Background:Tendon injury such as tendinopathy or rupture is common and has multiple etiologies, including both intrinsic and extrinsic factors. The genetic influence on susceptibility to tendon injury is not well understood.Purpose:To analyze the published literature regarding genetic factors associated with tendon injury.Study Design:Systematic review; Level of evidence, 3.Methods:A systematic review of published literature was performed in concordance with the Preferred Reporting Items of Systematic Reviews and Meta-analysis (PRISMA) guidelines to identify current evidence for genetic predisposition to tendon injury. PubMed, Ovid, and ScienceDirect databases were searched. Studies were included for review if they specifically addressed genetic factors and tendon injuries in humans. Reviews, animal studies, or studies evaluating the influence of posttranscription factors and modifications (eg, proteins) were excluded.Results:Overall, 460 studies were available for initial review. After application of inclusion and exclusion criteria, 11 articles were ultimately included for qualitative synthesis. Upon screening of references of these 11 articles, an additional 15 studies were included in the final review, for a total of 26 studies. The genetic factors with the strongest evidence of association with tendon injury were those involving type V collagen A1, tenascin-C, matrix metalloproteinase–3, and estrogen-related receptor beta.Conclusion:The published literature is limited to relatively homogenous populations, with only level 3 and level 4 data. Additional research is needed to make further conclusions about the genetic factors involved in tendon injury.

Background Patients often are asked to report walking distances before joint arthroplasty and when discussing their results after surgery, but little evidence demonstrates whether patient responses accurately represent their activity. Questions/purposes Are patients accurate in reporting distance walked, when compared with distance measured by an accelerometer, within a 50% margin of error? Methods Patients undergoing THA or TKA were recruited over a 16-month period. One hundred twenty-one patients were screened and 66 patients (55%) were enrolled. There were no differences in mean age (p = 0.68), proportion of hips versus knees (p = 0.95), or sex (p = 0.16) between screened and enrolled patients. Each patient wore a FitBitTM Zip accelerometer for 1 week and was blinded to its measurements. The patients reported their perceived walking distance in miles daily. Data were collected preoperatively and 6 to 8 weeks postoperatively. Responses were normalized against the accelerometer distances and Wilcoxon one-tailed signed-rank testing was performed to compare the mean patient error with a 50% margin of error, our primary endpoint. Results We found that patients’ self-reported walking distances were not accurate. The mean error of reporting was > 50% both preoperatively (p = 0.002) and postoperatively (p < 0.001). The mean magnitude of error was 69% (SD 58%) preoperatively and 93% (SD 86%) postoperatively and increased with time (p = 0.001). Conclusions Patients’ estimates of daily walking distances differed substantially from those patients’ walking distances as recorded by an accelerometer, the accuracy of which has been validated in treadmill tests. Providers should exercise caution when interpreting patient-reported activity levels. Level of Evidence Level III, diagnostic study.

Background: Orthopaedic residency education requires trainees to participate not only in clinical and research endeavors but also in quality improvement (QI) projects. To our knowledge, little has been published on how to implement a structured QI curriculum as part of an orthopaedic residency program. This article describes a single institution’s experience with developing a longitudinal, integrated, and collaborative resident QI curriculum. Methods: The Six Sigma DMAIC (Define, Measure, Analyze, Improve, and Control) process was taught to residents as a formal curriculum at our institution beginning in 2014. A structured integrated process was developed for residents to work in teams and meet on a monthly basis. Since then, residents have developed multiple QI projects with measured outcomes. Serial surveys have been administered to the residents to collect feedback. Results: Seven major QI projects have been implemented by residents since the program’s initiation. The resident surveys revealed significant improvement in comfort level with organizing QI projects. Residents also reported being comfortable working in interprofessional teams and incorporating patient safety techniques into clinical practice. Conclusions: There are few guidelines that reflect how to initiate a formal QI curriculum in an orthopaedic residency program to promote a standardized and systematic way to approach QI projects. With a structured DMAIC education plan, an emphasis on graded responsibilities within a team setting, and responsiveness to resident feedback, orthopaedic programs can develop an effective QI program to allow residents to learn valuable patient safety practices, which allows residents to have a meaningful and impactful effect on QI initiatives that will serve them well as they enter clinical practice.