Seasonal Allergy Induced Back Pain: A Report of Two Cases

BACKGROUND: Precision in glenoid baseplate placement is paramount to optimize fixation and longevity of reverse total shoulder arthroplasty (rTSA). Robotic assistance has recently been shown to improve mean accuracy in component positioning, but its most meaningful benefit may be the prevention of severe outliers-the "tail-risk" events that disproportionately compromise outcomes and inflate costs. This study sought to quantify and compare the frequency of outliers across 3 glenoid preparation techniques: manual, manual assisted with patient-specific instrumentation (PSI), and robotic arm-assisted preparation using the Mako System (Stryker, Kalamazoo, MI). METHODS: Using data from a comparative study of bone matrix models, we performed Monte Carlo simulations of 100,000 glenoid baseplate implantations per technique (manual, PSI, robotic-assisted). Parameters compared across techniques included glenoid component version, inclination, anteroposterior translation, superoinferior translation, and depth of reaming. Outliers were prespecified as cases exceeding both >10° angulation and >5 mm translation deviations from the pre-operative plan. RESULTS: The modeled error distributions narrowed progressively from manual to PSI to robotic techniques. Outlier frequencies were 24% for manual, 2% for PSI, and 0% for robotic assistance (95% confidence interval, 23.9%-24.5%; 1.85%-2.02%; 0.00%-0.0038%, respectively). Robotic assistance completely eliminated outlier malposition events. CONCLUSION: Mako robotic-assisted glenoid preparation in reverse total shoulder arthroplasty appears to virtually eliminate the occurrence of high-risk baseplate malposition outliers. When value is framed through tail-risk rather than mean accuracy, the principal contribution of robotic assistance in shoulder arthroplasty lies in risk containment, with potential, although unproven to date, clinical and economic implications. Further research linking its use to patient outcomes is warranted, as it may ultimately redefine the technology's value proposition.