Evaluation of spin in systematic reviews and meta-analyses involving glenoid augmentation in total shoulder arthroplasty
Year: 2025
Type: review
Abstract: Background: Spin in scientific literature is defined as bias that overstates efficacy and/or underestimates harms of an experimental treatment. Glenoid augmentation is a technique used to correct glenoid bone deficiency during shoulder surgery. Literature on the outcomes of glenoid augmentation in total shoulder arthroplasty (TSA) is limited, which may lead to a risk of bias in systematic reviews and meta-analyses in this topic. The goal of this study is to identify the quantity and types of spin in systematic reviews and meta-analyses of glenoid augmentation in TSA. Methods: A search was conducted on the PubMed, Scopus, and SPORTDiscus databases for systematic reviews and meta-analyses evaluating outcomes of glenoid augmentation in TSA. The abstract of each study was assessed for the 15 most common types of spin using the method proposed by Yavchitz et al Study quality was assessed per A Measurement Tool to Assess Systematic Reviews 2. Fisher's exact tests were performed to investigate relationships between general characteristics and spin types. Results: Thirteen (81.3%) of the 16 included studies were found to have at least one form of spin. The most common type of spin was type 5 ("the conclusion claims the beneficial effect of the experimental treatment despite a high risk of bias in primary studies"), which appeared in 7 studies (43.8%). There was a statistically significant association between the presence of a conflict of interest and the lack of reporting funding sources. Conclusion: Spin is highly prevalent in the abstracts of systematic reviews and meta-analyses studying glenoid augmentation with TSA. Misleading reporting is the most common category of spin.
Source: JSES International
Authors: Christopher J. Lamb, Brett M. Biedermann, Eric H. Lin, Amir Fathi, Christian Cruz, Frank A. Petrigliano, Joseph N. Liu
Institution: University of Southern California
Language: English
Subfield: Statistics, Probability and Uncertainty
Field: Decision Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $1,250
OpenAlex ID: W4408966355
