Summary Full-thickness tears to the rotator cuff can cause severe pain and disability. Untreated tears progress in size and are associated with muscle atrophy and an infiltration of fat to the area, a condition known as “fatty degeneration.” To improve the treatment of rotator cuff tears, a greater understanding of the changes in the contractile properties of muscle fibers and the molecular regulation of fatty degeneration is essential. Using a rat model of rotator cuff injury, we measured the force generating capacity of individual muscle fibers and determined changes in muscle fiber type distribution that develop after a full thickness rotator cuff tear. We also measured the expression of mRNA and miRNA transcripts involved in muscle atrophy, lipid accumulation, and matrix synthesis. We hypothesized that a decrease in specific force of rotator cuff muscle fibers, an accumulation of type IIb fibers, an upregulation in fibrogenic, adipogenic, and inflammatory gene expression occur in torn rotator cuff muscles. Thirty days following rotator cuff tear, we observed a reduction in muscle fiber force production, an induction of fibrogenic, adipogenic and autophagocytic mRNA and miRNA molecules, and a dramatic accumulation of macrophages in areas of fat accumulation.

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Background Preoperative radiographic templating for total knee arthroplasty (TKA) has been shown to be inaccurate. Patient demographic data, such as gender, height, weight, age, and race, may be more predictive of implanted component size in TKA. Materials and methods A multivariate linear regression model was designed to predict implanted femoral and tibial component size using demographic data along a consecutive series of 201 patients undergoing index TKA. Traditional, two-dimensional, radiographic templating was compared to demographic-based regression predictions on a prospective 181 consecutive patients undergoing index TKA in their ability to accurately predict intraoperative implanted sizes. Surgeons were blinded of any predictions. Results Patient gender, height, weight, age, and ethnicity/race were predictive of implanted TKA component size. The regression model more accurately predicted implanted component size compared to radiographically templated sizes for both the femoral (P = 0.04) and tibial (P < 0.01) components. The regression model exactly predicted femoral and tibial component sizes in 43.7 and 43.7% of cases, was within one size 90.1 and 95.6% of the time, and was within two sizes in every case. Radiographic templating exactly predicted 35.4 and 36.5% of cases, was within one size 86.2 and 85.1% of the time, and varied up to four sizes for both the femoral and tibial components. The regression model averaged within 0.66 and 0.61 sizes, versus 0.81 and 0.81 sizes for radiographic templating for femoral and tibial components. Conclusions A demographic-based regression model was created based on patient-specific demographic data to predict femoral and tibial TKA component sizes. In a prospective patient series, the regression model more accurately and precisely predicted implanted component sizes compared to radiographic templating. Level of evidence Prospective cohort, level II.

Background: Publications regarding anatomic total shoulder arthroplasty (TSA) have consistently reported that they provide significant improvement for patients with glenohumeral arthritis. New TSA technologies that have been introduced with the goal of further improving these outcomes include preoperative computed tomography (CT) scans, 3-dimensional preoperative planning, patient-specific instrumentation, stemless and short-stemmed humeral components, as well as metal-backed, hybrid, and augmented glenoid components. The benefit of these new technologies in terms of patientreported outcomes is unknown.Methods: We reviewed 114 articles presenting preoperative and postoperative values for commonly used patientreported metrics. The results were analyzed to determine whether patient outcomes have improved over the 20 years during which new technologies became available.Results: The analysis did not identify evidence that the results of TSA were statistically or clinically improved over the 2 decades of study or that any of the individual technologies were associated with significant improvement in patient outcomes.Conclusions: Additional research is required to document the clinical value of these new technologies to patients with glenohumeral arthritis.