This study aimed to gather insights from elbow experts using the Delphi method to evaluate the influence of patient characteristics and fracture morphology on the choice between operative and nonoperative treatment for coronoid fractures. A three-round electronic (e-)modified Delphi survey study was performed between March and December 2023. A total of 55 elbow surgeons from Asia, Australia, Europe, and North America participated, with 48 completing all questionnaires (87%). The panellists evaluated the factors identified as important in literature for treatment decision-making, using a Likert scale ranging from "strongly influences me to recommend nonoperative treatment" (1) to "strongly influences me to recommend operative treatment" (5). Factors achieving Likert scores ≤ 2.0 or ≥ 4.0 were deemed influential for treatment recommendation. Stable consensus is defined as an agreement of ≥ 80% in the second and third rounds.Aims
Methods
The aim of this study was to define the complications and long-term outcome following adolescent mid-shaft clavicular fracture. We retrospectively reviewed a consecutive series of 677 adolescent fractures in 671 patients presenting to our region (age 13 to 17 years) over a ten-year period (2009 to 2019). Long-term patient-reported outcomes (abbreviated version of the Disabilities of the Arm, Shoulder and Hand (QuickDASH) score and EuroQol five-dimension three-level (EQ-5D-3L) quality of life score) were undertaken at a mean of 6.4 years (1.2 to 11.3) following injury in severely displaced mid-shaft fractures (Edinburgh 2B) and angulated mid-shaft fractures (Edinburgh 2A2) at a minimum of one year post-injury. The median patient age was 14.8 years (interquartile range (IQR) 14.0 to 15.7) and 89% were male (n = 594/671).Aims
Methods
The aim of this study was to explore why some calcar screws are malpositioned when a proximal humeral fracture is treated by internal fixation with a locking plate, and to identify risk factors for this phenomenon. Some suggestions can be made of ways to avoid this error. We retrospectively identified all proximal humeral fractures treated in our institution between October 2016 and October 2018 using the hospital information system. The patients’ medical and radiological data were collected, and we divided potential risk factors into two groups: preoperative factors and intraoperative factors. Preoperative factors included age, sex, height, weight, body mass index, proximal humeral bone mineral density, type of fracture, the condition of the medial hinge, and medial metaphyseal head extension. Intraoperative factors included the grade of surgeon, neck-shaft angle after reduction, humeral head height, restoration of medial support, and quality of reduction. Adjusted binary logistic regression and multivariate logistic regression models were used to identify pre- and intraoperative risk factors. Area under the curve (AUC) analysis was used to evaluate the discriminative ability of the multivariable model.Aims
Methods
