Knee4Life Project: Empowering Knee Recovery After Total Knee Replacement Through Digital Health

NCT06429462 | Recruiting

• 1 other identifier: 339937
• Study Type: observational
• Target: 75
• Locations: 1 country
• Sites: 1

Brief Summary

The research project will investigate the extent to which a smartphone camera sensor tool can help predict and measure knee stiffness and pain after Total Knee Replacement Surgery (TKR) and how a tool such as this could be implemented into the NHS. Total knee replacement (TKR) is a frequent procedure undertaken in England and Wales, with more than 100,000 conducted each year. Although most patients have a successful outcome following their TKR, approximately 10-20% of patients are dissatisfied, predominantly because of pain and knee stiffness. A method to detect early problems with pain and stiffness could facilitate earlier referral to non-surgical treatments, which are effective in preventing the need for manipulation under anaesthetic (MUA). Here the investigators will validate and provide proof of concept for a smartphone camera sensor tool that measures knee range of motion alongside symptoms of pain for use in the home setting. The study will comprise of 3 stages;

1. 1.We will conduct 45 minute online interviews comprising of (1) people who have had total knee replacement surgery, (2) healthcare professionals and stakeholders.
2. 2.We will invite 30 participants who are 5-9 weeks post TKR and 30 participants who have had no previous musculoskeletal injuries to attend a session at the university. The lab testing will be conducted at the VSimulator, a biomechanics research lab at the Exeter Science park, and at the teaching labs on St Lukes Campus, Exeter. Here participants be asked to answer 8 questionnaires and have some of their movements measured.
3. 3.Participants will be asked to repeat the 'timed up and go' and the 'sit to stand' tests in their homes and record them using a mobile device.

Conditions

Total Knee Replacement

Keywords

rehabilitation; surgery; motion capture; focus group

Outcome Measures

Primary Outcomes (3)

• Validation of the accuracy and reliability of camera sensor tool through comparison of knee joint angles based on motion capture from different sources

  To validate in the lab and provide proof of concept for a smartphone camera sensor tool that measures knee range of motion (ROM) alongside symptoms of pain for use in the home setting. This will be assessed by comparing the knee joint angles and range of motion measures using two different forms of motion capture during different movements.

  through study completion, an average of 1 year

• Predicting knee stiffness after surgery through analysis of knee joint angles

  To investigate who might develop stiffness after Total Knee Replacement surgery. This will be measured by looking at the range of motion of the knee using motion capture data.

  through study completion, an average of 1 year

• Knee pain measured through the oxford pain score questionnaire

  Participants will be questioned on how painful their knee is post surgery using the Oxford pain score questionnaire.

  through study completion, an average of 1 year

Secondary Outcomes (1)

• Feasibility of clinical integration of camera sensor tool

  through study completion, an average of 1 year

Study Arms (5)

Healthy Controls (lab assessment)

Participants will be asked to complete 8 questionnaires before the lab assessments: The data will be entered and saved onto REDCap by a member of the research team. The 8 questionnaires including baseline data are PROMIS-29 v2, Oxford Knee Score, IPAQ Short Last 7 Days, Numeric Rating Scale, Single Ease Question, Barthel Index for Activities of Daily Living and EQ-5D-5L. Participants will be asked to complete the following: 2-minute walk on a treadmill 10 m walk (5 m x 2). Timed up and Go (TUG) Sit to stand test At home: TUG Sit to stand test

Diagnostic Test: smartphone camera sensor tool

Participant post total knee replacement surgery (lab assessment)

Participants will be asked to complete 8 questionnaires before the lab assessments: The data will be entered and saved onto REDCap by a member of the research team. The 8 questionnaires including baseline data are PROMIS-29 v2, Oxford Knee Score, IPAQ Short Last 7 Days, Numeric Rating Scale, Single Ease Question, Barthel Index for Activities of Daily Living and EQ-5D-5L. Participants will be asked to complete the following: 2-minute walk on a treadmill 10 m walk (5 m x 2). Timed up and Go (TUG) Sit to stand test At home: TUG Sit to stand test

Diagnostic Test: smartphone camera sensor tool

Healthcare professionals (focus group)

A member of the research team will conduct interviews to discuss how the knee4life project and how final tool can be deployed in clinics and services. These discussions will provide valuable insights into the future adoption and application of computer-vision technology. These will take place online.

Stakeholders (focus group)

A member of the research team will conduct interviews to discuss how the knee4life project and how final tool can be deployed in clinics and services. These discussions will provide valuable insights into the future adoption and application of computer-vision technology. These will take place online.

Participants post total knee replacement surgery

A member of the research team will conduct interviews to discuss how the knee4life project and how final tool can be deployed in clinics and services. These discussions will provide valuable insights into the future adoption and application of computer-vision technology. These will take place online.

Interventions

smartphone camera sensor tool DIAGNOSTIC_TEST

The study will involve the development and validation of a computer vision-based approach (using cameras to assess movements) to monitor knee flexion and extension, and a walking pattern assessment.

Healthy Controls (lab assessment); Participant post total knee replacement surgery (lab assessment)

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Convenience sampling will be used to recruit healthcare professionals and stakeholders. Participants need to be identified within the timeline and scope of the project. Obtaining volunteers who are easily available and willing is a sensible sampling strategy for the scope of the project. They will be identified through professional networks and associations and will be invited to take part in the study by the University of Exeter research team via email. Participants post-TKR will be recruited using a purposive sampling method, where individuals are selected based on their unique characteristics or experiences. For instance, they will be identified through hospital records and invited to participate by the NHS trust research team.

You may qualify if:

• People aged ≥18 years old
• Recently had a total knee replacement surgery or has worked with people following this surgery as a clinical, carer or therapist
• Able to give informed consent
• Able to communicate in English with the research team

You may not qualify if:

• Any medical condition compromising the safety or the ability to take part in the study
• Unable to adhere to study procedures

Sponsors & Collaborators

• University of Exeter: lead
• National Institute for Health Research, United Kingdom: collaborator
• Exeter Biomedical Research Centre (BRC) grant: collaborator

Study Sites (1)

University of Exeter

Exeter, EX1 2LP, United Kingdom

RECRUITING

Central Study Contacts

Maedeh Mansoubi, PhD

CONTACT

07866138722; M.Mansoubi@exeter.ac.uk

Study Design

• Study Type: observational
• Observational Model: CASE CONTROL
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: May 2, 2024
• First Posted: May 28, 2024
• Study Start: May 1, 2024
• Primary Completion: May 1, 2025
• Study Completion: May 1, 2025
• Last Updated: May 28, 2024

Record last verified: 2024-05

Data Sharing

• IPD Sharing: Will not share

Locations

GB (1)