Oral Surgery Oral Medicine Oral Pathology Oral Radiology最新文献

Background: Coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2, affects multiple systems, including the oral cavity, with ulcers, taste changes, and mucosal lesions. Existing studies are limited in scope, highlighting the need for large-scale studies to clarify the prevalence and clinical relevance of these oral outcomes.

Materials and methods: We conducted a retrospective cohort study using the TriNetX Research Network to analyze COVID-19 patients from 2020 to 2025. Queried oral conditions, including ulcers, taste alterations, salivary disturbances, and mucosal lesions. Propensity score matching was used to balance age, sex, and comorbidities. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated, with significance set at P < .05.

Results: Among 4,875,258 adults with COVID-19, the most common oral outcomes were taste alteration (0.588%), aphthous ulcers (0.106%), salivary disturbances (0.053%), and stomatitis (0.025%). Compared with age, sex, and co-morbid matched controls, COVID-19 was associated with a higher risk of taste alteration (OR = 10.11; P < .0001) and herpetic oral lesions (OR = 1.46; P < .0001), while other oral conditions were less frequent. Anti-COVID-19 medication use was associated with a lower incidence of taste alteration (0.14% vs 0.54%; P < .0001) and higher records of aphthous ulcers and herpetic lesions.

Conclusion: COVID-19 is associated with a significantly increased risk of taste alteration and herpetic oral lesions, while anti-COVID-19 medication use is associated with lower odds of taste alteration.

Background: Anti-tumor necrosis factor-alpha (anti-TNF-α) therapies are efficacious in managing immune-mediated inflammatory diseases, however, long-term use has been associated with notable adverse events. As patients use expands, understanding the spectrum of oral adverse events (OAEs) has become essential.

Materials and methods: We conducted a retrospective cohort study using the TriNetX research network. A 5‑year observation window identified patients prescribed anti‑TNF-α therapies. Patients with prior oral conditions, concurrent cancer therapies, or antiresorptive exposure were excluded. OAEs were categorized into xerostomia, mucosal disorders, infectious disorders, gingival hyperplasia, medication-related osteonecrosis of the jaw (MRONJ), and oral squamous cell carcinoma (OSCC). Propensity score matching (1:1, age/sex) compared anti‑TNF-α users with unexposed controls.

Results: In a cohort of 1,645,751 individuals receiving anti‑TNF‑α therapy, OAEs were frequent, with oral lichenoid lesions (1.27%, 20,135), candidiasis (1.09%, 17,475), xerostomia (0.87%, 14,024), stomatitis (0.68%, 10,904), and oral herpes (0.39%, 6,343) most commonly observed. Less frequent events included MRONJ (0.01%, 173), gingival hyperplasia (0.02%, 285), and OSCC (0.07%, 1,074). Compared with the general population, anti‑TNF‑α therapy significantly increased the odds of most mucosal and infectious conditions (P < .001), though oral lichen planus showed no association. Interestingly, OSCC exhibited an inverse association (OR = 0.75, P < .0001), suggesting a potential protective effect.

Conclusion: These findings highlight the importance of routine oral health surveillance and robust pharmacovigilance amongst patients on anti‑TNF-α therapies.

Objective: Although mucoepidermoid carcinoma is one of the most common salivary gland malignancies, its involvement in the jaws is exceedingly rare. This report's purpose is to describe the histologic and demographic features of intraosseous mucoepidermoid carcinoma (IMEC) and to add evidence to support a potential relationship with glandular odontogenic cysts (GOCs).

Study design: Cases of patients diagnosed with IMEC were obtained from Oral Pathology Laboratory, Inc, at New York-Presbyterian Queens from 1985 to 2024. Slides and clinical information were reviewed.

Results: Fourteen patients with IMEC were identified who had an average age of 58.6 years and a slight female predilection. IMEC was equally present in both jaws. Twelve patients were classified as having low-grade tumors with cystic areas composed of an admixture of epidermoid and mucous cells, 6 cases of which had areas resembling GOCs. Two patients had high-grade tumors demonstrating anaplasia and perineural invasion. One high-grade tumor had areas that resembled a GOC. Four of the 7 presentations of IMEC (6 low-grade and 1 high-grade) with GOC features were from the mandible.

Conclusions: We describe the common and uncommon histopathologic features of IMEC while also demonstrating that GOC-type areas often are seen as a component of these tumors. Therefore, all lesions identified as GOCs should be carefully analyzed to rule out the early development of an IMEC.

Objective: This study aims to develop an AI-powered detection system for identifying dental anatomy-specifically tooth numbers and names-using YOLO (You Only Look Once) models to enhance diagnostic efficiency and automation in dentistry STUDY DESIGN: An annotated dataset of 724 high-resolution digital intraoral dental photographs (505 for training, 112 for validation, 107 for testing), obtained from Kaggle and Roboflow, was used. Multiple YOLO versions (YOLOv8l, YOLOv9c, YOLOv10l, YOLO11l) were implemented. Model performance was evaluated based on recall, precision, F1 score, and mean Average Precision (mAP@50).

Results: YOLOv8l achieved the highest F1 score (96.7%) and recall (97.8%). YOLO11l yielded the best precision (96.6%) and highest mAP@50 (98.4%). All models demonstrated strong potential in detecting teeth accurately from high-resolution images.

Conclusion: YOLO-based models offer an effective solution for automatic detection of dental anatomy. Their integration into telemedicine and digital dentistry platforms can streamline diagnostic workflows, reduce manual workload, and expand access to dental care, particularly in underserved regions.