RESUMO
Background: Dental implant surgery has become a widely accepted method for replacing missing teeth. However, the success of dental implant procedures can be influenced by various factors, including the quality of preoperative planning and assessment. Cone beam computed tomography (CBCT) imaging provides valuable insights into a patient's oral anatomy, but accurately predicting implant success remains a challenge. Materials and Methods: In this randomized controlled trial (RCT), a cohort of 150 patients requiring dental implants was randomly divided into two groups: an artificial intelligence (AI)-assisted group and a traditional assessment group. Preoperative CBCT images of all patients were acquired and processed. The AI-assisted group utilized a machine learning model trained on historical data to assess implant success probability based on CBCT images, while the traditional assessment group relied on conventional methods and clinician expertise. Key parameters such as bone density, bone quality, and anatomical features were considered in the AI model. Results: After the completion of the study, the AI-assisted group demonstrated a significantly higher implant success rate, with 92% of implants successfully integrating into the bone compared to 78% in the traditional assessment group. The AI model showed an accuracy of 87% in predicting implant success, whereas traditional assessment methods achieved an accuracy of 71%. Additionally, the AI-assisted group had a lower rate of complications and required fewer postoperative interventions compared to the traditional assessment group. Conclusion: The AI-assisted approach significantly improved implant success rates and reduced complications, underscoring the importance of incorporating AI into the dental implant planning process.
RESUMO
Introduction: The lifespan of an edentulous mandible with one median implant to hold a full denture for 24 months was evaluated to see if the early loading had any impact on it. Single-implant denture retention for the mandibular region was proposed by "Cordioli et al. in the 1990s. Objectives: Whether rapid loading and placement of a "single median implant" may result in the implant survival rate comparable to rehabilitation with a single implant and second-stage surgery. Methods: It was found that 81 of the 158 implant recipients had quick loading, whereas the rest had delayed loading (77 patients). Patients in the context of "delayed loading group" had follow-up appointments at 1 month, 4 months, 12 months, and 24 months. In addition, the nine implants failed in the 3 months after loading in a quick loading group, while just one implant failed before loading. Median implant survival at 2 years was the study's main goal. Direct loading had a 7% fatality rate advantage over traditional loading because of the alleged advantages of immediate loading, including the avoidance of second-stage surgery. Prosthetic problems were evaluated using Fisher's exact test. Results: A higher rate of implant survival was not seen when implants were loaded more quickly (P = 0.81). A statistically significant difference (P = 0.019) was seen in implant survival between the therapy groups. Conclusion: Single implant loading in an edentulous mandible has a worse survival rate than delayed loading, according to all available research.