The Learning Curve in Orthopaedic Robotic Arthroplasty: A Systematic Review

Robotic-assisted arthroplasty has been adopted rapidly across orthopaedic surgery on the premise that it improves the accuracy of bone preparation and implant positioning. Introducing any new intraoperative technology, however, imposes a learning curve: a period during which operative time, workflow, and potentially accuracy and safety differ from a surgeon's established steady-state performance. Quantifying this learning curve matters for surgical training, credentialing, theatre scheduling, and the fair interpretation of early comparative outcomes, yet published estimates vary widely in both magnitude and the methods used to derive them. Existing syntheses have generally been confined to a single procedure (most often total knee arthroplasty) or a single platform, have applied inconsistent definitions of the learning-curve endpoint, and have not reliably separated inflection-based thresholds (the case number at which operative time stops falling) from time-neutrality thresholds (the case number at which robotic operative time matches the conventional technique). The purpose of this systematic review and descriptive meta-analysis is to establish, across procedures and platforms, how many cases are required to traverse the operative-time learning curve in orthopaedic robotic arthroplasty, and to examine whether this threshold differs by procedure (hip, knee, shoulder), by robotic platform, or by imaging modality (image-based versus imageless). A secondary purpose is to characterise the broader, non-poolable evidence on implant and component positioning accuracy, patient-reported and functional outcomes, and complication and revision rates in relation to surgical experience. The review searches four databases (Ovid MEDLINE, Embase, Web of Science Core Collection, and Google Scholar), appraises included studies with ROBINS-I and RoB 2, and synthesises learning-curve thresholds descriptively using the median and interquartile range as the primary summary, because these thresholds are right-skewed and individual studies do not report a standard error, so a conventional inverse-variance meta-analysis is not appropriate. Inflection-based and time-neutrality endpoints are analysed separately as non-equivalent outcomes, and the certainty of the evidence is rated using GRADE. The expected outcomes are a pooled descriptive estimate of the operative-time learning-curve threshold with its interquartile range; pre-specified subgroup comparisons by procedure, platform, and imaging modality; a structured narrative synthesis of positioning accuracy, patient-reported outcomes, and complications; an assessment of small-study and reporting bias using a sample-size-based funnel plot and Spearman rank correlation; and a GRADE-rated summary of certainty for each main outcome. We anticipate that the findings will provide training programmes, credentialing bodies, and practising surgeons with an evidence-based benchmark for the number of cases needed to reach proficiency, and will clarify the extent to which the learning curve is modified by the specific procedure, device, and imaging approach.