Fifty-seven runners were randomly assigned to one of three groups - minimalist shoe walking (MSW), foot strengthening exercise (FS), or control (C). All groups maintained their pre-study running mileage throughout the study. The MSW group walked in provided footwear, increasing weekly the number of steps/day taken in the shoes. The FS group performed a set of progressive resistance exercises at least 5 days/week. Foot muscle strength (via custom dynamometers) and size (via ultrasound) were measured at the beginning (week 0), middle (week 4), and end (week 8) of the study. Mixed model ANOVAs were run to determine if the interventions had differing effects on the groups.Single nucleotide polymorphism; estrogen receptor; muscle stiffness; injury prediction; athletes RESULTS: There were significant group by time interactions for all muscle size and strength measurements. All muscle sizes and strength increased significantly from weeks 0-8 in the FS and MSW groups, while there were no changes in the C group. Some muscles increased in size by week 4 in the FS and MSW groups.Single nucleotide polymorphism; estrogen receptor; muscle stiffness; injury prediction; athletes CONCLUSION: Minimalist shoe walking is as effective as foot strengthening exercises in increasing in foot muscle size and strength. The convenience of changing footwear rather than performing specific exercises may result in greater compliance.

BackgroundQuantifying the strength of the intrinsic foot muscles has been a challenge for clinicians and researchers. The reliable measurement of this strength is important in order to assess weakness, which may contribute to a variety of functional issues in the foot and lower leg, including plantar fasciitis and hallux valgus. This study reports 3 novel methods for measuring foot strength – doming (previously unmeasured), hallux flexion, and flexion of the lesser toes.MethodsTwenty-one healthy volunteers performed the strength tests during two testing sessions which occurred one to five days apart. Each participant performed each series of strength tests (doming, hallux flexion, and lesser toe flexion) four times during the first testing session (twice with each of two raters) and two times during the second testing session (once with each rater). Intra-class correlation coefficients were calculated to test for reliability for the following comparisons: between raters during the same testing session on the same day (inter-rater, intra-day, intra-session), between raters on different days (inter-rater, inter-day, inter-session), between days for the same rater (intra-rater, inter-day, inter-session), and between sessions on the same day by the same rater (intra-rater, intra-day, inter-session).ResultsICCs showed good to excellent reliability for all tests between days, raters, and sessions. Average doming strength was 99.96 ± 47.04 N. Average hallux flexion strength was 65.66 ± 24.5 N. Average lateral toe flexion was 50.96 ± 22.54 N.ConclusionsThese simple tests using relatively low cost equipment can be used for research or clinical purposes. If repeated testing will be conducted on the same participant, it is suggested that the same researcher or clinician perform the testing each time for optimal reliability.

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Background: When performing revision shoulder arthroplasty, surgeons do not have access to the results of intraoperative culture specimens and will administer empiric antibiotics to cover for the possibility of deep infection until the culture results are finalized. The purpose of this study was to report the factors associated with the initiation, modification, and adverse events of 2 different postoperative antibiotic protocols in a series of revision shoulder arthroplasties. Methods: In this study, 175 patients undergoing revision shoulder arthroplasty were treated with either a protocol of intravenous (IV) antibiotics if there was a high index of suspicion for infection or a protocol of oral antibiotics if the index of suspicion was low. Antibiotics were withdrawn if cultures were negative and were modified as indicated if the cultures were positive. Antibiotic course, modification, and adverse effects to antibiotic administration were documented. Results: On univariate analysis, factors significantly associated with the initiation of IV antibiotics were male sex (p < 0.001), history of infection (p < 0.001), intraoperative humeral loosening (p = 0.003), and membrane formation (p < 0.001). On multivariate analysis, male sex (p = 0.003), history of infection (p = 0.003), and membrane formation (p < 0.001) were found to be independent predictors of the initiation of IV antibiotics. On the basis of preoperative and intraoperative characteristics, surgeons anticipated the culture results in 75% of cases, and modification of antibiotic therapy was required in 25%. The modification from oral to IV antibiotics due to positive culture results was made significantly more often in male patients (p < 0.001). Adverse effects of antibiotic administration occurred in 19% of patients. The rates of complications were significantly lower in the patients treated with oral antibiotics and a shorter course of antibiotics (p < 0.001). Conclusions: Complications associated with antibiotic administration after revision shoulder arthroplasty are not infrequent and are more common in patients whose initial protocol is IV antibiotics. Further study is needed to balance the effectiveness and risks of post-revision antibiotic treatment given the frequency of antibiotic-related complications. Level of Evidence: Therapeutic Level IV. See Instructions for Authors for a complete description of levels of evidence.

PurposeThis study sought to develop and internally validate a machine learning model to identify risk factors and quantify overall risk of secondary meniscus injury in a longitudinal cohort after primary ACL reconstruction (ACLR). MethodsPatients with new ACL injury between 1990 and 2016 with minimum 2‐year follow‐up were identified. Records were extensively reviewed to extract demographic, treatment, and diagnosis of new meniscus injury following ACLR. Four candidate machine learning algorithms were evaluated to predict secondary meniscus tears. Performance was assessed through discrimination using area under the receiver operating characteristics curve (AUROC), calibration, and decision curve analysis; interpretability was enhanced utilizing global variable importance plots and partial dependence curves. ResultsA total of 1187 patients underwent ACLR; 139 (11.7%) experienced a secondary meniscus tear at a mean time of 65 months post‐op. The best performing model for predicting secondary meniscus tear was the random forest (AUROC = 0.790, 95% CI: 0.785–0.795; calibration intercept = 0.006, 95% CI: 0.005–0.007, calibration slope = 0.961 95% CI: 0.956–0.965, Brier’s score = 0.10 95% CI: 0.09–0.12), and all four machine learning algorithms outperformed traditional logistic regression. The following risk factors were identified: shorter time to return to sport (RTS), lower VAS at injury, increased time from injury to surgery, older age at injury, and proximal ACL tear. ConclusionMachine learning models outperformed traditional prediction models and identified multiple risk factors for secondary meniscus tears after ACLR. Following careful external validation, these models can be deployed to provide real‐time quantifiable risk for counseling and timely intervention to help guide patient expectations and possibly improve clinical outcomes. Level of evidenceIII.