Navigating the learning curve: assessing caseload and comparing outcomes before and after the learning curve of
Christian J Hecht Ii1, Joshua R Porto1, Parshva A Sanghvi1
1Department of Orthopaedic Surgery, Center for Hip Preservation, Orthopaedic and Rheumatologic Institute, Cleveland Clinic Foundation, 9500 Euclid Avenue, Mail Code A41, Cleveland, OH, 44195, USA.
Purpose:
Computer-navigated (CN) total hip arthroplasty (THA) offers improved acetabular component placement and radiographic outcomes, but inconsistent assessment methods of its learning curves render the evaluation of adopting a novel platform challenging. Therefore, we conducted a systematic review to assess the learning curve associated with CN-THA, both tracking a surgeon's performance across initial cases and comparing their performance to manual THA (M-THA).
Methods:
A search was conducted using PubMed, MEDLINE, EBSCOhost, and Google Scholar on June 16, 2023 to find research articles published after January 1, 2000 (PROSPERO registration: CRD4202339403) that investigated the learning curve associated with CN-THA. 655 distinct articles were retrieved and subsequently screened for eligibility. In the final analysis, nine publications totaling 847 THAs were evaluated. The Methodological Index for Nonrandomized Studies (MINORS) tool was utilized to evaluate the potential for bias, with the mean MINORS score of 21.3 ± 1.2.
Results:
CN-THA showed early advantages to M-THA for component placement accuracy and radiographic outcomes but longer operative times (+ 3- 20 min). There was a learning curve required to achieve peak proficiency in these metrics, though mixed methodologies made the required caseload unclear.
Conclusions:
CN-THA offers immediate advantages to M-THA for component placement accuracy and radiographic outcomes, though CN-THA's advantages become more pronounced with experience. Surgeons should anticipate longer operative times during the learning curve for CN-THA, which lessen following a modest caseload. A more thorough evaluation of novel computer-navigated technologies would be enhanced by adopting a more uniform method of defining learning curves for outcomes of interest. Registration PROSPERO registration of the study protocol: CRD42023394031, 27 June 2023.
