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Learning curve for robotic-assisted total knee arthroplasty

Filippo Migliorini et al · BMC · 2026

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Abstract Introduction The learning curve refers to the relationship between a learner's execution of a task and the number of attempts or time necessary to perform it in a predictable, reliable, and optimal fashion. The learner's competence in a task should improve over time as they execute the job more frequently. The present investigation aims to clarify the learning curve associated with robotic-assisted total knee arthroplasty (TKA). Methods Consecutive patients undergoing total knee arthroplasty at the Department of Orthopaedic Surgery, Eifelklinik St. Brigida, Simmerath, Germany, between 2021 and 2025 were prospectively screened for participation in this clinical study. All procedures were performed through a medial parapatellar approach, following a functional alignment strategy. Implantation was performed in accordance with the manufacturer’s recommendations using the Smith & Nephew Legion Genesis II system with a posterior-stabilised polyethylene insert. Both femoral and tibial components were cemented with Palacos cement (Heraeus Medical GmbH, Wehrheim, Germany). Postoperative physiotherapy followed the standard institutional protocol. At hospital admission, demographic variables including age, body mass index (BMI), and sex were recorded. Operative time was documented for each procedure and defined as the interval from skin incision to completion of wound closure. Results The first 200 robotic-assisted TKAs were monitored. 66% (112 of 200 patients) were women, and 47.5% (95 of 200 TKAs) were performed on the right side. The mean age of the patients was 68.6 ± 8.1 years, and their BMI was 28.6 kg/m². The exponential decay model revealed a characteristic learning curve, characterised by initial rapid gains followed by a plateau. The estimated asymptotic operative time was approximately 89.2 minutes, with a learning rate coefficient of 0.035. This implies that the majority of efficiency improvements occur early, but meaningful reductions persist beyond the 20th case. Block-wise comparisons supported the existence of an earlier functional learning threshold. Statistically significant reductions in operative time, compared with the first 10 cases, were observed from the 41st to 50th procedure block (p = 0.02), with stabilisation in the 90-minute range thereafter. Conclusion The most efficient gains occur early, and operative times stabilise at around 90 minutes after approximately 40 procedures. Registration German Registry of Clinical Trials (ID DRKS00030614).

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APA 7

al, F. M. E. (2026). Learning curve for robotic-assisted total knee arthroplasty. https://doi.org/10.1186/s13018-026-06835-y

MLA

al, Filippo Migliorini et. "Learning curve for robotic-assisted total knee arthroplasty." 2026. https://doi.org/10.1186/s13018-026-06835-y.

Chicago

al, Filippo Migliorini et. 2026. "Learning curve for robotic-assisted total knee arthroplasty.". https://doi.org/10.1186/s13018-026-06835-y.

Harvard

al, F. M. E. 2026, Learning curve for robotic-assisted total knee arthroplasty, BMC, available at: https://doi.org/10.1186/s13018-026-06835-y [Accessed 7 Aug. 2026].

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Titolo
Learning curve for robotic-assisted total knee arthroplasty
Autore / collaboratori
Filippo Migliorini et al
Editore
BMC
Anno di pubblicazione
2026
ISSN
1749-799X
ISSN
1749-799X
Lingua
Inglés

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