RESUMO
Objectives: This study aimed to develop and validate machine learning (ML) models using H2O-AutoML, an automated ML program, for predicting medication-related osteonecrosis of the jaw (MRONJ) in patients with osteoporosis undergoing tooth extraction or implantation. Patients and. Methods: We conducted a retrospective chart review of 340 patients who visited Dankook University Dental Hospital between January 2019 and June 2022 who met the following inclusion criteria: female, age ≥55 years, osteoporosis treated with antiresorptive therapy, and recent dental extraction or implantation. We considered medication administration and duration, demographics, and systemic factors (age and medical history). Local factors, such as surgical method, number of operated teeth, and operation area, were also included. Six algorithms were used to generate the MRONJ prediction model. Results: Gradient boosting demonstrated the best diagnostic accuracy, with an area under the receiver operating characteristic curve (AUC) of 0.8283. Validation with the test dataset yielded a stable AUC of 0.7526. Variable importance analysis identified duration of medication as the most important variable, followed by age, number of teeth operated, and operation site. Conclusion: ML models can help predict MRONJ occurrence in patients with osteoporosis undergoing tooth extraction or implantation based on questionnaire data acquired at the first visit.
RESUMO
Surgical ciliated cysts occur primarily in the maxilla after radical maxillary sinus surgery. We report the first case of a surgical ciliated cyst that developed in the infratemporal fossa 25 years after the patient sustained severe facial trauma. The patient complained of mandibular pain and limited mouth opening. The patient's condition was completely resolved 5 months after marsupialization via Le Fort I osteotomy. Surgical morbidities can be minimized by proper diagnosis and less invasive surgery.
