Function Measure; (B) GMFM-D and (C) GMFM-E; (D) 6MWT: 6 min walking test; (E) FAQ: Gillette Functional Assessment Questionnaire; RAGT: Robot-Assisted Gait Training; VRTT: Virtual Reality Treadmill Training.

References

    1. Wong C.P., Forsyth R., Kelly T.P., Eyre J.A. Incidence, aetiology, and outcome of non-traumatic coma: A population based study. Arch. Dis. Child. 2001;84:193–199. doi: 10.1136/adc.84.3.193.
    1. Gazzellini S., Strazzer S., Stortini M., Veredice C., Beretta E., Lispi M.L., Petacchi M.E., Menna M., Cipriani P., Zampolini M., et al. Pediatric rehabilitation of severe acquired brain injury: A multicenter survey. Eur. J. Phys. Rehabil. Med. 2012;48:423–431.
    1. Maranesi E., Riccardi G.R., Di Donna V., Di Rosa M., Fabbietti P., Luzi R., Pranno L., Lattanzio F., Bevilacqua R. Effectiveness of Intervention Based on End-effector Gait Trainer in Older Patients With Stroke: A Systematic Review. J. Am. Med. Dir. Assoc. 2020;21:1036–1044. doi: 10.1016/j.jamda.2019.10.010.
    1. Mehrholz J., Thomas S., Kugler J., Pohl M., Elsner B. Electromechanical-assisted training for walking after stroke. Cochrane Database Syst. Rev. 2020
    1. Yeh S., Lin L., Tam K., Tsai C., Hong C., Kuan Y. Efficacy of robot-assisted gait training in multiple sclerosis: A systematic review and meta-analysis. Mult. Scler. Relat. Disord. 2020;41:102034. doi: 10.1016/j.msard.2020.102034.
    1. Fang C., Tsai J., Li G., Lien A.S., Chang Y. Effects of robot-assisted gait training in individuals with spinal cord injury: A meta-analysis. BioMed Res. Int. 2020;2020:2102785. doi: 10.1155/2020/2102785.
    1. Lefmann S., Russo R., Hillier S. The effectiveness of robotic-assisted gait training for paediatric gait disorders: Systematic review. J. Neuroeng. Rehabil. 2017;14:1–10. doi: 10.1186/s12984-016-0214-x.
    1. Jin L.H., Yang S.-S., Choi J.Y., Sohn M.K. The Effect of Robot-Assisted Gait Training on Locomotor Function and Functional Capability for Daily Activities in Children with Cerebral Palsy: A Single-Blinded, Randomized Cross-Over Trial. Brain Sci. 2020;10:801. doi: 10.3390/brainsci10110801.
    1. Cherni Y., Ballaz L., Lemaire J., Maso F.D., Begon M. Effect of low dose robotic-gait training on walking capacity in children and adolescents with cerebral palsy. Neurophysiol. Clin. 2020;50:507–519. doi: 10.1016/j.neucli.2020.09.005.
    1. Carvalho I., Pinto S.M., Chagas D.D.V., Praxedes Dos Santos J.L., de Sousa Oliveira T., Batista L.A. Robotic Gait Training for Individuals with Cerebral Palsy: A Systematic Review and Meta-Analysis. Arch. Phys. Med. Rehabil. 2017;98:2332–2344. doi: 10.1016/j.apmr.2017.06.018.
    1. Petrarca M., Frascarelli F., Carniel S., Colazza A., Minosse S., Tavernese E., Castelli E. Robotic-assisted locomotor treadmill therapy does not change gait pattern in children with cerebral palsy. Int. J. Rehabil. Res. 2021;44:69–76. doi: 10.1097/MRR.0000000000000451.
    1. Druzbicki M., Rusek W., Snela S., Dudek J., Szczepanik M., Zak E., Durmala J., Czernuszenko A., Bonikowski M., Sobota G. Functional effects of robotic-assisted locomotor treadmill thearapy in children with cerebral palsy. J. Rehabil. Med. 2013;45:358–363. doi: 10.2340/16501977-1114.
    1. Swinnen E., Lefeber N. Benefits of robotic gait rehabilitation in cerebral palsy: Lessons to be learned. Dev. Med. Child Neurol. 2021;63:248–249. doi: 10.1111/dmcn.14795.
    1. Beretta E., Storm F.A., Strazzer S., Frascarelli F., Petrarca M., Colazza A., Cordone G., Biffi E., Morganti R., Maghini C., et al. Effect of Robot-Assisted Gait Training in a Large Population of Children With Motor Impairment Due to Cerebral Palsy or Acquired Brain Injury. Arch. Phys. Med. Rehabil. 2020;101:106–112. doi: 10.1016/j.apmr.2019.08.479.
    1. Beretta E., Molteni E., Biffi E., Morganti R., Avantaggiato P., Strazzer S. Robotically-driven orthoses exert proximal-to-distal differential recovery on the lower limbs in children with hemiplegia, early after acquired brain injury. Eur. J. Paediatr. Neurol. 2018;22:652–661. doi: 10.1016/j.ejpn.2018.03.002.
    1. Beretta E., Romei M., Molteni E., Avantaggiato P., Strazzer S. Combined robotic-aided gait training and physical therapy improve functional abilities and hip kinematics during gait in children and adolescents with acquired brain injury. Brain Inj. 2015;29:955–962. doi: 10.3109/02699052.2015.1005130.
    1. Karunakaran K.K., Ehrenberg N., Cheng J., Bentley K., Nolan K.J. Kinetic Gait Changes after Robotic Exoskeleton Training in Adolescents and Young Adults with Acquired Brain Injury. Appl. Bionics Biomech. 2020;2020:8845772. doi: 10.1155/2020/8845772.
    1. Ghai S., Ghai I. Virtual Reality Enhances Gait in Cerebral Palsy: A Training Dose-Response Meta-Analysis. Front. Neurol. 2019;10:236. doi: 10.3389/fneur.2019.00236.
    1. Fandim J.V., Saragiotto B.T., Porfirio G.J.M., Santana R.F. Effectiveness of virtual reality in children and young adults with cerebral palsy: A systematic review of randomized controlled trial. Braz. J. Phys. Ther. 2020 doi: 10.1016/j.bjpt.2020.11.003. in press.
    1. Deutsch J.E., McCoy S.W. Virtual Reality and Serious Games in Neurorehabilitation of Children and Adults: Prevention, Plasticity, and Participation. Pediatr. Phys. Ther. 2017;29(Suppl. 3):S23–S36. doi: 10.1097/PEP.0000000000000387.
    1. Peri E., Panzeri D., Beretta E., Reni G., Strazzer S., Biffi E. Motor Improvement in Adolescents Affected by Ataxia Secondary to Acquired Brain Injury: A Pilot Study. BioMed Res. Int. 2019;2019:8967138. doi: 10.1155/2019/8967138.
    1. Beretta E., Cesareo A., Maghini C., Turconi A.C., Reni G., Strazzer S., Biffi E. An Immersive Virtual Reality Platform to Enhance Walking Ability of Children with Acquired Brain Injuries. Methods Inf. Med. 2017;56:119–126. doi: 10.3414/ME16-02-0020.
    1. Reiffel J.A. Propensity-Score Matching: Optimal, Adequate, or Incomplete? J. Atr. Fibrillation. 2018;11:2130. doi: 10.4022/jafib.2130.
    1. Jupiter D.C. Propensity Score Matching: Retrospective Randomization? J. Foot Ankle Surg. 2017;56:417–420. doi: 10.1053/j.jfas.2017.01.013.
    1. Austin P.C. Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity-score matched samples. Stat. Med. 2009;28:3083–3107. doi: 10.1002/sim.3697.
    1. Rosenbaum P.R., Rubin D.B. The central role of the propensity score in observational studies for causal effects. Biometrika. 1983;70:41–55. doi: 10.1093/biomet/70.1.41.
    1. Palisano R., Rosenbaum P., Walter S., Russell D., Wood E., Galuppi B. Development and reliability of a system to classify gross motor function in children with cerebral palsy. Dev. Med. Child Neurol. 1997;39:214–223. doi: 10.1111/j.1469-8749.1997.tb07414.x.
    1. Jackman M., Novak I., Lannin N. Effectiveness of functional hand splinting and the cognitive orientation to occupational performance (CO-OP) approach in children with cerebral palsy and brain injury: Two randomised controlled trial protocols. BMC Neurol. 2014;14:144. doi: 10.1186/1471-2377-14-144.
    1. Linder-Lucht M., Othmer V., Walther M., Vry J., Michaelis U., Stein S., Weissenmayer H., Korinthenberg R., Mall V., Validation of the Gross Motor Function Measure-Traumatic Brain Injury Study Group Validation of the Gross Motor Function Measure for Use in Children and Adolescents With Traumatic Brain Injuries. Pediatrics. 2007;120:e880–e886. doi: 10.1542/peds.2006-2258.
    1. Mossberg K.A., Fortini E. Responsiveness and Validity of the Six-Minute Walk Test in Individuals with Traumatic Brain Injury. Phys. Ther. 2012;92:726–733. doi: 10.2522/ptj.20110157.
    1. Novacheck T.F., Stout J.L., Tervo R. Reliability and validity of the Gillette Functional Assessment Questionnaire as an outcome measure in children with walking disabilities. J. Pediatr. Orthop. 2000;20:75–81. doi: 10.1097/01241398-200001000-00017.
    1. Schwartz M.H., Rozumalski A. The gait deviation index: A new comprehensive index of gait pathology. Gait Posture. 2008;28:351–357. doi: 10.1016/j.gaitpost.2008.05.001.
    1. Storm F.A., Petrarca M., Beretta E., Strazzer S., Piccinini L., Maghini C., Panzeri D., Corbetta C., Morganti R., Reni G., et al. Minimum Clinically Important Difference of Gross Motor Function and Gait Endurance in Children with Motor Impairment: A Comparison of Distribution-Based Approaches. BioMed Res. Int. 2020;2020:2794036. doi: 10.1155/2020/2794036.
    1. Schmid S., Romkes J., Taylor W.R., Lorenzetti S., Brunner R. Orthotic correction of lower limb function during gait does not immediately influence spinal kinematics in spastic hemiplegic cerebral palsy. Gait Posture. 2016;49:457–462. doi: 10.1016/j.gaitpost.2016.08.013.
    1. Flux E., van der Krogt M., Cappa P., Petrarca M., Desloovere K., Harlaar J. The Human Body Model versus conventional gait models for kinematic gait analysis in children with cerebral palsy. Hum. Mov. Sci. 2020;70:102585. doi: 10.1016/j.humov.2020.102585.
    1. Wu M., Kim J., Arora P., Gaebler-Spira D.J., Zhang Y. Effects of the Integration of Dynamic Weight Shifting Training Into Treadmill Training on Walking Function of Children with Cerebral Palsy: A Randomized Controlled Study. Am. J. Phys. Med. Rehabil. 2017;96:765–772. doi: 10.1097/PHM.0000000000000776.
    1. Harvey R.L. Improving poststroke recovery: Neuroplasticity and task-oriented training. Curr. Treat. Options Cardiovasc. Med. 2009;11:251–259. doi: 10.1007/s11936-009-0026-4.
    1. Ishizuka M., Shibuya N., Takagi K., Hachiya H., Tago K., Sato S., Shimizu T., Matsumoto T., Aoki T., Kubota K. Impact of anastomotic leakage on postoperative survival of patients with colorectal cancer: A meta-analysis using propensity score matching studies. Surg. Oncol. 2021;37:101538. doi: 10.1016/j.suronc.2021.101538.
    1. Stuart E.A. Matching Methods for Causal Inference: A Review and a Look Forward. Stat. Sci. 2010;25:1–21. doi: 10.1214/09-STS313.
    1. American Evaluation Association . Using Propensity Scores with Small Samples. American Evaluation Association; San Antonio, TX, USA: 2010. Annual Meetings of the American Evaluation Association.

Source: PubMed

3
Abonnieren