The elbow is prone to stiffness due to its unique anatomy and profound capsular reaction to inflammation. The resulting movement impairment may significantly interfere with a patient’s activities of daily living. Trauma (including surgery for trauma), posttraumatic arthritis, and heterotopic ossification (HO) are the most common causes of elbow stiffness. In stiffness caused by soft tissue contractures, initial conservative treatment with physiotherapy (PT) and splinting is advised. In cases in which osseous deformities limit range of motion (e.g. malunion, osseous impingement, or HO), early surgical intervention is recommended. Open and arthroscopic arthrolysis are the primary surgical options. Arthroscopic arthrolysis has a lower complication and revision rate but has narrower indications. Early active mobilization using PT after surgery is recommended in postoperative rehabilitation and may be complemented by splinting or continuous passive motion therapy. Most results are gained within the first few months but can continue to improve until 12 months. This paper reviews the current literature and provides state-of-the-art guidance on the management regarding prevention, evaluation, and treatment of elbow stiffness.

Osseous deformities in children arise due to progressive angular growth or complete physeal arrest. Clinical and radiological alignment measurements help to provide an impression of the deformity, which can be corrected using guided growth techniques. However, little is known about timing and techniques for the upper extremity. Treatment options for deformity correction include monitoring of the deformity, (hemi-)epiphysiodesis, physeal bar resection, and correction osteotomy. Treatment is dependent on the extent and location of the deformity, physeal involvement, presence of a physeal bar, patient age, and predicted length inequality at skeletal maturity. An accurate estimation of the projected limb or bone length inequality is crucial for optimal timing of the intervention. The Paley multiplier method remains the most accurate and simple method for calculating limb growth. While the multiplier method is accurate for calculating growth prior to the growth spurt, measuring peak height velocity (PHV) is superior to chronological age after the onset of the growth spurt. PHV is closely related to skeletal age in children. The Sauvegrain method of skeletal age assessment using elbow radiographs is possibly a simpler and more reliable method than the method by Greulich and Pyle using hand radiographs. PHV-derived multipliers need to be developed for the Sauvegrain method for a more accurate calculation of limb growth during the growth spurt. This paper provides a review of the current literature on the clinical and radiological evaluation of normal upper extremity alignment and aims to provide state-of-the-art directions on deformity evaluation, treatment options, and optimal timing of these options during growth.

Re-displacement of a pediatric diaphyseal forearm fracture can lead to a malunion with symptomatic impairment in forearm rotation, which may require a corrective osteotomy. Corrective osteotomy with two-dimensional (2D) radiographic planning for malunited pediatric forearm fractures can be a complex procedure due to multiplanar deformities. Three-dimensional (3D) corrective osteotomy can aid the surgeon in planning and obtaining a more accurate correction and better forearm rotation. This prospective study aimed to assess the accuracy of correction after 3D corrective osteotomy for pediatric forearm malunion and if anatomic correction influences the functional outcome. Our primary outcome measures were the residual maximum deformity angle (MDA) and malrotation after 3D corrective osteotomy. Post-operative MDA > 5° or residual malrotation > 15° were defined as non-anatomic corrections. Our secondary outcome measure was the gain in pro-supination. Between 2016–2018, fifteen patients underwent 3D corrective osteotomies for pediatric malunited diaphyseal both-bone fractures. Three-dimensional corrective osteotomies provided anatomic correction in 10 out of 15 patients. Anatomic corrections resulted in a greater gain in pro-supination than non-anatomic corrections: 70° versus 46° (p = 0.04, ANOVA). Residual malrotation of the radius was associated with inferior gain in pro-supination (p = 0.03, multi-variate linear regression). Three-dimensional corrective osteotomy for pediatric forearm malunion reliably provided an accurate correction, which led to a close-to-normal forearm rotation. Non-anatomic correction, especially residual malrotation of the radius, leads to inferior functional outcomes.

Background: For bone morphology and biomechanics analysis, landmarks are essential to define position, orientation, and shape. These landmarks define bone and joint coordinate systems and are widely used in these research fields. Currently, no method is known for automatically identifying landmarks on virtual 3D bone models of the radius and ulna. This paper proposes a knowledge-based method for locating landmarks and calculating a coordinate system for the radius, ulna, and combined forearm bones, which is essential for measuring forearm function. This method does not rely on pre-labeled data. Validation: The algorithm is validated by comparing the landmarks placed by the algorithm with the mean position of landmarks placed by a group of experts on cadaveric specimens regarding distance and orientation. Results: The median Euclidean distance differences between all the automated and reference landmarks range from 0.4 to 1.8 millimeters. The median angular differences of the coordinate system of the radius and ulna range from -1.4 to 0.6 degrees. The forearm coordinate system’s median errors range from -0.2 to 2.0 degrees. The median error in calculating the rotational position of the radius relative to the ulna is 1.8 degrees. Conclusion: The automatic method’s applicability depends on the use context and desired accuracy. However, the current method is a validated first step in the automatic analysis of the three-dimensional forearm anatomy.

Background and purpose: For medial knee osteoarthritis (OA), operative and nonoperative treatment options are available. Two widely applied unloading therapies are a valgus unloader brace and a high tibial osteotomy (HTO). We aimed to compare the effects of a valgus unloader knee brace with an HTO on knee pain after 1 year in patients with symptomatic medial knee OA.Methods: We recruited patients from 9 Dutch hospitals between August 2014 and February 2019 for an open-labeled multi-center randomized controlled trial (Dutch Trial Register NL4200). Patients aged 18 to 65 years with symptomatic medial compartmental knee OA were randomized to either a valgus unloader brace or an HTO. The primary outcome was the pain subscale of the Knee injury and Osteoarthritis Outcome score (KOOS) after 1 year. Patients were evaluated at 3, 6, 9, 12, and 24 months.Results: 51 patients were included in the study, of whom 23 were randomized to the unloader brace and 28 to the HTO. The HTO, compared with the unloader brace, showed a significant and clinically relevant difference at 12 months of follow-up in KOOS pain of –28 (95% confidence interval –43 to –13).Conclusion: We found that, on group level, an HTO is more effective in reducing knee pain than an unloader brace after 12 months.

Purpose: This study aims to develop and externally validate a treatment algorithm to predict nonoperative treatment success or failure in patients with anterior cruciate ligament (ACL) rupture.Methods: Data were used from two completed studies of adult patients with ACL ruptures: the Conservative versus Operative Methods for Patients with ACL Rupture Evaluation study (development cohort) and the KNee osteoArthritis anterior cruciate Ligament Lesion study (validation cohort). The primary outcome variable is nonoperative treatment success or failure. Potential predictor variables were collected, entered into the univariable logistic regression model and then incorporated into the multivariable logistic regression model for constructing the treatment algorithm. Finally, predictive performance and goodness‐of‐fit were assessed and externally validated by discrimination and calibration measures.Results: In the univariable logistic regression model, a stable knee measured with the pivot shift test and a posttrauma International Knee Documentation Committee (IKDC) score 30 years and a body mass index > 30 kg/m² were predictive for not needing an ACL reconstruction. Age, pretrauma Tegner score, the outcome of the pivot shift test and the posttrauma IKDC score are entered into the treatment algorithm. The predictability of needing an ACL reconstruction after nonoperative treatment (discrimination) is acceptable in both the development and the validation cohort: area under the curve = resp. 0.69 (95% confidence interval [CI]: 0.58–0.81) and 0.68 (95% CI: 0.58–0.78).Conclusion: This study shows that the treatment algorithm can acceptably predict whether an ACL injury patient will have a(n) (un)successful nonoperative treatment (discrimination). Calibration of the treatment algorithm suggests a systematical underestimation of the need for ACL reconstruction. Given the limitations regarding the sample size of this study, larger data sets must be constructed to improve the treatment algorithm further.Level of Evidence: Level II.