Background: Native vertebral osteomyelitis (NVO) presents diagnostic and therapeutic challenges requiring adherence to complex clinical guidelines. The emergence of large language models (LLMs) offers new avenues for real-time clinical decision support, yet their utility in managing NVO has not been formally assessed. Methods: This study evaluated four LLMs—Consensus, Gemini, ChatGPT-4o Mini, and ChatGPT-4o—using 13 standardized questions derived from the 2015 IDSA guidelines. Each model generated 13 responses (n = 52), which were independently assessed by three orthopedic surgeons for accuracy (4-point scale) and comprehensiveness (five-point scale). Results: ChatGPT-4o produced the longest responses (428.0 ± 45.4 words), followed by ChatGPT-4o Mini (392.2 ± 97.4), Gemini (358.2 ± 60.5), and Consensus (213.2 ± 68.8). Accuracy ratings showed that ChatGPT-4o and Gemini achieved the highest proportion of “Excellent” responses (54% and 51%, respectively), while Consensus received only 20%. Comprehensiveness scores mirrored this trend, with ChatGPT-4o (3.95 ± 0.79) and Gemini (3.82 ± 0.68) significantly outperforming Consensus (2.87 ± 0.66). Domain-specific analysis revealed that ChatGPT-4o achieved a 100% “Excellent” accuracy rating in therapy-related questions. Statistical analysis confirmed significant inter-model differences (p < 0.001). Conclusions: Advanced LLMs—especially ChatGPT-4o and Gemini—demonstrated high accuracy and depth in interpreting clinical guidelines for NVO. These findings highlight their potential as effective tools in augmenting evidence-based decision-making and improving consistency in clinical care.

Background/Objectives: Trochanteric femoral fractures pose significant surgical challenges, particularly in elderly patients. Intramedullary nailing (IMN) and plate fixation (PF) are the primary operative strategies, yet their comparative efficacy and safety remain debated. This meta-analysis synthesizes randomized controlled trials (RCTs) to evaluate clinical, functional, perioperative, and biomechanical outcomes of IMN versus PF specifically in trochanteric fractures. Methods: A systematic search of six databases was conducted up to 20 May 2024, to identify RCTs comparing IMN and PF in adult patients with trochanteric femoral fractures. Data extraction followed PRISMA guidelines, and outcomes were pooled using random-effects models. Subgroup analyses examined the influence of fracture stability, implant type, and patient age. Risk of bias was assessed using the Cochrane RoB 2.0 tool. Results: Fourteen RCTs (n = 4603 patients) were included. No significant differences were found in reoperation rates, union time, implant cut-out, or mortality. IMN was associated with significantly reduced operative time (MD = −5.18 min), fluoroscopy time (MD = −32.92 s), and perioperative blood loss (MD = −111.68 mL). It also had a lower risk of deep infection. Functional outcomes and anatomical results were comparable. Subgroup analyses revealed fracture stability and nail type significantly modified operative time, and compression screws were associated with higher reoperation rates than IMN. Conclusions: For trochanteric femoral fractures, IMN and PF yield comparable results for most clinical outcomes, with IMN offering some advantages in surgical efficiency and perioperative morbidity, though functional outcomes were comparable. Implant selection and fracture stability influence outcomes, supporting individualized surgical decision making.