Learning curve for active robotic total knee arthroplasty

Autor: William J. Long, Siddharth A. Mahure, Stefan Kreuzer, Bernard N. Stulberg, Yair D Kissin, Greg M. Teo
Rok vydání: 2021
Předmět:
Zdroj: Knee Surgery, Sports Traumatology, Arthroscopy. 30:2666-2676
ISSN: 1433-7347
0942-2056
DOI: 10.1007/s00167-021-06452-8
Popis: Total Knee Arthroplasty (TKA) procedures incorporate technology in an attempt to improve outcomes. The Active Robot (ARo) performs a TKA with automated resections of the tibia and femur in efforts to optimize bone cuts. Evaluating the Learning Curve (LC) is essential with a novel tool. The purpose of this study was to assess the associated LC of ARo for TKA. A multi-center prospective FDA cohort study was conducted from 2017 to 2018 including 115 patients that underwent ARo. Surgical time of the ARo was defined as Operative time (OT), segmented as surgeon-dependent time (patient preparation and registration) and surgeon-independent time (autonomous bone resection by the ARo). An average LC for all surgeons was computed. Complication rates and patient-reported outcome (PRO) scores were recorded and examined to evaluate for any LC trends in these patient related factors. The OT for the cases 10–12 were significantly quicker than the OT time of cases 1–3 (p
Databáze: OpenAIRE
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