Journal of Stomatology Oral and Maxillofacial Surgery最新文献

Introduction: Proper tongue positioning is crucial for obtaining high-quality diagnostic images in orthopantomography (OPG). Incorrect positioning often results in a radiolucent artifact in the palatoglossal air space, compromising image quality. This issue may necessitate repeating the study or advancing to Cone-Beam Computed Tomography (CBCT), both of which increase radiation exposure. This study aimed to evaluate the effectiveness of using unleavened bread as a physical aid to decrease the occurrence of this artifact.

Materials and methods: An experimental study was conducted involving 100 individuals, who were divided into two groups. The control group consisted of 50 participants who received standard verbal instructions, while the study group included 50 participants who used unleavened bread placed against the palate. Two trained technicians acquired panoramic radiographs, and a blinded evaluator analyzed the images for the presence or absence of radiolucency in both the anterior and posterior regions. The Chi-square test was utilized to compare prevalence rates, and a binary logistic regression was performed to identify predictors, adjusting for age and sex.

Results: No significant differences were observed in the baseline characteristics of the sample (p = 0.763). The prevalence of the posterior artifact in the control group was 50%, compared to 22% in the Unleavened Bread group. This difference was statistically significant (p = 0.006). A binary logistic regression analysis confirmed that membership in the Unleavened Bread group was the only significant independent predictor (OR = 0.25; p = 0.003), indicating a 75% protective effect against the posterior artifact. However, the intervention did not show statistical significance in correcting anterior radiolucency.

Conclusions: The use of unleavened bread is an effective method for controlling artifacts associated with the palatoglossal air space in the posterior region. This confirms that the issue is a correctable technical error. The maneuver serves as a reliable biomechanical standard, enhancing diagnostic quality and reducing the patient's overall radiation exposure by minimizing the need for repeat examinations. However, its effectiveness is selective; it shows no statistical impact on the anterior region due to certain mechanical limitations.

Background: The expanding use of LLMs (Large Language Models) for rapid, practical information access has accelerated their integration into medicine and dentistry. Yet inaccuracies and fabricated citations raise concerns about reliability in clinical contexts. This study compares ChatGPT 4.0 and OpenEvidence on questions regarding intentional replantation and examines how endodontists & oral and maxillofacial surgeons evaluate the perceived accuracy and completeness of their responses.

Methods: Twenty clinically oriented questions addressing both the endodontic and surgical dimensions of intentional replantation were generated using the "alsoasked.com" tool and subsequently reviewed by specialists in endodontics and oral and maxillofacial surgery. Each question was submitted individually to both models. ChatGPT 4.0 was provided with a specialized prompt to emulate expert-level use, whereas OpenEvidence was queried without additional guidance. The resulting 40 responses were evaluated for FKGL (Flesch-Kincaid Grade Level) readability and textual similarity. Perceived accuracy and completeness were analyzed using linear mixed-effects models, with LLM type and evaluator specialty as fixed effects and rater identity as a random effect.

Results: Both LLMs produced responses with advanced readability, and no significant difference in FKGL scores was observed (p = 0.092). Textual similarity remained low (0-9%), reflecting a high degree of originality across outputs. The LMM analyses demonstrated that LLM type had a significant main effect on both perceived accuracy and completeness (p < 0.001), with OpenEvidence receiving higher scores than ChatGPT 4.0 for both outcomes. The evaluator's clinical specialty did not show a significant independent main effect. However, a significant interaction between LLM type and clinical specialty was observed for perceived accuracy, whereas this interaction did not reach statistical significance for completeness.

Conclusions: OpenEvidence's higher perceived accuracy and completeness suggest domain-specific, structured LLMs may better generate high-quality clinical information. This study also provides a rare cross-specialty comparison of evaluations by endodontists and oral-maxillofacial surgeons.

Background: Osteopetrosis, characterized by impaired osteoclast function and increased bone density, poses significant clinical challenges when complications like mandibular osteomyelitis arise. This report elucidates the clinicoradiographic progression and management of such a case in ADO-II, driven by a novel de novo CLCN7 c.2227C>T (p.R743W) mutation.

Case presentation: A 57-year-old male presented with refractory mandibular osteomyelitis accompanied by facial swelling and trismus. Radiographs revealed mandibular osteolysis, "sandwich vertebrae," and "Erlenmeyer flask" deformities. He had anemia and thrombocytopenia. Sequencing analysis revealed a de novo CLCN7 c.2227C>T (p.R743W) mutation in the patient. Therapeutic measures involved partial splenic artery embolization, administration of intravenous cefuroxime and ornidazole combined with hyperbaric oxygen therapy and pleural drainage. The osteomyelitis persisted due to avascular necrosis in sclerotic bone, despite the adoption of multidisciplinary management.

Conclusions: This case highlights the aggressive phenotype associated with the CLCN7 c.2227C>T (p.R743W) mutation, the importance of early genetic testing and personalized therapeutic strategies.

This article has been withdrawn at the request of the authors. The Publisher apologizes for any inconvenience this may cause.The full Elsevier Policy on Article Withdrawal can be found at https://www.elsevier.com/about/policies/article-withdrawal

This article has been withdrawn at the request of the authors. The Publisher apologizes for any inconvenience this may cause. The full Elsevier Policy on Article Withdrawal can be found at https://www.elsevier.com/about/our-business/policies/article-withdrawal.