Fig 1.
Our population started with 2,752 patients who underwent arthroscopic rotator cuff repair, 1,586 were excluded according to the exclusion criteria. The final eligible cohort comprised 1,166 full-thickness repairs, which were stratified by mediolateral tear size into small (≤10 mm), medium (11–29 mm), and large (30–50 mm) tears. Tear size–specific multivariable logistic regression and binned χ² threshold analyses were performed within each subgroup.
Table 1.
Baseline characteristics by tear size group. Continuous variables are reported as mean ± standard deviation (SD) unless otherwise specified; number of anchors and symptom duration are reported as median (interquartile range [IQR]). Categorical variables are reported as number (percentage).
Fig 2.
Structural retear rates by tear size.
Bar graph demonstrating the proportion of patients with structural retear identified on 6-month postoperative ultrasound, stratified by mediolateral tear size. Retear rates increased with increasing tear size, supporting tear-size–specific evaluation of factors associated with repair failure.
Table 2.
Factors associated with structural retear. Separate models were fitted within each tear size group (Small, Medium, Large). Results are reported as ORs with 95% confidence intervals (CIs) and corresponding p-values. These analyses assess associations and were not intended for prediction.
Fig 3.
Factors associated with structural retear.
Forest plot showing odds ratios (ORs) with 95% confidence intervals from tear size–stratified multivariable logistic regression models evaluating factors associated with structural retear at 6 months following arthroscopic rotator cuff repair. Models were adjusted for demographic, surgical, tear-related, and preoperative clinical variables and fitted separately for small, medium, and large tears. An OR greater than 1 indicates increased odds of retear.
Table 3.
Factors associated with postoperative satisfaction. Separate models were fitted within each tear size group. Results are presented as ORs with 95% CIs and p-values. These models evaluate associations rather than predictive performance.
Fig 4.
Factors associated with postoperative satisfaction.
Forest plot showing odds ratios (ORs) with 95% confidence intervals from tear size–stratified multivariable logistic regression models evaluating factors associated with postoperative satisfaction at 6 months. Satisfaction was dichotomized as Good (scores 3–4) versus Poor (scores 0–2). Models were adjusted for demographic, surgical, tear-related, and preoperative clinical factors. An OR greater than 1 indicates increased odds of good postoperative satisfaction.