• BACKGROUND
    • The purpose of this study was to evaluate the prognostic value of the lateralization shoulder angle (LSA) and distalization shoulder angle (DSA) following reverse total shoulder arthroplasty (rTSA).
  • METHODS
    • This systematic review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. PubMed, Cochrane Central Register of Controlled Trials, and Scopus were queried on February 18, 2024. The inclusion criteria encompassed studies reporting correlations between LSA, DSA, and patient-reported outcome scores in patients undergoing rTSA with a minimum follow-up of 2 years. Study quality was evaluated using the Methodological Index for Non-Randomized Studies score. Meta-analysis was performed using a random-effects model with correlation coefficients (r) calculated via Fisher's z-transformation. Heterogeneity was assessed with the Q test and I2 values.
  • RESULTS
    • After screening, 4 studies met inclusion criteria, representing a total of 974 shoulders with a minimum follow-up of 24 months. The studies included retrospective cohort designs with Methodological Index for Non-Randomized Studies scores ranging from 14 to 15. Meta-analysis revealed no significant correlation between LSA or DSA and functional outcomes (American Shoulder and Elbow Surgeons score, Constant score) or range of motion (ROM) (active anterior elevation [AAE] and active external rotation). The overall correlation coefficient for LSA and DSA with postoperative outcomes was 0.023 (95% confidence interval [CI]: -0.056 to 0.101, P = .572). Similarly, no significant correlations were found between LSA or DSA and AAE or active external rotation, with the random effects model showing an effect size of -0.097 (95% CI: -0.231 to 0.037, P = .156) for AAE and DSA and 0.056 (95% CI: -0.052 to 0.165, P = .309) for AAE and LSA.
  • CONCLUSION
    • DSA and LSA may not predict the postoperative range of motion or clinical outcomes following rTSA. Future studies are warranted to develop and validate measurements of that can be used to help optimize patient outcomes.