No abstract

Background/Aims: No studies have characterized the morbidity and mortality of maxillary & malar fractures on a national scale. The aim of this study was to examine the risk factors for mortality in pediatric patients who had sustained maxillary and malar fractures by using a national pediatric hospital inpatient care database. Materials and methods:This retrospective cohort study was conducted using the Kids' Inpatient Database (KID). The primary predictor variable was the cause of injury. The primary outcome variable was mortality rate. Additional predictor variables included age, gender, race, income, payer information, year and place of injury, number of facial fractures, concomitant facial fractures, other fractures of the body, and intracranial/ internal organ injury. Univariate and multivariate regression models were performed to assess risk factors for mortality. Statistical significance was set to a p-value <.05.Results: A total of 5859 patients met the inclusion criteria. The most common age group was 13-17 years of age (n = 3816, 65.1%). Motor vehicle accidents were the most common mechanism of injury (n = 2172, 37.1%). The presence of cranial vault (OR = 2.81, p = .017), skull base (OR = 2.72, p < .001), and vertebral column fractures (OR = 2.13, p = .016), as well as sub-arachnoid hemorrhage (OR = 4.75, p = .005), traumatic pneumothorax/hemothorax (OR = 2.16, p = .015), and heart/lung injury (OR = 3.37, p < .001) were each independently associated with increased odds of mortality.Conclusions: Patients in their late teens most commonly sustained malar and maxillary fractures, likely due to general trends in craniomaxillofacial development. The presence of other fractures located in close proximity to the mid-face increased the risk of mortality among pediatric patients with malar and maxillary fractures. This may be explained by the anatomical approximation of the mid-face to vital neurovascular structures of the head, which, when damaged, may prove fatal.

program, but research productivity did. For U.S. MDs, research productivity was significantly associated with both medical school research ranking and taking a gap year. Matched individuals were ranked in the top 5 on the ACAPS form, while non-matched individuals were ranked between 5-10. A multiple logistic regression model showed that Step 1 score, total academic productivity (the sum of published works, presentations and submitted work) and average rank on the ACAPS form were found to be significant (p<0.01). This model correctly predicted 87.6% of successful matches and 63.0% of non-matches. CONCLUSION:Applicants from top-ranked research institutions were associated with having greater academic productivity and taking gap years. A regression model could accurately predict match status, but does not capture factors such as qualitative assessments or contact between faculty. In the setting of changes to USMLE grading and the plastic surgery application process, awareness of these factors will allow programs to reflect on the attributes that they find most important, while also reflecting on the pitfalls of emphasizing attributes which may promote algorithmic bias.

No abstract

No abstract