Robotic Assisted Rehabilitation for Balance and Gait in Orthopedic Patients.

NCT ID: NCT05459584

Last Updated: 2024-01-24

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Clinical Phase

NA

Total Enrollment

24 participants

Study Classification

INTERVENTIONAL

Study Start Date

2022-08-01

Study Completion Date

2023-10-31

Brief Summary

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Osteoarthritis is a chronic, degenerative disease affecting the joints. It is characterized by the presence of bone tissue that goes to make up for the loss of articular cartilage, causing pain and limitation of movement. Osteoarthritis is a direct consequence of aging: it affects almost all 70-year-olds, peaking between 75 and 79 years. The presence of osteoarthritic processes at the hip and knee joints can result in pain, difficulty maintaining standing for a long time, and difficulty walking with loss of balance, increasing the risk of accidental falls to the ground. Falls are a frequent cause of mortality and morbidity and, often, limit autonomy leading to premature entry into assisted living facilities.

In Italy, in 2002 it was estimated that 28.6% of people over 65 years fall within a year: of these, 43% fall more than once and 60% of falls occur at home. Such falls can often result in fractures leading to the need for hospitalization with significant impact on both motor and cognitive function. Balance and gait rehabilitation are of primary importance for the recovery of a person's autonomy and independence, especially in older individuals who have undergone osteosynthesis or prosthesis surgery of the lower limbs. Technological and robotic rehabilitation allows for greater intensity, objectivity, and standardization in treatment protocols, as well as in outcome measurement. In this context, patient motivation is fuelled and maintained by both the sensory stimuli that support technological treatment and the challenge of achieving ever better results, objective feedback from instrumental assessments. Osteoarthritic patients who have undergone osteosynthesis or lower extremity prosthetic surgery require special attention, especially with the goal of preventing further accidents and reducing the patient's risk of falling.

Given these considerations, it is believed that conventional physical therapy combined with technological balance treatment may be more effective on rehabilitation outcome than conventional therapy alone.

Detailed Description

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Twenty-four patients of both sexes will be recruited, evaluated, and treated at Rehabilitation and Physical Medicine Unit, Fondazione Policlinico Universitario A. Gemelli IRCCS of Rome, from August 2022 to August 2023. Patients will be divided into two groups by 1:1 randomization ratio: one group (Technological Group, TG) will perform specific rehabilitation for the balance using the robotic platform (Hunova®, Movendo Technology srl, Genova, IT) 3 times a week, for 4 weeks (12 total sessions), for 45 minutes of treatment, in addition to the conventional treatment and one group will perform only the conventional treatment (Control Group, CG), as per daily routine.

Conditions

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Osteoarthritis, Knee Osteoarthritis, Hip Gait Disorders in Old Age Balance; Distorted

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Interventional pilot randomized controlled trial
Primary Study Purpose

TREATMENT

Blinding Strategy

SINGLE

Investigators

Study Groups

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Experimental: Technological Group

Technological group (TG) patients will undergo robotic treatment for the improvement balance through the robotic platform (Hunova® Movendo Technology srl, Genova, IT), 3 times per week for 45 minutes each, in addition to the conventional treatment (total 180 minutes per day). In particular, the technological rehabilitation performed employing a footboard will be mostly aimed at improving the balance both in sitting and standing position, and will be proposed static and dynamic exercises, exercises dual-task exercises, and exercises to improve trunk control.

Group Type EXPERIMENTAL

Technological Rehabilitation

Intervention Type DEVICE

Specific rehabilitation for balance disorder using the robotic platform

No Intervention: Control Group

Congrol Group (CG) patients will undergo conventional rehabilitation treatment only, using the main rehabilitation methods (e.g., neurocognitive theory, Bobath Concept, Progressive neuromuscular facilitation, etc.).

Group Type NO_INTERVENTION

No interventions assigned to this group

Interventions

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Technological Rehabilitation

Specific rehabilitation for balance disorder using the robotic platform

Intervention Type DEVICE

Other Intervention Names

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Hunova® Movendo Technology srl

Eligibility Criteria

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Inclusion Criteria

* Age greater than or equal to 55 years;
* Patients with outcomes of surgery for prosthetic hip or knee replacement;
* Latency from the acute event between 15 days and 3 months;
* Cognitive abilities to execute simple orders and understand the physical therapist's directions \[assessed by Token Test (score ≥26.5)\];
* Ability to walk independently or with little assistance;
* Ability to understand and sign informed consent.

Exclusion Criteria

* Presence of systemic, neurological, cardiac pathologies that make walking hazardous or cause motor deficits;
* Presence of oncological pathologies;
* Presence of plantar ulcers;
* Partial or total amputation of foot segments.
Minimum Eligible Age

55 Years

Maximum Eligible Age

99 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Fondazione Policlinico Universitario Agostino Gemelli IRCCS

OTHER

Sponsor Role lead

Responsible Party

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GIOVANNINI SILVIA

Researcher

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Silvia Giovannini, MD, phD

Role: PRINCIPAL_INVESTIGATOR

Fondazione Policlinico Universitaria A. Gemelli IRCCS

Locations

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Fondazione Policlinico Universitario A. Gemelli IRCCS

Rome, , Italy

Site Status

Countries

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Italy

References

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R Core Team (2021). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.

Reference Type BACKGROUND

Alessandri G, Zuffiano A, Perinelli E. Evaluating Intervention Programs with a Pretest-Posttest Design: A Structural Equation Modeling Approach. Front Psychol. 2017 Mar 2;8:223. doi: 10.3389/fpsyg.2017.00223. eCollection 2017.

Reference Type RESULT
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Castelli L, De Luca F, Marchetti MR, Sellitto G, Fanelli F, Prosperini L. The dual task-cost of standing balance affects quality of life in mildly disabled MS people. Neurol Sci. 2016 May;37(5):673-9. doi: 10.1007/s10072-015-2456-y. Epub 2016 Jan 4.

Reference Type RESULT
PMID: 26728268 (View on PubMed)

Cattaneo D, Carpinella I, Aprile I, Prosperini L, Montesano A, Jonsdottir J. Comparison of upright balance in stroke, Parkinson and multiple sclerosis. Acta Neurol Scand. 2016 May;133(5):346-54. doi: 10.1111/ane.12466. Epub 2015 Aug 3.

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Reference Type RESULT

Glyn-Jones S, Palmer AJ, Agricola R, Price AJ, Vincent TL, Weinans H, Carr AJ. Osteoarthritis. Lancet. 2015 Jul 25;386(9991):376-87. doi: 10.1016/S0140-6736(14)60802-3. Epub 2015 Mar 4.

Reference Type RESULT
PMID: 25748615 (View on PubMed)

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Reference Type RESULT
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Reference Type RESULT

Hu LT, Bentler PM. Cutoff Criteria for Fit Indexes in Covariance Structure Analysis: Conventional Criteria versus New Alternatives. Structural Equation Modeling, 1999, 6, 1-55. doi: 10.1080/10705519909540118

Reference Type RESULT

Julious, SA. 'Sample size of 12 per group rule of thumb for a pilot study'. Pharmaceutical Statistics. 2005, Vol 4. Pages 287-291.

Reference Type RESULT

Kline, RB. (2016). Principles and Practice of Structural Equation Modeling, 4th Edn. New York, NY: The Guilford Press.

Reference Type RESULT

MacCallum RC, Browne MW, Sugawara HM. Power analysis and determination of sample size for covariance structure modeling. Psychological Methods, 1996, 1(2), 130-149. doi: 10.1037/1082-989X.1.2.130

Reference Type RESULT

Muthén, BO and Curran PJ. General longitudinal modeling of individual differences in experimental designs: a latent variable framework for analysis and power estimation. Psychol. Methods 1997, 2, 371-402. doi: 10.1037/1082-989X.2.4.371

Reference Type RESULT

Prosperini L, Castelli L, De Luca F, Fabiano F, Ferrante I, De Giglio L. Task-dependent deterioration of balance underpinning cognitive-postural interference in MS. Neurology. 2016 Sep 13;87(11):1085-92. doi: 10.1212/WNL.0000000000003090. Epub 2016 Aug 12.

Reference Type RESULT
PMID: 27521436 (View on PubMed)

Prosperini L, Castelli L, Sellitto G, De Luca F, De Giglio L, Gurreri F, Pozzilli C. Investigating the phenomenon of "cognitive-motor interference" in multiple sclerosis by means of dual-task posturography. Gait Posture. 2015 Mar;41(3):780-5. doi: 10.1016/j.gaitpost.2015.02.002. Epub 2015 Feb 21.

Reference Type RESULT
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Reference Type RESULT
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Other Identifiers

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0022215/22

Identifier Type: -

Identifier Source: org_study_id

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