How Much Will High Tension Adversely Affect Rotator Cuff Repair Integrity?

Abstract

To suggest a cutoff value of tension related to retear of a repaired chronically contracted rotator cuff and to analyze the correlation between predictive factors and integrity of repair in large to massive contracted rotator cuff tears (RCTs). We analyzed arthroscopic rotator cuff repairs for large to massive (>3 cm) contracted RCTs, not amenable to complete repair by standard means with meticulous release, with a minimum of 1 year follow-up. An intraoperative procedure was designed for the estimation of repair tension using a tensiometer. Clinical and radiological findings were compared between the healed group and the retear group, and magnetic resonance imaging was performed ∼1 year postoperatively for the evaluation of integrity of the repair site. The receiver operating characteristic curve was used to identify the cutoff value of the independent factors. Factors affecting postoperative retear were examined with multivariate analysis. Fifty patients were enrolled in this study and divided into the healed group (31 patients) and the retear group (19 patients) according to the follow-up magnetic resonance imaging findings. Significant results showed that tension (5.13 < 95% confidence interval [CI] < 58.15, P < .001) and acromiohumeral interval (AHI) (1.13 < 95% CI < 33.10, P = .013) were important factors for the integrity of rotator cuff repair. The cutoff value of tension was 35 N, and an AHI <6.6 mm may also be considered a predictor of retear. An occupation ratio of the tension >35 N was the strongest predictor of retear, with an area under the curve of 0.799, sensitivity of 84.2%, and specificity of 67.7% (accuracy = 76.0%). The integrity of a large to massive rotator cuff repair is strongly related to the tension to reach the articular margin of the footprint and AHI. We found that the possibility of retear increases when tension ≥35 N is required. AHI <6.6 mm may also be considered a predictor of retear. Level III, retrospective cohort design.