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Machine learning (ML) studies are becoming increasingly popular in orthopedics but lack a critically appraisal of their adherence to peer‐reviewed guidelines. The objective of this review was to (1) evaluate quality and transparent reporting of ML prediction models in orthopedic surgery based on the transparent reporting of multivariable prediction models for individual prognosis or diagnosis (TRIPOD), and (2) assess risk of bias with the Prediction model Risk Of Bias ASsessment Tool. A systematic review was performed to identify all ML prediction studies published in orthopedic surgery through June 18th, 2020. After screening 7138 studies, 59 studies met the study criteria and were included. Two reviewers independently extracted data and discrepancies were resolved by discussion with at least two additional reviewers present. Across all studies, the overall median completeness for the TRIPOD checklist was 53% (interquartile range 47%–60%). The overall risk of bias was low in 44% (n = 26), high in 41% (n = 24), and unclear in 15% (n = 9). High overall risk of bias was driven by incomplete reporting of performance measures, inadequate handling of missing data, and use of small datasets with inadequate outcome numbers. Although the number of ML studies in orthopedic surgery is increasing rapidly, over 40% of the existing models are at high risk of bias. Furthermore, over half incompletely reported their methods and/or performance measures. Until these issues are adequately addressed to give patients and providers trust in ML models, a considerable gap remains between the development of ML prediction models and their implementation in orthopedic practice. [ABSTRACT FROM AUTHOR]

Introduction: Deformity of the spinal column after trauma could lead to pain, impaired function, and may sometimes necessitate extensive and high-risk surgery. This 'condition' has multiple terms and definitions that are used in research and clinics. A specific term and definition of this condition however is still lacking. A uniform and internationally accepted term and definition are necessary to compare cases and treatments in the future., Research Question: Reach consensus on the term and definition of this deformity after spine trauma using a Delphi approach., Material and Methods: An 'all-rounds invitation' Delphi process was used in this study among a group of international experts. The first round consisted of an online survey using input from preparatory studies, a typical clinical case and ICD-11 codes. The second round showed the results in-person and discussion was encouraged. Participants voted for rejection of certain terms. In the third round the final vote took place. When >80 % of the votes was for or against a term the term was rejected or accepted., Results: Response rate was high (≥84 %). The 3 Delphi rounds were completed. Unanimous voting led to the acceptance of the term and abbreviation as PSD. Deformity in any plane, pain, impaired function, and neurological deficit, were deemed important to include in the definition of PSD., Discussion and Conclusion: Unanimous consensus was reached on 'Posttraumatic spinal deformity: Condition where a trauma to the spine results in a deformity in any plane and results in pain and an impaired function with or without a neurological deficit.', Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Editorial Capacity of FC Oner in special issue If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)