NCT05459584

Brief Summary

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.

Trial Health

87
On Track

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
24

participants targeted

Target at below P25 for not_applicable

Timeline
Completed

Started Aug 2022

Geographic Reach
1 country

1 active site

Status
completed

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

First Submitted

Initial submission to the registry

July 13, 2022

Completed
2 days until next milestone

First Posted

Study publicly available on registry

July 15, 2022

Completed
17 days until next milestone

Study Start

First participant enrolled

August 1, 2022

Completed
1.1 years until next milestone

Primary Completion

Last participant's last visit for primary outcome

August 31, 2023

Completed
2 months until next milestone

Study Completion

Last participant's last visit for all outcomes

October 31, 2023

Completed
Last Updated

January 24, 2024

Status Verified

January 1, 2024

Enrollment Period

1.1 years

First QC Date

July 13, 2022

Last Update Submit

January 23, 2024

Conditions

Keywords

RehabilitationTechnologyBalance

Outcome Measures

Primary Outcomes (1)

  • Berg Balance Scale (BBS)

    The Berg Balance Scale (BBS) is used to objectively determine a patient's ability (or inability) to safely balance during a series of predetermined tasks. It is a 14 item list with each item consisting of a five-point ordinal scale ranging from 0 to 4, with 0 indicating the lowest level of function and 4 the highest level of function and takes approximately 20 minutes to complete. It does not include the assessment of gait.

    Change from Baseline Ambulation Index at 4 weeks

Secondary Outcomes (17)

  • Motricity Index (MI)

    Change from Baseline Ambulation Index at 4 weeks

  • Timed Up and Go Test (TUG)

    Change from Baseline Ambulation Index at 4 weeks

  • Knee Injury and Osteoarthritis Outcome Score - Italian Version (KOOS-I)

    Change from Baseline Ambulation Index at 4 weeks

  • Hip disability and Osteoarthritis Outcome Score - Italian version (HOOS-I)

    Change from Baseline Ambulation Index at 4 weeks

  • Ambulation Index (AI)

    Change from Baseline Ambulation Index at 4 weeks

  • +12 more secondary outcomes

Study Arms (2)

Experimental: Technological Group

EXPERIMENTAL

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.

Device: Technological Rehabilitation

No Intervention: Control Group

NO INTERVENTION

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.).

Interventions

Specific rehabilitation for balance disorder using the robotic platform

Also known as: Hunova® Movendo Technology srl
Experimental: Technological Group

Eligibility Criteria

Age55 Years - 99 Years
Sexall
Healthy VolunteersNo
Age GroupsAdult (18-64), Older Adult (65+)

You may qualify if:

  • 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.

You may not qualify if:

  • 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.

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

Fondazione Policlinico Universitario A. Gemelli IRCCS

Rome, 00168, Italy

Location

Related Publications (19)

  • 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/.

    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.

  • Aprile I, Iacovelli C, Padua L, Galafate D, Criscuolo S, Gabbani D, Cruciani A, Germanotta M, Di Sipio E, De Pisi F, Franceschini M. Efficacy of Robotic-Assisted Gait Training in chronic stroke patients: Preliminary results of an Italian bi-centre study. NeuroRehabilitation. 2017;41(4):775-782. doi: 10.3233/NRE-172156.

  • Burnham KP, Anderson DR. Multimodel Inference: Understanding AIC and BIC in Model Selection. Sociological Methods & Research. 2004;33(2):261-304. doi:10.1177/0049124104268644

    RESULT
  • 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.

  • 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.

  • Davis RB, Õunpuu S, Tyburski D, Gage JR. A gait analysis data collection and reduction technique. Hum. Mov. Sci. 1991; 10, 575-587

    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.

  • Harris PA, Taylor R, Minor BL, Elliott V, Fernandez M, O'Neal L, McLeod L, Delacqua G, Delacqua F, Kirby J, Duda SN; REDCap Consortium. The REDCap consortium: Building an international community of software platform partners. J Biomed Inform. 2019 Jul;95:103208. doi: 10.1016/j.jbi.2019.103208. Epub 2019 May 9.

  • Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009 Apr;42(2):377-81. doi: 10.1016/j.jbi.2008.08.010. Epub 2008 Sep 30.

  • Hu LT, Bentler PM. Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification. Psychological Methods. 1998, 3(4), 424-453. doi: 10.1037/1082-989X.3.4.424

    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

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

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

    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

    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

    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.

  • 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.

  • Sinusas K. Osteoarthritis: diagnosis and treatment. Am Fam Physician. 2012 Jan 1;85(1):49-56.

MeSH Terms

Conditions

Osteoarthritis, KneeOsteoarthritis, Hip

Condition Hierarchy (Ancestors)

OsteoarthritisArthritisJoint DiseasesMusculoskeletal DiseasesRheumatic Diseases

Study Officials

  • Silvia Giovannini, MD, phD

    Fondazione Policlinico Universitaria A. Gemelli IRCCS

    PRINCIPAL INVESTIGATOR

Study Design

Study Type
interventional
Phase
not applicable
Allocation
RANDOMIZED
Masking
SINGLE
Who Masked
INVESTIGATOR
Purpose
TREATMENT
Intervention Model
PARALLEL
Model Details: Interventional pilot randomized controlled trial
Sponsor Type
OTHER
Responsible Party
PRINCIPAL INVESTIGATOR
PI Title
Researcher

Study Record Dates

First Submitted

July 13, 2022

First Posted

July 15, 2022

Study Start

August 1, 2022

Primary Completion

August 31, 2023

Study Completion

October 31, 2023

Last Updated

January 24, 2024

Record last verified: 2024-01

Data Sharing

IPD Sharing
Will not share

Locations