Editorial Commentary: Shifting From Redundancy to Rigor in Orthopaedic Large Language Model Research

Large language model (LLM) research in musculoskeletal medicine is growing rapidly, but much of the literature remains methodologically weak and highly repetitive. To address this, the orthopaedic LLM research community needs a shared benchmarking infrastructure/framework to evaluate models on clinically grounded tasks using fixed-prompt templates and transparent scoring. Drawing on established LLM benchmarking practices, such a framework would enable reproducibility, discourage cherry-picking, and promote meaningful innovation. Like surgical registries in orthopaedics, open LLM benchmarks can clarify performance, guide adoption, and ensure that progress is both measurable and clinically relevant.