Robotic arthroplasty software training improves understanding of total knee arthroplasty alignment and balancing principles: a randomized controlled trial.

Understanding alignment and gap balancing in Total Knee Arthroplasty (TKA) can be challenging for trainee and experienced orthopedic surgeons. Traditional learning methods may not effectively translate to real-life scenarios. The advent of advanced technologies like robotic surgery and navigation systems has revolutionized intraoperative understanding of gap balancing techniques. This trial aims to investigate the effectiveness of robotic TKA planning software in educating trainees about alignment and ligament balancing. We hypothesize that a single session with the software will significantly enhance trainees' understanding of these techniques. This UK-based single-center, two-arm, group parallel randomized controlled trial was conducted during a national robotic arthroplasty symposium. It aims to evaluate the effect of robotic knee arthroplasty software training on understanding TKA alignment and gap balancing principles using Multiple Choice Questions (MCQs). The MCQ test was crafted based on established guidelines from a different institution with expert consensus in the field. Our study revealed that baseline knowledge of gap balancing and alignment principles was generally low among all participants. However, the intervention group, which received comprehensive robotic software training, demonstrated a significant improvement in their MCQ scores compared to the control group, which did not undergo the training. In conclusion, our study demonstrates that robotic arthroplasty software training significantly improves the understanding of TKA alignment and balancing principles among orthopedic trainees. Level of Evidence II.

Sulforaphane and Sulforaphane-Nitrile Metabolism in Humans Following Broccoli Sprout Consumption: Inter-individual Variation, Association with Gut Microbiome Composition, and Differential Bioactivity.

SCOPE: The glucosinolate glucoraphanin from broccoli is converted to sulforaphane (SFN) or sulforaphane-nitrile (SFN-NIT) by plant enzymes or the gut microbiome. Human feeding studies typically observe high inter-individual variation in absorption and excretion of SFN, however, the source of this variation is not fully known. To address this, a human feeding trial to comprehensively evaluate inter-individual variation in the absorption and excretion of all known SFN metabolites in urine, plasma, and stool, and tested the hypothesis that gut microbiome composition influences inter-individual variation in total SFN excretion has been conducted. METHODS AND RESULTS: Participants (n = 55) consumed a single serving of broccoli or alfalfa sprouts and plasma, stool, and total urine are collected over 72 h for quantification of SFN metabolites and gut microbiome profiling using 16S gene sequencing. SFN-NIT excretion is markedly slower than SFN excretion (72 h vs 24 h). Members of genus Bifidobacterium, Dorea, and Ruminococcus torques are positively associated with SFN metabolite excretion while members of genus Alistipes and Blautia has a negative association. CONCLUSION: This is the first report of SFN-NIT metabolite levels in human plasma, urine, and stool following consumption of broccoli sprouts. The results help explain factors driving inter-individual variation in SFN metabolism and are relevant for precision nutrition.