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Evidence-Based Clinical Management of Orthopaedic Trauma: 25 Years in Retrospect,...
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Evidence-Based Clinical Management of Orthopaedic Trauma: 25 Years in Retrospect, and a Forecast of 25 Years to Come

A special issue of Journal of Clinical Medicine (ISSN 2077-0383). This special issue belongs to the section "Orthopedics".

Deadline for manuscript submissions: 25 June 2025 | Viewed by 2535

Special Issue Editors

Prof. Dr. Dirk Stengel

E-Mail Website
Guest Editor
BG Kliniken—Klinikverbund der Gesetzlichen Unfallversicherung gGmbH (Hospital Group of the German Social Accident Insurance), Leipziger Pl. 1, 10117 Berlin, Germany
Interests: clinical trials; systematic reviews; meta-analyses; diagnostic tests; radiological imaging; ultrasonography; multiple trauma; musculoskeletal injuries; septic surgery
Prof. Dr. Paul Alfred Grützner

E-Mail Website
Guest Editor
Department for Trauma and Orthopaedic Surgery, BG Trauma Center Ludwigshafen, University of Heidelberg, Ludwigshafen on the Rhine, Ludwigshafen, Germany
Interests: polytrauma; joint fractures; imaging; orthogeriatrics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In 2025, we look back on 25 years of evidence-based orthopaedic surgery. We will celebrate this anniversary by holding a scientific symposium with renowned guest-speakers at the BG Klinikum Unfallkrankenhaus Berlin, a leading tertiary-care trauma centre in the capital of Germany. This Special Issue is intended to accompany the event, depict the current state-of-the art, and pave the way for future research. Transferring the principles of evidence-based medicine to the surgical disciplines has already turned out to be difficult, and appeared almost impossible in the setting of orthopaedic and multiple trauma. Yet, major international consortia were formed, enabling cutting-edge multicentre trials which fundamentally changed our understanding of established care processes and improved patient outcomes. Novel clinical trial concepts, innovative methods to model large-scale routine data, molecular and personalized medicine, artificial intelligence, etc., will further boost our knowledge in future. We invite systematic reviews and meta-analyses on major issues in orthopaedic trauma, reports of randomized trials, and large-scale observational data.

We look forward to your submissions!

Prof. Dr. Dirk Stengel
Prof. Dr. Paul Alfred Grützner
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Clinical Medicine is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Publisher’s Notice

All papers submitted to this Special Issue are reviewed by independent referees, and the final decision is made by a Journal of Clinical Medicine Editorial Board Member who does not have any conflict of interest with the submission. 

Keywords

  • evidence-based medicine
  • orthopaedic surgery
  • clinical trials
  • systematic reviews
  • patient outcomes
  • multiple trauma
  • artificial intelligence
  • injuries

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Published Papers (3 papers)

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Research

15 pages, 2975 KiB  
Article
The Power of Heuristics in Predicting Fracture Nonunion
by Jonas Armbruster, Eva Steinhausen, Simon Hackl, Marie K. Reumann, Dirk Stengel, Frank Niemeyer, Gregor Reiter, Paul Alfred Gruetzner and Holger Freischmidt
J. Clin. Med. 2025, 14(8), 2713; https://doi.org/10.3390/jcm14082713 - 15 Apr 2025
Viewed by 174
Abstract
Background/Objectives: Although extensive research on risk factors for nonunion development has been published, clinicians frequently rely on heuristic reasoning—intuitive, experience-based decision-making—to predict nonunions. However, the accuracy of these intuitive assessments and the influence of clinician experience remain uncertain. This study aims to assess [...] Read more.
Background/Objectives: Although extensive research on risk factors for nonunion development has been published, clinicians frequently rely on heuristic reasoning—intuitive, experience-based decision-making—to predict nonunions. However, the accuracy of these intuitive assessments and the influence of clinician experience remain uncertain. This study aims to assess clinicians’ diagnostic accuracy in predicting nonunion, investigate the impact of experience on predictive performance, and identify patient-specific factors contributing to diagnostic errors. Methods: This retrospective, multi-center cohort study included 98 patients with surgically treated tibial shaft fractures between 2018 and 2023 from four level-one trauma centers in Germany. Fracture outcomes were classified as either nonunion (n = 20) or regular fracture healing (n = 78). Patient cases were presented to 24 clinicians. Each clinician independently assessed preoperative and postoperative biplanar X-rays and patient histories to predict fracture healing. Results: Clinicians’ sensitivity significantly improved from 50.4% to 60.2%, while specificity declined (74.0% to 70.7%) with the addition of postoperative information. No significant differences in predictive performance were observed across different levels of clinician experience. Changes in assessment after reviewing postoperative information were equally likely to be beneficial or detrimental. Certain patient factors, including obesity and smoking, influenced prediction errors. Conclusions: This study is the first to assess heuristic reasoning in nonunion prediction. The findings suggest that clinician experience does not significantly enhance diagnostic accuracy under limited-information conditions. Patients should be informed that predicting individual nonunion risk remains challenging. Larger studies are needed to explore the role of patient-specific factors and refine clinical decision-making in fracture healing prognosis. Full article
(This article belongs to the Special Issue Evidence-Based Clinical Management of Orthopaedic Trauma: 25 Years in Retrospect, and a Forecast of 25 Years to Come)
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9 pages, 1209 KiB  
Article
Patient Recruitment Characteristics for Wearable-Sensor-Based Outcome Assessment in Trauma Surgery
by Benedikt J. Braun, Kira Hofmann, Chiara N. Meierhofer, Maximilian M. Menger, Tanja C. Maisenbacher, Carolina Vogel, Dannik Haas, Meir T. Marmor, Tina Histing, Eva-Marie Braun and The AO Smart Digital Solutions Task Force
J. Clin. Med. 2025, 14(3), 805; https://doi.org/10.3390/jcm14030805 - 26 Jan 2025
Viewed by 606
Abstract
Background/Objectives: Using a patient’s own wearable sensor to obtain objective outcome data is a growing field in trauma allowing for the assessment of the recovery trajectory back toward the pre-injury performance. The aim of this study was to analyze recruitment characteristics and reasons [...] Read more.
Background/Objectives: Using a patient’s own wearable sensor to obtain objective outcome data is a growing field in trauma allowing for the assessment of the recovery trajectory back toward the pre-injury performance. The aim of this study was to analyze recruitment characteristics and reasons for declined study participation in an orthopedic trauma study that measures postoperative recovery using wearables. Methods: Data from 225 patients screened for participation in a wearable-sensor-based outcome study were assessed. The influence of age, sex and injury location on study participation was analyzed. Reasons for patients declining to participate were investigated from the screening log. Availability and type of sensor system in patients agreeing to participate were analyzed. Results: Overall, 48% of patients agreed to participate. Age was the only significantly different factor between agreeing and declining patients (p < 0.05). The main reasons to decline study participation were technical difficulties with or inability to use the wearable device, lack of availability of a wearable, and general disinterest to participate in a study. Notably, 7% declined due to data safety concerns. Conclusions: The results show that age, availability of the wearable, and technical ability to use a wearable are the main obstacles impacting objective outcome measurement using a personal wearable device. In studies including geriatric patients, a dedicated device requiring no patient handling can be a valid option to improve enrollment. Understanding the reasons for declining to participate will facilitate the development of future sensor-based studies to address concerns of technical handling through alternative means of data harvesting and increase the inclusion rate. These outcomes will guide future study designs to optimize patient inclusion. Full article
(This article belongs to the Special Issue Evidence-Based Clinical Management of Orthopaedic Trauma: 25 Years in Retrospect, and a Forecast of 25 Years to Come)
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11 pages, 880 KiB  
Article
Discrepancies in ChatGPT’s Hip Fracture Recommendations in Older Adults for 2021 AAOS Evidence-Based Guidelines
by Hong Jin Kim, Pil Whan Yoon, Jae Youn Yoon, Hyungtae Kim, Young Jin Choi, Sangyoon Park and Jun-Ki Moon
J. Clin. Med. 2024, 13(19), 5971; https://doi.org/10.3390/jcm13195971 - 8 Oct 2024
Cited by 2 | Viewed by 1260
Abstract
Background: This study aimed to assess the reproducibility and reliability of Chat-Based GPT (ChatGPT)’s responses to 19 statements regarding the management of hip fractures in older adults as adopted by the American Academy of Orthopaedic Surgeons’ (AAOS) evidence-based clinical practice guidelines. Methods [...] Read more.
Background: This study aimed to assess the reproducibility and reliability of Chat-Based GPT (ChatGPT)’s responses to 19 statements regarding the management of hip fractures in older adults as adopted by the American Academy of Orthopaedic Surgeons’ (AAOS) evidence-based clinical practice guidelines. Methods: Nineteen statements were obtained from the 2021 AAOS evidence-based clinical practice guidelines. After generating questions based on these 19 statements, we set a prompt for both the GPT-4o and GPT-4 models. We repeated this process three times at 24 h intervals for both models, producing outputs A, B, and C. ChatGPT’s performance, the intra-ChatGPT reliability, and the accuracy rates were assessed to evaluate the reproducibility and reliability of the hip fracture-related guidelines. Regarding the strengths of the recommendation compared with the 2021 AAOS guidelines, we observed accuracy of 0.684, 0.579, and 0.632 for outputs A, B, and C, respectively. Results: The precision was 0.740, 0.737, and 0.718 in outputs A, B, and C, respectively. For the reliability of the strengths of the recommendation, the Fleiss kappa was 0.409, indicating a moderate level of agreement. No statistical differences in the strengths of the recommendation were observed in outputs A, B, and C between the GPT-4o and GPT-4 versions. Conclusion: ChatGPT may be useful in providing guidelines for hip fractures but performs poorly in terms of accuracy and precision. However, hallucinations remain an unresolved limitation associated with using ChatGPT to search for hip fracture guidelines. The effective utilization of ChatGPT as a patient education tool for the management of hip fractures should be addressed in the future. Full article
(This article belongs to the Special Issue Evidence-Based Clinical Management of Orthopaedic Trauma: 25 Years in Retrospect, and a Forecast of 25 Years to Come)
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