Rehabilitation Protocols Following Patellar Instability Surgery: A Structured Review of Published Recommendations and AI Generated Guidance.
Journal:
Current reviews in musculoskeletal medicine
Published Date:
Jun 8, 2026
Abstract
PURPOSE OF REVIEW: To review postoperative rehabilitation protocols after surgery for patellar instability, including medial patellofemoral ligament reconstruction (MPFLR), tibial tubercle osteotomy (TTO), trochleoplasty, and combined procedures. A secondary aim was to compare published recommendations with guidance generated by selected artificial intelligence (AI) platforms. RECENT FINDINGS: Sixty three protocol entries were included: 35 isolated MPFLR, 9 isolated TTO, 4 isolated trochleoplasty, and 15 combined procedures. Isolated MPFLR showed the most consistent rehabilitation pattern, favoring immediate weight bearing as tolerated (66%, p < 0.001), locked bracing for up to 6 weeks (63%, p < 0.001), and full ROM by 6 to 12 weeks (51%, p = 0.002). Isolated TTO protocols recommended delayed or non weight bearing (56%), locked brace duration greater than 6 weeks (67%), and full ROM by 6 to 12 weeks (44%), with no significant predominance (all p > 0.05). Trochleoplasty protocols were too few and heterogeneous. Combined procedures were mostly protective but variable overall. RTS criteria were mostly time, functional, and strength based (76%-89%), whereas psychological readiness (43%) and physician approval (22%) were infrequent. AI generated protocols broadly reproduced MPFLR rehabilitation principles but lacked procedure specific differentiation. Rehabilitation protocols following patellar instability surgery remain highly variable, particularly for non MPFLR procedures. Isolated MPFLR protocols generally follow a more structured and accelerated pathway, whereas rehabilitation after TTO, trochleoplasty, and combined procedures remains less clearly defined and more protective. RTS decisions rely mainly on time, strength, and functional based criteria, whereas psychological readiness remains underutilized. AI based tools may serve as supportive decision making aids but currently require integration with clinical judgment and procedure-specific expertise.
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