Robotic assistance reduces operative time variability in reverse shoulder arthroplasty: a retrospective single-surgeon study.

BACKGROUND

Robotic assistance for reverse total shoulder arthroplasty (rTSA) improves the accuracy and consistency of implant positioning, but whether this reproducibility extends to the surgical workflow is unknown. This study sought to compare operative time variability between conventional and robotic-assisted rTSA using the Mako robotic system (Stryker, Kalamazoo, MI).

METHODS

We retrospectively reviewed consecutive elective primary rTSAs performed by a single fellowship-trained shoulder surgeon. Operative time was defined as incision start to incision closure. The first 23 robotic-assisted cases using the Mako robotic system were designated the learning phase based on a prior internal operative time learning curve analysis and were excluded. Post-learning curve robotic-assisted cases were compared with conventional cases from the same period. The primary outcome was operative time variability, quantified using the standard deviation (SD) and coefficient of variation, and compared with the Brown-Forsythe test and the variance ratio with 95% confidence interval (CI). Native glenoid retroversion and RSA angle were compared as markers of case complexity.

RESULTS

Thirty-nine robotic-assisted cases were compared with 38 conventional cases. Robotic operative time was substantially less variable than conventional operative time (SD 9.9 vs. 19.7 min; coefficient of variation 13.3% vs. 25.0%; variance ratio 4.01; 95% CI, 2.09-7.69; Brown-Forsythe P < .001), while mean operative time was equivalent (74.2 vs. 78.8 min; P = .20). The groups did not differ in native glenoid retroversion (9.2° vs. 8.7°; P = .77) or RSA angle (14.3° vs. 15.1°; P = .57).

CONCLUSION

Robotic-assisted rTSA was associated with more consistent operative times than conventional rTSA, with no significant difference in mean operative time. These findings suggest that the value of robotic assistance in rTSA may extend beyond implant positioning to the reproducibility of surgical workflow.