Wearable Sensors for Monitoring Recovery After Total Knee Arthroplasty

Sponsor
Aalborg University Hospital (Other)
Overall Status
Not yet recruiting
CT.gov ID
NCT05992064
Collaborator
Aalborg University (Other)
30
24

Study Details

Study Description

Brief Summary

The goal of this observational study is to investigate the potential of wearable sensors for monitoring the postoperative recovery of patients after TKA.

The main question the study aims to answer is:

• whether alterations in gait characteristics and the changes in PA levels measured by wearable PA trackers can accurately reflect a patient's postoperative recovery status and provide clinically relevant information to aid their management.

Participants will wear PA trackers during the perioperative period of TKA (2 weeks before until 3 months after, and then agin for 2 weeks one year after the surgery) and we will analyze their gait and PA and correlate them with their recovery after surgery.

Condition or Disease Intervention/Treatment Phase
  • Other: Measuring gait

Detailed Description

Introduction

Total knee arthroplasty (TKA) is a common surgical intervention for end-stage knee osteoarthritis (OA) patients who have failed conservative treatments. However, despite advances in surgical techniques and postoperative care, some patients experience complications and delayed recovery, leading to increased healthcare costs and worse clinical outcomes. Therefore, monitoring the postoperative recovery of TKA patients is critical for improving the outcomes and reducing healthcare costs.

Currently, various approaches assess patients' postoperative progress following TKA, including patient- and clinician-reported outcomes, as well as radiographic imaging. However, these methods are typically conducted at limited time intervals, and their objectivity is frequently questioned due to the potential for variability. The physical activity (PA) of patients, particularly walking as the primary form of PA, has proven to be a reliable indicator of their overall health and functionality. Abnormalities in walking patterns or reduced levels of physical activity can indicate decreased compliance, pain, or the occurrence of adverse events. Early diagnosis and treatment are crucial in mitigating the potential consequences of these adverse events, such as pulmonary embolism (PE), deep vein thrombosis (DVT), infection, and others.

In recent years, wearable sensors, such as PA trackers, have emerged as a promising tool for monitoring postoperative recovery. These sensors can continuously and objectively monitor a patient's PA levels and provide data that can be used to track the patients' recovery progress based on their daily activities. Furthermore, studies have demonstrated that patients are able to comply with the use of wearable sensors during the postoperative period after orthopedic surgeries. The investigators have demonstrated the patients' compliance with using the same sensors in a separate study. However, despite the potential benefits of wearable sensors for monitoring TKA recovery, several uncertainties remain. One key issue is whether changes in PA levels and gait alterations detected by wearable sensors can provide a reliable indicator of a patient's postoperative recovery status. Moreover, it is currently unclear whether the data collected from these sensors can yield clinically meaningful information that can effectively aid in managing TKA patients. Further research is needed to address these questions and establish the potential value of wearable sensors in the context of monitoring recovery after TKA.

Therefore, this study aims to investigate the potential of wearable sensors, specifically PA trackers, for monitoring the postoperative recovery of patients after TKA. Our study will recruit patients with knee OA scheduled to undergo TKA and monitor them continuously for three months after surgery using PA trackers. By analyzing the data collected from these trackers, the investigators aim to determine whether alterations in gait characteristics and the changes in PA levels measured by wearable PA trackers can accurately reflect a patient's postoperative recovery status and provide clinically relevant information to aid their management. In addition, in the study the investigators will measure PA and gait accelerations one year after TKA to evaluate the final outcome of the surgery once the recovery period is complete.

Methods

The investigators will use PA trackers to monitor the participants' PA levels. The PA trackers are previously validated sensors (SENS Motion®) designed for monitoring PA in health care and comprise accelerometers. Plasters on the lateral distal thigh will attach the sensors and measure 3D linear accelerations of lower limbs. The linear accelerations will be translated into the amount of PA and the number of steps taken per day by the SENS Motion algorithm.

The investigators will monitor the participants 24/7 using PA trackers from two weeks before surgery until three months after surgery. A two-weeks follow-up measurement will also be performed 12 months after surgery. The study will consist of three data collection periods: pre-op (two weeks), post-op (three months), and 12-months follow-up (two weeks).

  1. Enrollment (Baseline visit)
  • At least two weeks before the surgery, patients will be enrolled in the study and given detailed information about the protocol. Informed consent will be obtained, and basic patient information, including their civil registration number, age, sex, comorbidities, surgical history, height, weight, and lower limb lengths, will be collected. In addition, patients will be given knee injury and osteoarthritis outcome score (KOOS) and European Quality of Life 5 Dimensions 3 Level Version (EQ-5D-3L) questionnaires to complete. The investigators will also evaluate the patients' frailty level using CFS. All data will be recorded in a REDCap database hosted by region of North Jutland, Denmark.

  • The location of the sensors on the distal thigh of the affected knee will be marked, and a PA tracker (SENS Motion) will be attached to the specified location. Patients will then be asked to walk at a self-selected speed for about two minutes to register a template for their walking pattern. The SENS app will be installed on the patients' smartphones. Next, the patients will be instructed on transferring data from sensors' internal memory to the SENS cloud system, changing the adhesives, and attaching the sensor to the exact location specified by the markers. Patients will be provided enough plasters and a marker pen, and instructional material will guide them through the process. Participants will be instructed to wear the devices at all times, even when showering or swimming.

  1. Pre-op period
  • The PA tracker will continuously record the patients' PA levels and lower limb accelerations. The collected data will be transferred daily from the PA tracker to the SENS cloud system.

  • To ensure the accuracy and completeness of the data, the investigators will monitor the data transfer process. Specifically, the data collected by the PA tracker will be transferred from the SENS cloud system to the Q-drive every week. If a participant fails to transfer their data within 72 hours, they will be contacted to remind them to do so.

  • All data collected during pre-op will be used to establish the participants' baseline PA levels. This information will be used as a reference point to assess changes in PA levels and lower limb accelerations after surgery and during the follow-up period.

  1. Operation day

• On the day of the operation, the operation nurse will remove the sensors before surgery and reattach them in the exact location following the procedure. The patient's records will be reviewed to obtain information on the type and duration of surgery, as well as any complications that may have occurred. The data will be recorded in a REDCap database.

  1. Post-op Period
  • After surgery, participants will be instructed to wear the tracker continuously for three months. During the postoperative period, the investigators will closely monitor patients' PA levels. Patients who fail to transfer sensor data within 72 hours will be contacted to ensure continuous data collection. The sensor data will be transferred weekly from the SENS cloud system to Q-drive. The investigators will also administer weekly EQ-5D-3L questionnaires and monthly KOOS questionnaires to assess patients' health status and knee function through the REDCap platform.

  • After three months, the sensors will be turned off and returned to the hospital. The investigators will extract relevant information from patients' records to identify possible complications and classify them based on the standardized list and definitions of the Knee Society 14.

  1. 12-months follow up
  • The follow-up period will consist of an additional two weeks of data collection one year after surgery, during which participants will continue to wear the tracker to assess the changes in PA levels and lower limb accelerations.

  • At the 12-month follow-up, patients will be invited to participate in the follow-up part of the study, and if they consent, they will receive sensors to wear continuously for 14 days. Data will be collected continuously during this period, and KOOS and EQ-5D-3L questionnaires will be administered through REDCap. In addition, the patients' journals will be reviewed for any potential complications.

  • Once the 14-day period is complete, the sensors will be deactivated and returned to the hospital.

Study Design

Study Type:
Observational
Anticipated Enrollment :
30 participants
Observational Model:
Cohort
Time Perspective:
Prospective
Official Title:
Investigating the Potential of Wearable Sensors for Monitoring the Postoperative Recovery of Total Knee Arthroplasty Patients: A Protocol for Prospective Longitudinal Observational Study
Anticipated Study Start Date :
Oct 1, 2023
Anticipated Primary Completion Date :
Oct 1, 2024
Anticipated Study Completion Date :
Oct 1, 2025

Outcome Measures

Primary Outcome Measures

  1. The postoperative daily changes from the baseline (preoperative) Fourier coefficients of walking acceleration signals until 3 months after total knee arthroplasty [Two weeks before the surgery until three months after the surgery]

    3D lower limb accelerations corresponding to walking bouts will be extracted and transformed by Fast Fourier Transform. The first five pairs of Fourier coefficients will be used for data analysis.

  2. The postoperative changes from the baseline (preoperative) Fourier coefficients of walking acceleration signals at 12 months after total knee arthroplasty [Two weeks before and 12 months after the surgery]

    3D lower limb accelerations corresponding to walking bouts will be extracted and transformed by Fast Fourier Transform. The first five pairs of Fourier coefficients will be used for data analysis.

Secondary Outcome Measures

  1. The postoperative daily changes from the baseline (preoperative) cadence until 3 months after total knee arthroplasty [Two weeks before the surgery until three months after the surgery]

    Acceleration data will be analyzed to determine the gait cadence defined as the number of steps taken per minute.

  2. The postoperative daily changes from the baseline (preoperative) stance time until 3 months after total knee arthroplasty [Two weeks before the surgery until three months after the surgery]

    Acceleration data will be analyzed to determine the stance time of the gait described as the percentage of the gait cycle time spent on stance phase.

  3. The postoperative daily changes from the baseline (preoperative) rest time until 3 months after total knee arthroplasty [Two weeks before the surgery until three months after the surgery]

    Acceleration data will be analyzed to determine the proportion of time the patient spent lying down during each day expressed as the percentage.

  4. The postoperative daily changes from the baseline (preoperative) sitting time until 3 months after total knee arthroplasty [Two weeks before the surgery until three months after the surgery]

    Acceleration data will be analyzed to determine the proportion of time the patient spent sitting during each day expressed as the percentage.

  5. The postoperative daily changes from the baseline (preoperative) standing time until 3 months after total knee arthroplasty [Two weeks before the surgery until three months after the surgery]

    Acceleration data will be analyzed to determine the proportion of time the patient spent standing during each day expressed as the percentage.

  6. The postoperative daily changes from the baseline (preoperative) walking time until 3 months after total knee arthroplasty [Two weeks before the surgery until three months after the surgery]

    Acceleration data will be analyzed to determine the proportion of time the patient spent walking during each day expressed as the percentage.

  7. The postoperative daily changes from the baseline (preoperative) step counts until 3 months after total knee arthroplasty [Two weeks before the surgery until three months after the surgery]

    Acceleration data will be analyzed to determine the number of steps the patient takes during each day.

  8. The postoperative daily changes from the baseline (preoperative) sit-to-stand counts until 3 months after total knee arthroplasty [Two weeks before the surgery until three months after the surgery]

    Acceleration data will be analyzed to determine the number of sit-to-stands the patient performs during each day.

  9. The postoperative daily changes from the baseline (preoperative) activity count index until 3 months after total knee arthroplasty [Two weeks before the surgery until three months after the surgery]

    The activity count index will be calculated by using the variance of the magnitude of the linear accelerations and demonstrates the quantitative level of PA.

  10. The postoperative changes from the baseline (preoperative) cadence at 12 months after total knee arthroplasty [Two weeks before and 12 months after the surgery]

    Acceleration data will be analyzed to determine the gait cadence defined as the number of steps taken per minute.

  11. The postoperative changes from the baseline (preoperative) stance time at 12 months after total knee arthroplasty [Two weeks before and 12 months after the surgery]

    Acceleration data will be analyzed to determine the stance time of the gait described as the percentage of the gait cycle time spent on stance phase.

  12. The postoperative changes from the baseline (preoperative) rest time at 12 months after total knee arthroplasty [Two weeks before and 12 months after the surgery]

    Acceleration data will be analyzed to determine the proportion of time the patient spent lying down during each day expressed as the percentage.

  13. The postoperative changes from the baseline (preoperative) sitting time at 12 months after total knee arthroplasty [Two weeks before and 12 months after the surgery]

    Acceleration data will be analyzed to determine the proportion of time the patient spent sitting during each day expressed as the percentage.

  14. The postoperative changes from the baseline (preoperative) standing time at 12 months after total knee arthroplasty [Two weeks before and 12 months after the surgery]

    Acceleration data will be analyzed to determine the proportion of time the patient spent standing during each day expressed as the percentage.

  15. The postoperative changes from the baseline (preoperative) walking time at 12 months after total knee arthroplasty [Two weeks before and 12 months after the surgery]

    Acceleration data will be analyzed to determine the proportion of time the patient spent walking during each day expressed as the percentage.

  16. The postoperative changes from the baseline (preoperative) step counts at 12 months after total knee arthroplasty [Two weeks before and 12 months after the surgery]

    Acceleration data will be analyzed to determine the number of steps the patient takes during each day.

  17. The postoperative changes from the baseline (preoperative) sit-to-stand counts at 12 months after total knee arthroplasty [Two weeks before and 12 months after the surgery]

    Acceleration data will be analyzed to determine the number of sit-to-stands the patient performs during each day.

  18. The postoperative changes from the baseline (preoperative) activity count index at 12 months after total knee arthroplasty [Two weeks before and 12 months after the surgery]

    The activity count index will be calculated by using the variance of the magnitude of the linear accelerations and demonstrates the quantitative level of PA.

  19. The change in KOOS [Baseline (2 weeks before surgery); and 1 month, 2 months, 3 months, and 12 months after the surgery.]

    The KOOS questionnaire is an instrument to assess the patient's opinion about their knee and associated problems. Only the domains evaluating the pain, symptoms and functions of daily activities will be used.

  20. The change in EQ-5D-3L [Baseline (2 weeks before surgery); and 1 month, 2 months, 3 months, and 12 months after the surgery.]

    EQ-5D-3L is a generic tool for Patient Reported Outcomes (PRO) measurement that can assess patients' quality of life, irrespective of the disease.

Eligibility Criteria

Criteria

Ages Eligible for Study:
18 Years and Older
Sexes Eligible for Study:
All
Accepts Healthy Volunteers:
No
Inclusion Criteria:
  • Patients diagnosed with knee OA and scheduled to undergo unilateral TKA at Aalborg University Hospital, Farsø.
Exclusion Criteria:
  • Daily pain (numeric rating scale (NRS) ≥ 4) or severe OA in the contralateral knee (KL-IV)

  • Daily pain (NRS ≥ 4) or severe OA in the spine and other lower limb joints

  • BMI > 35 kg/m2

  • Recent surgery in the spine or lower limbs (< 6 months)

  • Neurological movement disorders

  • Inflammatory arthritis

  • Patients who are not smartphone users

  • Frail patients with clinical frailty scale (CFS)10 ≥ 5

  • Residents of nursing homes

  • Patients dependent to walking aids for ambulation

  • Patients with dementia or memory problems

  • Patients with skin sensitivity or issues at the location of the plasters.

Contacts and Locations

Locations

No locations specified.

Sponsors and Collaborators

  • Aalborg University Hospital
  • Aalborg University

Investigators

  • Principal Investigator: Ole Rahbek, MD, PhD, Aalborg University Hospital

Study Documents (Full-Text)

None provided.

More Information

Publications

Responsible Party:
Ole Rahbek, Professor, Aalborg University Hospital
ClinicalTrials.gov Identifier:
NCT05992064
Other Study ID Numbers:
  • F2022-196
First Posted:
Aug 15, 2023
Last Update Posted:
Aug 15, 2023
Last Verified:
Aug 1, 2023
Individual Participant Data (IPD) Sharing Statement:
Undecided
Plan to Share IPD:
Undecided
Studies a U.S. FDA-regulated Drug Product:
No
Studies a U.S. FDA-regulated Device Product:
No

Study Results

No Results Posted as of Aug 15, 2023