Using a cadaver shoulder instability model and load-testing device, we compared biomechanical characteristics of double-row and single-row capsulolabral repairs. We hypothesized a greater reduction in glenohumeral motion and translation and a higher load to failure in a mattress double-row capsulolabral repair than in a single-row repair.
In 6 matched pairs of cadaveric shoulders, a capsulolabral injury was created. One shoulder was repaired with a single-row technique, and the other with a double-row mattress technique. Rotational range of motion, anterior-inferior translation, and humeral head kinematics were measured. Load-to-failure testing measured stiffness, yield load, deformation at yield load, energy absorbed at yield load, load to failure, deformation at ultimate load, and energy absorbed at ultimate load.
Double-row repair significantly decreased external rotation and total range of motion compared with single-row repair. Both repairs decreased anterior-inferior translation compared with the capsulolabral-injured condition, however, no differences existed between repair types. Yield load in the single-row group was 171.3 ± 110.1 N, and in the double-row group it was 216.1 ± 83.1 N (P = .02). Ultimate load to failure in the single-row group was 224.5 ± 121.0 N, and in the double-row group it was 373.9 ± 172.0 N (P = .05). Energy absorbed at ultimate load in the single-row group was 1,745.4 ± 1,462.9 N-mm, and in the double-row group it was 4,649.8 ± 1,930.8 N-mm (P = .02).
In cases of capsulolabral disruption, double-row repair techniques may result in decreased shoulder rotational range of motion and improved load-to-failure characteristics.
In cases of capsulolabral disruption, repair techniques with double-row mattress repair may provide more secure fixation. Double-row capsulolabral repair decreases shoulder motion and increases load to failure, yield load, and energy absorbed at yield load more than single-row repair.
This research output has an Altmetric Attention Score of 6. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 December 2016.
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