Back

A Comparison between Evidence-Generated Transtibial Sockets and Conventional CADCAM Designs, from the Patient's Perspective

Mbithi, F.; Donovan-Hall, M.; Bramley, J.; Steer, J.; Rossides, C.; Worsley, P.; Ostler, C.; Metcalf, C.; Hannett, D.; Ward, C.; Kitchen, J.; Steventon, S.; McIntosh, K.; Guo, S.; Harvey, H.; Henderson Slater, D.; Kolli, V.; Dickinson, A.

2024-09-18 rehabilitation medicine and physical therapy
10.1101/2024.09.17.24312762 medRxiv
Show abstract

ObjectivePersonalised prosthetic socket design depends upon skilled prosthetists who aim to balance functional human-prosthesis coupling with safe, comfortable load transmission to skin and soft tissues. This studys objective was to assess the comfort of sockets generated from past computer aided socket design records. DesignA crossover non-inferiority trial with embedded qualitative interview study. SettingThree United Kingdom National Health Service clinics. ParticipantsSeventeen people with nineteen transtibial amputations. InterventionEvidence-Generated sockets and conventional clinician-led computer aided (Control) designs Main MeasuresSocket Comfort Score and semi-structured interview. ResultsEvidence-Generated sockets had no statistically-significant difference in comfort compared to clinician-led Control sockets (p=0.38, effect size=0.08), but a lower socket comfort score variability across the group. Analysis of interviews revealed themes around fitting session experiences, similarities and differences between the Evidence-Generated and Control sockets, and residual limb factors impacting perceptions of socket comfort. These provided insights into the participants experience of the study and the value of expert prosthetist input in socket design. ConclusionsEvidence-Generated sockets demonstrated noninferiority to conventional clinical computer aided design practice in terms of socket comfort. Both quantitative and qualitative results indicated how clinician input remains essential and is valued by prosthesis users. Work is underway to incorporate the evidence-generated sockets into computer aided design software such that they can act as a digital starting point for modification by expert clinicians at fitting, potentially reducing time spent on basic design, enabling prosthetists to focus on more highly-skilled customisation and co-design with their patients.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.