Background/Objectives: Artificial intelligence (AI) tools for fracture detection in radiographs are increasingly approved for clinical use but remain underutilized. Understanding physician attitudes before implementation is essential for successful integration into emergency care workflows. This study investigates the acceptance of an AI-based fracture detection tool among physicians in emergency care settings, using the Unified Theory of Acceptance and Use of Technology (UTAUT) model. Methods: A cross-sectional, pre-implementation survey was conducted among 92 physicians across three hospitals participating in the SMART Fracture Trial (ClinicalTrials.gov: NCT06754137). The questionnaire assessed the four core UTAUT constructs—performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating conditions (FC)—and additional constructs such as attitude toward technology (AT), diagnostic confidence (DC), and workflow efficiency (WE). Responses were collected on a five-point Likert scale. Structural equation modeling (SEM) and confirmatory factor analysis (CFA) were performed to assess predictors of behavioral intention (BI). Results: PE was the strongest predictor of BI (β = 0.5882, p < 0.001), followed by SI (β = 0.391, p < 0.001), FC (β = 0.263, p < 0.001), and EE (β = 0.202, p = 0.001). These constructs explained a substantial proportion of variance in BI. WE received the lowest ratings, while internal consistency for SI and BI was weak. Moderator analyses showed prior AI experience improved EE, whereas more experienced physicians were more skeptical regarding WE and DC. However, none of the moderators significantly influenced BI. Conclusions: Physicians’ intention to use AI fracture detection is primarily influenced by perceived usefulness and ease of use. Implementation strategies should focus on intuitive design, targeted training, and clear communication of clinical benefits. Further research should evaluate post-implementation usage and user satisfaction.

Background: Autologous osteochondral transplantation (AOT)—the transfer of hyaline cartilage with its underlying subchondral bone—is well established for focal osteochondral lesions, yet evidence for larger (>200 mm²) defects is limited. We assessed clinical and functional outcomes of AOT in patients with osteochondral knee lesions exceeding 200 mm². Methods: In this retrospective cohort study, 52 patients underwent AOT for full-thickness osteochondral defects of the femoral condyles or patellofemoral joint. All lesions were ≥200 mm² and treated with a standardized press-fit technique using one to four overlapping cylindrical grafts. Pain and knee function were evaluated preoperatively and at 3, 6, and 12 months postoperatively with the Visual Analogue Scale (VAS), Tegner–Lysholm Knee Score (TLKS), and Knee Society Score (KSS). Results: Mean defect size was 224.4 ± 84.5 mm². The VAS improved from 6.32 ± 1.1 preoperatively to 0.72 ± 0.6 at 12 months (p < 0.001). The TLKS rose from 58.6 ± 11.4 to 95.0 ± 6.8 and the KSS from 63.8 ± 12.2 to 97.4 ± 4.9 during the same period (both p < 0.001). Most gains occurred within the first 3–6 months and were sustained at 12 months. No major surgical complications were observed, and outcomes were unaffected by age, sex, or graft number/size. Conclusions: AOT is a safe, effective option for large osteochondral knee defects (>200 mm²), offering rapid, durable pain relief and excellent functional recovery while preserving native joint structures. Accurate donor site reconstruction and precise graft placement in the weight-bearing zone appear critical for optimal results. Longer-term prospective studies are needed to confirm durability and refine patient-selection criteria.

Background: This study presents a systematic approach using a natural language processing (NLP) algorithm to assess the necessity of routine imaging after central venous catheter (CVC) placement and removal. With pneumothorax being a key complication of CVC procedures, this research aims to provide evidence-based recommendations for optimizing imaging protocols and minimizing unnecessary imaging risks. Methods: We analyzed electronic health records from four university hospitals in Salzburg, Austria, focusing on X-rays performed between 2012 and 2021 following CVC procedures. A custom-built NLP algorithm identified cases of pneumothorax from radiologists’ reports and clinician requests, while excluding cases with contraindications such as chest injuries, prior pneumothorax, or missing data. Chi-square tests were used to compare pneumothorax rates between CVC insertion and removal, and multivariate logistic regression identified risk factors, with a focus on age and gender. Results: This study analyzed 17,175 cases of patients aged 18 and older, with 95.4% involving CVC insertion and 4.6% involving CVC removal. Pneumothorax was observed in 106 cases post-insertion (1.3%) and in 3 cases post-removal (0.02%), with no statistically significant difference between procedures (p = 0.5025). The NLP algorithm achieved an accuracy of 93%, with a sensitivity of 97.9%, a specificity of 87.9%, and an area under the ROC curve (AUC) of 0.9283. Conclusions: The findings indicate no significant difference in pneumothorax incidence between CVC insertion and removal, supporting existing recommendations against routine imaging post-removal for asymptomatic patients and suggesting that routine imaging after CVC insertion may also be unnecessary in similar cases. This study demonstrates how advanced NLP techniques can support value-based medicine by enhancing clinical decision making and optimizing resources.

Background: Healthcare systems worldwide are increasingly burdened by rising costs, growing patient demand, and limited resources. In this context, cost-effectiveness analysis (CEA) plays a vital role in evaluating the clinical value of medical interventions relative to their costs. Despite the lack of evidence supporting their necessity, routine post-removal chest X-rays for central venous catheters (CVCs) are still performed in some hospitals due to persistent misconceptions about their benefits. This study seeks to address these misconceptions by examining the costs of routine imaging through a cost analysis of complication detection rates in a large inpatient cohort, with the aim of highlighting the inefficiencies of this practice and promoting evidence-based approaches. Methods: A retrospective cohort analysis was performed across four university hospitals in Salzburg, Austria, including 984 CVC removals conducted between 2012 and 2021. Comparisons were made between X-rays after primary catheter insertion and post-removal X-rays to isolate complications specifically associated with CVC removal. A simple cost-per-outcome analysis, a subtype of CEA, was chosen to determine the cost per complication detected. The approach incorporated activity-based costing, adjusted to 2024 price levels via the Austrian Consumer Price Index (CPI), to capture real-world resource utilization. Results: Complications related to CVC removal were identified in five cases (0.5%), including one catheter rupture due to self-removal, two failed removals, one hemothorax, and one case of intrathoracic bleeding. Of these, three complications were detected on X-rays, including a retained catheter fragment, signs of intrathoracic bleeding, and a hemothorax. Additionally, one asymptomatic patient had a likely incidental finding of a small pneumothorax, which required no intervention. The cost of routine X-rays was calculated at EUR 38.20 per X-ray, resulting in a total expenditure of EUR 37,588.80 for 984 X-rays. This corresponds to EUR 7517.76 per detected complication (n = 4). The odds of detecting a complication on an X-ray were 193 times higher in symptomatic patients than in asymptomatic patients (p < 0.001). Conclusions: This study confirms that complications following CVC removal are rare with only five detected cases. Routine imaging did not improve clinical decision-making, as complications were significantly more likely to be identified in symptomatic patients through clinical evaluation alone. Given the high financial cost (EUR 37,588.80 for 984 X-rays, EUR 7517.76 per detected complication), routine post-removal X-rays are unnecessary in asymptomatic patients and should be reserved for symptomatic cases based on clinical judgment. Adopting a symptom-based imaging approach would reduce unnecessary healthcare costs, minimize patient radiation exposure, and optimize resource allocation in high-volume procedures such as CVC removal.

Background/Objectives: The study outlines the systematic approach taken to develop and apply a robust NLP algorithm to determine the necessity of performing routine imaging after central venous catheter (CVC) placement and removal, based on the incidence of pneumothorax observed. Methods: Electronic health records from four university hospitals in Salzburg, Austria, on X-rays performed between 2012 and 2021 following CVC procedures, were analyzed using an NLP al-gorithm. The algorithm detected a pneumothorax in radiologists' reports and clinician requests, while excluding cases with contraindications such as chest injuries, prior pneumothorax, missing data, or unrelated follow-up X-rays. Chi-square tests were used to compare pneumothorax rates between CVC insertion and removal, and multivariate logistic regression identified risk factors, with a focus on age and gender. Results: The study analyzed 17,175 cases of patients aged 18 and older, with 95.4% involving CVC insertion and 4.6% involving CVC removal. Pneumothorax was identified in 106 cases after insertion (1.3%) and in 3 cases after removal (0.02%). The Chi-square test showed no statistically significant difference in pneumothorax incidence between insertion and removal (p = 0.4797), in-dicating no substantial difference in pneumothorax risk between these procedures. Conclusions: Given the lack of significant difference in pneumothorax incidence between CVC insertion and removal, and the established consensus that routine imaging is unnecessary after CVC removal, these findings indicate that routine imaging following CVC insertion may also be unnecessary in asymptomatic patients.

Background and Clinical Significance: We report an exceptionally rare case of mechanical aortic valve replacement necessitated by self-inflicted needle penetration with aortic valve and left ventricular involvement in a patient with recurrent self-harm behavior. Case Presentation: A 24-year-old female with post-traumatic stress disorder and emotionally unstable personality disorder, borderline type, presented with dyspnea two weeks after self-inserting multiple needles into her thorax. Computed tomography revealed a needle lodged in the aortic root and an intramyocardial needle with hemorrhagic pericardial effusion. Emergency sternotomy revealed inflammatory destruction of the right coronary aortic cusp with complete perforation. Following failed reconstruction attempts, mechanical aortic valve replacement was performed. The patient survived the immediate postoperative period but demonstrated recurrent non-adherence to oral anticoagulation, including multiple episodes of over- and under-anticoagulation. More than six years after surgery, she presented with cardiogenic shock due to prosthetic valve thrombosis after discontinuing warfarin for two weeks. Despite venoarterial ECMO and fibrinolytic therapy, she died from refractory left ventricular failure. Conclusions: This case highlights critical challenges in managing patients with severe psychiatric disorders requiring mechanical valve prostheses and suggests that bioprosthetic valves may warrant careful consideration in patients with major concerns regarding long-term anticoagulation adherence.