Technological innovations in medicine are increasingly expected to replicate the diagnostic, decision-making, and procedural skills of experienced physicians. This review explores the evolution, current status, and limitations of artificial intelligence (AI) and robotic surgery in clinical practice. Radiology and pathology have led the way in digital transformation, enabling AI applications through standardized datasets and electronic health records. However, limitations such as algorithmic opacity, legal-ethical uncertainties, and fragmented digital infrastructures continue to hinder broader implementation. In robotic surgery, soft tissue procedures have not yet demonstrated significant advantages over conventional laparoscopy in terms of cost or operative efficiency. Orthopedic applications, particularly in arthroplasty, are promising but still lack long-term validation. Importantly, for any technology to create true value in healthcare, its benefits must clearly outweigh its costs. As healthcare systems face mounting pressure from aging populations and rising procedural demand, particularly for cholecystectomy, prostatectomy, and arthroplasty, the development of efficient and scalable technologies becomes inevitable. While neither AI nor robotic surgery has yet fulfilled its transformative promise, historical trends suggest that innovation will persist toward overcoming these barriers.

Purpose: Early mortality rate in geriatric patients after hip fractures remains very high. Determining the prognostic factors is crucial for decreasing early mortality. This study aimed to evaluate the prognostic risk factors affecting early mortality after hip fracture in the elderly. Methods: Medical records of 335 patients with age 70 years or older who sustained hip fractures which were treated by hemiarthroplasty or proximal femoral nailing between May 2017 and May 2019 were reviewed. Neutrophil/lymphocyte ratio (NLR) and platelet/lymphocyte ratio (PLR) were investigated for validity as the new prognostic markers. The other variables included age, gender, type of surgery, type of implant, type of anesthesia, American Society of Anesthesiologists (ASA) score, presence of comorbidities, delirium, length of hospital stay, time delay to surgery, number of erythrocyte transfusions, and laboratory data were assessed for 30-day, 90-day, and one-year mortality. Univariate analysis and logistic regression analysis were used to determine the associated mortality. Results: Thirty-day mortality rate was 10.4% and was associated with being aged ≥90 years (p-value: 0.013, odds ratio {OR}: 0.13) and ASA score of 4 (p-value: 0.019, OR: 0.22). Ninety-day mortality rate was 21.5% and was associated with age (p-value: 0.002), being aged 80-89 years (p-value: 0.032, OR: 0.43), being aged ≥90 years (p-value: 0.001, OR: 0.13), general anesthesia (p-value: 0.016, OR: 0.41), preoperative high NLR level (p-value: 0.028, OR: 1.05), high blood urea nitrogen (BUN) level (p-value: 0.049, OR:1.02). One year mortality rate was 33.7% and independent significant prognostic risk factors were determined as being aged ≥90 years (p-value: 0.003, OR: 0.23), length of hospital stay (p-value: 0.003, OR: 1.04), and preoperative serum albumin level (p-value: 0.037, OR: 0.6). The other evaluated risk factors were not independently found to be associated with all early mortality time. Conclusion: Patients at or over 90 years old were at risk for all early mortality time points. NLR which is a new and cheap biomarker can be used as a prognostic risk factor for 90-day mortality. The variable of PLR was not found valuable for early mortality.

Background: This bibliometric study aimed to identify and analyze the top 100 articles related to artificial intelligence in the field of orthopedics.Methods: The articles were assessed based on their number of citations, publication years, countries, journals, authors, affiliations, and funding agencies. Additionally, they were analyzed in terms of their themes and objectives. Keyword co-occurrence, co-citation of authors, and co-citation of references analyses were conducted using VOSviewer (version 1.6.19).Results: The number of citations of these articles ranged from 32 to 272, with six papers having more than 200 citations The years of 2019 (n: 37) and 2020 (n: 19) together constituted 56% of the list. The USA was the leading contributor country to this field (n: 61). The most frequently used keywords were “machine learning” (n: 26), “classification” (n: 18), “deep learning” (n: 16), “artificial intelligence” (n: 14), respectively. The most common themes were decision support (n: 25), fracture detection (n: 24), and osteoarthrtitis staging (n: 21). The majority of the studies were diagnostic in nature (n: 85), with only two articles focused on treatment.Conclusions: This study provides valuable insights and presents the historical perspective of scientific development on artificial intelligence in the field of orthopedics. The literature in this field is expanding rapidly. Currently, research is generally done for diagnostic purposes and predominantly focused on decision support systems, fracture detection, and osteoarthritis classification.

Introduction: Achilles tendon rupture is a common and debilitating injury that significantly impacts mobility and quality of life. Effective treatment options that promote faster and more complete healing are needed. Fibroblast growth factor-2 (FGF-2) has shown potential in enhancing tendon repair. This study aims to investigate the efficacy of FGF-2 in promoting tendon healing in a rat model of Achilles tendon rupture, providing insights into its potential as a therapeutic option.Materials and methods: Forty-eight rat hind legs with complete Achilles tendon ruptures were divided into four equal groups: the Sham (S) group (tendon repair only), the Polymer (P) group (tendon repair with scaffold wrapping), the Produced FGF-2 (PF) group (scaffold coated with lab-produced FGF-2), and the Commercial FGF-2 (CF) group (scaffold coated with commercially sourced FGF-2). Histological analyses at two and four weeks post-surgery evaluated healing based on nuclear morphology, vascularity, fibril organization, inflammation, and adipogenesis.Results: At the end of the second week, no macroscopic healing was observed in one rat each from the S and P groups. By the end of the fourth week, macroscopic healing was observed in all groups. The S and P groups exhibited similarly severe fibril disorganization, pathological adipogenesis, and sustained inflammation, particularly at the fourth week. In contrast, the CF group demonstrated improved tendon healing with increased vascularity and extracellular matrix, lower inflammatory cell infiltration, and better fibril organization. Pathological adipogenesis was absent in the CF group, especially at the fourth week. The PF group showed comparable improvements at the second week but experienced a relapse by the 4th week, with increased inflammation and adipogenesis.Conclusion: FGF-2 coated scaffolds significantly enhanced tendon healing in a rat Achilles tendon rupture model by improving fibril organization, increasing vascularity, and reducing inflammation and pathological adipogenesis. These findings suggest that FGF-2 could be a promising therapeutic option for accelerating tendon repair. Future perspectives on tendon repair will focus on enhancing FGF-2 delivery using innovative scaffolds, paving the way for more effective therapies and improved patient outcomes.

Introduction: This study aimed to retrospectively analyze patients who presented to the orthopedic and traumatology clinic following the 2023 Kahramanmaraş earthquakes. Patients and Methods: Over a week after the earthquakes, two hundred and sixty patients were consulted at our clinic. Demographic data of the patients, duration of being under the rubble, fracture locations, types of surgeries performed, number of surgical sessions attended by individuals, and early mortality rate within one month were determined. Results: The mean age of the patients was 40.2 ± 22.4 years. One hundred thirty-eight (53.1%) were female, and 122 (46.9%) were male. The average duration of being under the rubble was determined as 27.1 ± 28.0 hours. Sixteen patients died within one month after the earthquake. The one-month mortality rate among patients with orthopedic injuries was 6.15%. Forty-seven fasciotomies were performed in 35 patients, and 22 amputations were performed in 19 patients. The most injured region was the lower extremity (78 cases, 40%). The ratio of external and internal fixation in extremity fractures was 22%. Conclusions: The management of musculoskeletal injuries can be successful with proper triage and treatment plans. Decisions regarding fasciotomy and amputation in patients with crush syndrome following an earthquake should be individualized. Implant sets should be planned accordingly, especially considering the higher occurrence of lower extremity injuries.