Rotator cuff tears are common upper-extremity injuries that significantly impair shoulder function, leading to pain, reduced range of motion, and a decrease in quality of life. With the increasing reliance on artificial intelligence large language models (AI LLMs) for health information, it is crucial to evaluate the quality and readability of the information provided by these models. A pool of 50 questions was generated related to rotator cuff tear by querying popular AI LLMs (ChatGPT 3.5, ChatGPT 4, Gemini, and Microsoft CoPilot) and using Google search. After that, responses from the AI LLMs were saved and evaluated. For information quality the DISCERN tool and a Likert Scale was used, for readability the Patient Education Materials Assessment Tool for Printable Materials (PEMAT) Understandability Score and the Flesch-Kincaid Reading Ease Score was used. Two orthopedic surgeons assessed the responses, and discrepancies were resolved by a senior author. Out of 198 answers, the median DISCERN score was 40, with 56.6% considered sufficient. The Likert Scale showed 96% sufficiency. The median PEMAT Understandability score was 83.33, with 77.3% sufficiency, while the Flesch-Kincaid Reading Ease score had a median of 42.05 with 88.9% sufficiency. Overall, 39.8% of the answers were sufficient in both information quality and readability. Differences were found among AI models in DISCERN, Likert, PEMAT Understandability, and Flesch-Kincaid scores. AI LLMs generally cannot offer sufficient information quality and readability. While they are not ready for use in medical field, they show a promising future. There is a necessity for continuous re-evaluation of these models due to their rapid evolution. Developing new, comprehensive tools for evaluating medical information quality and readability is crucial for ensuring these models can effectively support patient education. Future research should focus on enhancing readability and consistent information quality to better serve patients.

Accurate component placement in shoulder arthroplasty is crucial for avoiding complications, achieving superior biomechanical performance and optimizing functional outcomes. Shoulder and elbow surgeons have explored various methods to improve surgical understanding and precise execution including preoperative planning with 3D computed tomography (CT), patient-specific instrumentation (PSI), intraoperative navigation, and mixed reality (MR). 3D preoperative planning facilitated by CT scans and advanced software, enhances surgical precision, influences decision-making for implant types and approaches, reduces errors in guide pin placement, and contributes to cost-effectiveness. Navigation demonstrates benefits in reducing malpositioning, optimizing baseplate stability, improving humeral cut, and potentially conserving bone stock, although challenges such as varied operating times and costs warrant further investigation. The personalized patient care and enhanced operational efficiency associated with PSI are not only attractive for achieving desired component positions but also hold promise for improved outcomes in complex cases involving glenoid bone loss. Augmented reality (AR) and virtual reality (VR) technologies play a pivotal role in reshaping shoulder arthroplasty. They offer benefits in preoperative planning, intraoperative guidance, and interactive surgery. Studies demonstrate their effectiveness in AR-guided guidewire placement, providing real-time surgical advice during reverse total shoulder arthroplasty (RTSA). Additionally, these technologies show promise in orthopedic training, delivering superior realism and accelerating learning compared to conventional methods.

Background: Supracondylar humerus fractures (SCHFs) are the most common injuires of the elbow in children, often categorized by the Gartland classification. While type 1 and 2 fractures commonly managed conservatively, type 3 and 4 fractures typically require surgical treatment. Although closed reduction and percutaneous pinning have shown success, open reduction may be required in cases where adequate reduction cannot be achieved. This study aims to identify radiological and clinical risk factors associated with transitioning from closed reduction to open reduction in Gartland type 3 and 4 SCHF in children. Study Design and Methods: We retrospectively analysed 159 patients operated on between 2014 and 2022 for Gartland type 3 and 4 SCHF. Parameters including age, gender, injury severity, time to surgery, neurovascular damage, medial spike angle, fracture-skin distance, medial-lateral deviation, rotation, fracture level, and Baumann angle were evaluated. Results: A total of 159 SCHF in children aged 3 to 12 years, classified as Gartland type 3 (106 patients, 66.6%) and type 4 (53 patients 33.4%), underwent surgical intervention. Notably, 46 patients (28.9%) initially managed with closed reduction exhibited failure, prompting the necessity for conversion to open reduction. Injury severity, lateral deviation, advanced age, low medial spike angle, and low fracture tip-to-skin distance were found to be factors that could potentially increase the need for open reduction (P<0.05). Logistic regression analysis showed that the low medial spike angle, flexion type injury, and low fracture type increased the likelihood of open surgery (P<0.05). Sex, side, duration to surgery, and Baumann angle showed no significant associations. Conclusions: SCHF commonly necessitate surgical intervention in children. Although the risk factors for failed closed reduction and the need for open surgery have been discussed in the literature, there is no consensus. Preoperative planning, particularly for patients with specific factors like lateral deviation, advanced age, low medial spike angle, low fracture-to-skin distance and high injury severity, should consider potential open surgery requirements. Level of Evidence: Level III

The posterior cruciate ligament (PCL) is a vital knee stabilizer. While PCL injuries are rare, high-energy traumas can lead to total ruptures, with accompanying injuries requiring surgery. This study aims to investigate the demographics, concomitant injuries, and postoperative complications of patients who underwent PCL reconstruction due to high-energy trauma in a large patient sample. Patients who underwent PCL reconstruction from 2016 to 2022 were retrospectively evaluated using data from a nationwide personal health recording system. Patient demographics, injury mechanisms, associated fractures, soft tissue injuries, and postoperative complications were collected from patient notes, clinical visits, and surgical notes. Individuals with a PCL injury following high-energy trauma (car accident, falls from height, motorcycle accident) with a minimum follow-up of 1 year were included in the study. The study included 416 patients with a mean age of 32.4 years. Isolated PCL injuries (n = 97, 23.3%) were observed less frequently than multiple-ligament injuries (n = 319, 76.7%). Most cases were treated with single-stage surgery (86.8%), while staged surgeries were performed in a minority of cases (13.2%). There was no relationship between trauma mechanisms and multiple-ligament involvement, accompanying injuries, or postoperative complications. Surgeries following car accidents were more likely to occur as staged surgeries (p = 0.014). Additionally, the complication rates for staged surgeries and younger patients (≤ 18 years) were significantly higher (p = 0.009). High-energy trauma-induced PCL injuries are often associated with severe concurrent knee injuries with multiple ligament involvement. PCL reconstructions following car accidents are more likely to be staged. These findings highlight the importance of careful consideration in managing these cases to minimize complications, particularly in younger age groups. Level III.

The primary objective of this study was to examine the incidence of fractures among individuals aged 20–64 years over a 7-year timeframe by utilising an electronic recording system that is integrated with a substantial portion of the Turkish population. De-identified health records were acquired from the nationwide personal health recording system. Four age groups were established: 20–34, 35–44, 45–54, and 55–64 years. Incidence rates were further analysed according to sex and age group. A total of 3,286,991 fractures were recorded in the 7-year time period, with male patients accounting for 62.1% of those cases. The overall fracture incidence rate in the Turkish adult population was 1029/100,000. The incidence rate was 727.44/100,000 for women and 1158.86/100,000 for men (p < 0.001). The age group with the highest number of fractures was 20–34 years with 1337.012 (37.3%) fractures. Wrist fractures (17.46%), finger fractures (14.4%), and foot fractures (11.85%) accounted for 43.7% of all fractures. In women, the incidence of fractures, excluding those of the hand and wrist, increased significantly as the age groups increased (p < 0.05). Wrist, finger, and foot fractures were found to be the most common fractures among individuals aged 20–64 years. Fracture incidence was highest in men and in the age group of 20–34 years, encompassing individuals who are more active in work and sports.