Angiolipoma, distinguishable from other lipomas by its excessive degree of vascular vessels, are rare in the head and neck and require unique management. A slow growing mass, located underneath the inferior border of the right mandibular angle of a 51-year-old female, was excised under general anesthesia. Unexpected excessive bleeding during the excision was observed and the histological specimen was diagnosed as angiolipoma. As shown in this case report, pre-operative imaging modalities have a crucial influence and are sufficient to diagnose and manage angiolipomas. The “Gold standard” treatment is excision with clear margins and bleeding management should be taken into account according to appropriate differential diagnosis.

The growth in worldwide popularity of electric bikes (E-bikes) and powered scooters (P-scooters) has been accompanied by an increase in injuries associated with their use. The aim of this study was to evaluate the contribution of rider age to injury severity, represented by need for hospitalization. A retrospective review of the database of a tertiary medical center yielded 1234 patients (75.7% male) who attended the emergency department (ED) in 2014–2020 for injuries sustained while riding an E-bike or P-scooter. Mean age was 31.52 ± 14.77 years: 23% were aged 51 years. Ninety patients (7.3%) were hospitalized. Older age was significantly associated with the need for hospitalization on univariate analysis (p <.001), but significance was not maintained on binary logistic regression (OR = 1.02, 95%CI 0.99–1.06; p = 0.11). Patients who underwent imaging evaluation in the ED were at lower risk of hospitalization, and patients who had surgery or a relatively long operative procedure were at higher risk of hospitalization. The study shows that older age (>51 years) is not associated with a significantly increased probability of severe injury in E-bike and P-scooter riders. This finding has important implications for insurers and healthcare administrators.

The growing popularity of E-bikes and P-scooters has led to their increasing involvement in injuries. This study sought to evaluate the impact of drug and alcohol consumption on hospitalization rates for electric-vehicle-associated injuries. A retrospective cross-sectional study design was used, including patients evacuated to the emergency department (ED) of a tertiary medical center in 2014–2020 for injuries sustained while riding E-bikes or P-scooters. Data on clinical characteristics were collected from the medical files, including pre-accident usage of alcohol or drugs. Of the 1234 patients (75.7% male) who met the inclusion criteria, 90 (7.3%) were hospitalized. The mean (SD) number of admission days was 5.44 (±0.12). Alcohol consumption was associated with 2.2% of injuries and drug use with 0.6%. Patients who rode under the influence of alcohol were significantly more likely to be hospitalized than discharged (6.7% vs. 1.8%, χ² (2) =19.25, p < 0.001); the odds ratio was 14.1. A similar association with hospitalization was found for drug use (χ² (2) = 7.83, p = 0.02). Riding an E-bike or P-scooter under the influence of alcohol or drugs increases the probability of severe injury requiring hospital admission. These results should prompt the relevant authorities to initiate effective legislation of alcohol and drug use.

Background and Objectives: The worldwide increase in electric bike (E-bike) and powered scooter (P-scooter) use in recent years has been accompanied by an increase in associated injuries to riders. The aim of this study was to evaluate trends in the incidence and types of E-bikes and P-scooter-related injuries in riders evacuated to a tertiary ED. Materials and Methods: A retrospective cross-sectional design was used. The cohort included 1234 patients referred to the emergency department (ED) of a tertiary medical center in 2014–2020 for injuries sustained while riding an E-bike or P-scooter. Demographic, clinical, and injury data were collected from the medical files, and injury rates were evaluated over time. Results: The results showed that the annual number of ED visits by injured E-bike and P-scooter riders increased steadily over the study period concomitant with an increase in ED referrals for hospitalization, indicating severe injury. The upper and lower extremities were the most frequent anatomic sites of injury in every year of the study, with variations among the different age groups. Conclusions: Our findings suggest a need for safety regulations for riders who operate two-wheel powered vehicles, such as licensing requirements and mandatory protective gear, especially for anatomic sites most at risk.

“Big-nose variant” is an anatomical phenomenon defined as the pneumatization of inferior third of the nasal cavity within the alveolar ridge while simultaneously displacing the maxillary sinus laterally. The purpose of the present study was to assess the prevalence of the big-nose variant phenomenon and suggest a morphology classification system. Diagnostic anatomical evaluation was performed in a tertiary medical center on 321 randomly selected maxillary cone beam computerized tomography scans of patients who presented at an oral and maxillofacial department. Two anatomical categories were defined for anatomical identification: classes for horizontal mesiodistal distribution, and divisions for vertical distribution. Class 2, defined as location of the nasal/sinus border between the distal edge of the canine up to the distal edge of second premolar, was found to be the most prevalent (64.6%). Class 3, defined as location of the nasal/sinus border distal to mesial edge of the first molar, was found in 17.9% of cases. Regarding the divisions category, in 96% and 58.2% of teeth examined, nasal cavity alone was found to be superior to the canine and first premolar, respectively, defined as Division A. In 46.9% and 85.6% of teeth examined, maxillary sinus alone was located above the second premolar and first molar, respectively, defined as Division C. Identifying Class 3 on the paraxial reconstruction is the first step in identifying big-nose variant, with further assurance gained from each determining division. The use of the classes and divisions may enable better maxillary treatment planning, alert surgeons for the unexpected, and avoid complications.