The purpose of this study is to determine whether simulation training improves the performance during arthroscopic surgery ('keyhole' surgery into a joint).
This single blinded randomised controlled study of junior orthopaedic trainees aims to assess whether the addition of simulation training improves arthroscopic technical skills performance of junior orthopaedic trainees during knee arthroscopy in the operating theatre compared to their usual clinical training programme. This will be assessed using objective motion analysis parameters recorded from wireless elbow-mounted motion sensors during surgery.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
OTHER
Masking
SINGLE
Enrollment
30
Simulation training in a skills lab for 1 hour per week over 13 weeks on dry, bench-top box trainers and anatomical simulators
Nuffield Orthopaedic Centre
Oxford, Oxfordshire, United Kingdom
Number of Hand Movements Required by Participants to Perform a Diagnostic Arthroscopy of the Knee in Theatre
Wireless elbow-mounted accelerometer and gyroscopic sensors worn by the participant will generate 6 degree of freedom motion data (three rotational degrees around the x, y and z axes, known as 'roll', 'pitch', and 'yaw', and three translational degrees of freedom along x, y and z axes, known as 'surge', 'sway' and 'heave') which will be analysed using validated, bespoke algorithms to calculate the number of hand movements taken whilst performing a diagnostic knee arthroscopy according to a standardised protocol.
Time frame: 3 months
Smoothness of Hand Movements by Participants to Perform a Diagnostic Arthroscopy of the Knee in Theatre
Wireless elbow-mounted accelerometer and gyroscopic sensors worn by the participant will generate 6 degree of freedom motion data which will be analysed using validated, bespoke algorithms to calculate the smoothness (also known as 'jerk', the first derivative of acceleration by time, or third derivative of distance by time) of hand movements taken whilst performing a diagnostic knee arthroscopy according to a standardised protocol according to a standardised protocol.
Time frame: 3 months
Time Taken by Participants to Perform a Diagnostic Arthroscopy of the Knee in Theatre
Wireless elbow-mounted accelerometer and gyroscopic sensors worn by the participant will generate 6 degree of freedom motion data which will be analysed using validated, bespoke algorithms. These data will also collect time signatures, which can be used to work out the time taken by participants to perform a diagnostic arthroscopy of the knee in theatre according to a standardised protocol.
Time frame: 3 months
Minor Hand Movements Required by Participants to Perform a Diagnostic Arthroscopy of the Knee in Theatre
Wireless elbow-mounted accelerometer and gyroscopic sensors worn by the participant will generate 6 degree of freedom motion data (three rotational degrees around the x, y and z axes, known as 'roll', 'pitch', and 'yaw', and three translational degrees of freedom along x, y and z axes, known as 'surge', 'sway' and 'heave') which will be analysed using validated, bespoke algorithms to calculate the number of movements (below the threshold for 'hand movements' above in outcome 1, but above the data noise threshold) taken whilst performing a diagnostic knee arthroscopy according to a standardised protocol.
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Time frame: 3 months
Stationary Time of Participants to Perform a Diagnostic Arthroscopy of the Knee in Theatre
Wireless elbow-mounted accelerometer and gyroscopic sensors worn by the participant will generate 6 degree of freedom motion data which will be analysed using validated, bespoke algorithms. These data will also collect time signatures, which can be used to work out the length of time during the procedure where each hand is stationary while participants perform a diagnostic arthroscopy of the knee in theatre according to a standardised protocol.
Time frame: 3 months
Idle Time of Participants to Perform a Diagnostic Arthroscopy of the Knee in Theatre
Wireless elbow-mounted accelerometer and gyroscopic sensors worn by the participant will generate 6 degree of freedom motion data which will be analysed using validated, bespoke algorithms. These data will also collect time signatures, which can be used to work out the length of time during the procedure where both hands are stationary at the same time while participants perform a diagnostic arthroscopy of the knee in theatre according to a standardised protocol.
Time frame: 3 months
Dominance of Participants to Perform a Diagnostic Arthroscopy of the Knee in Theatre
Wireless elbow-mounted accelerometer and gyroscopic sensors worn by the participant will generate 6 degree of freedom motion data which will be analysed using validated, bespoke algorithms. These data will be analysed for the relative activity and dominance of each hand during the procedure while participants perform a diagnostic arthroscopy of the knee in theatre according to a standardised protocol.
Time frame: 3 months
Global Rating Scale Performance During Diagnostic Knee Arthroscopy in Theatre
Validated global rating scale for assessing diagnostic knee arthroscopy performance
Time frame: 3 months
Deviation From 'Idealised' Motion Parameters for Participants to Perform a Diagnostic Arthroscopy of the Knee in Theatre
Previously described motion parameters of participants performing a diagnostic knee arthroscopy in theatre (see Primary outcome 1, and secondary outcomes 2-8) reported as a ratio to the 'ideal' performance as measured from the supervising clinician performing an optimal diagnostic knee arthroscopy on the same patient as the participant while wearing the wireless elbow-mounted accelerometer and gyroscopic sensors which will record 6 degree of freedom motion data to allow calculation of 'number of hand movements', 'smoothness', 'time taken', 'minor hand movements', 'stationary time', 'idle time' and dominance'
Time frame: 3 months
Motion Analysis Parameters During Simulation
Change in participant performance on dry, bench top box trainers and anatomical simulators between baseline and 3 months using motion analysis parameters described in Primary outcome 1 and secondary outcomes 2-8 as measured by wireless elbow-mounted accelerometer and gyroscopic sensors
Time frame: 3 months
Resting State Network Functional Changes on fMRI (Functional Magnetic Resonance Imaging)
Use of MELODIC (Multivariate Exploratory Linear Optimized Decomposition into Independent Components) to identify resting state networks, and analyse differences in functional connectivity at baseline and three months between the intervention and control arms.
Time frame: 3 months
Voxel Based Morphometry Structural Changes on fMRI (Functional Magnetic Resonance Imaging)
Using FSLVBM (fMRIB's Software Library Voxel Based Morphometry) to calculate voxel-wise changes in grey matter volumes at baseline and three months between the intervention and control arms. Changes in VBM imply changes in grey matter volume and represent structural brain change.
Time frame: 3 months
Diffusion Tractography Structural Changes on fMRI (Functional Magnetic Resonance Imaging)
Using FDT (fMRIB's Diffusion Toolbox) to model local diffusion and changes in tractography at baseline and three months between the intervention and control arms. Changes in diffusion imply micro-structural (axonal) connectivity and represent structural brain change.
Time frame: 3 months
Quantitative Magnetisation Transfer Structural Changes on fMRI (Functional Magnetic Resonance Imaging)
Quantitative magnetisation transfer imaging estimates liquid and semisolid (macromolecular) constituents of tissue at baseline and three months between the intervention and control arms. Changes in macromolecular content imply micro-structural (myelin) connectivity and represent structural brain change.
Time frame: 3 months
Feasibility of Additional Simulation Training
Qualitative survey of participants opinions of the addition of simulation to their usual clinical training programme
Time frame: 3 months