Background: Pertrochanteric hip fractures are common and among serious injuries of the old population with considerable mortality and morbidity. The aim of this study was to evaluate long-term effects of recombinant human parathyroid hormone on postoperative clinical and radiologic outcomes in elderly patients with pertrochanteric hip fractures. Materials and Methods: Between 2016 and 2019, we prospectively assessed 80 patients with pertrochanteric hip fractures who underwent reduction and internal fixation with a dynamic hip screw. Patients were divided randomly into two groups. About 40 patients in the control group who received supplementary calcium (1000 mg/day) and vitamin D (800 UI/day), and 40 others who were treated additionally with 20–28 mg daily teriparatide for three months post-operatively. The functional and radiologic assessment was done using visual analog scale (VAS), Harris hip score (HSS), and standard radiographs of the hip. Results: At the final follow-up, there was a significant difference between the two groups regarding average HSS (68.38 in the control group versus 74.12 in the treatment group, P-value <0.001). VAS score was also significantly lower in the treatment group (P-value <0.001). Regarding radiographic evidence of union, the results were not statistically different between the two groups. Conclusions: The current study illustrated that short-term daily administration of teriparatide improves long-term functional outcome after pertrochanteric hip fracture fixation and can reduce the pain but does not affect union and callus formation.

Nonmelanoma skin cancer (NMSC), including basal cell carcinoma and squamous cell carcinoma, is the most prevalent type of skin cancer. While generally less aggressive than melanoma, early detection and treatment are crucial to prevent the complications. Artificial intelligence (AI) systems show promise in enhancing the accuracy, efficiency, and accessibility of NMSC diagnosis and management. These systems can facilitate early interventions, reduce unnecessary procedures, and promote collaboration among healthcare providers. Despite AI algorithms demonstrating moderate-to-high performance in diagnosing NMSC, several challenges remain. Ensuring the robustness, explainability, and generalizability of these models is vital. Collaborative efforts focusing on data diversity, image quality standards, and ethical considerations are necessary to address these issues. Building patient trust is also essential for the successful implementation of AI in the clinical settings. AI algorithms may outperform experts in controlled environments but can fall short in the real-world clinical applications, indicating a need for more prospective studies to evaluate their effectiveness in the practical scenarios. Continued research and development are essential to fully realize AI’s potential in improving NMSC diagnosis and management by overcoming the existing challenges and conducting comprehensive studies.