Journal of Oral and Maxillofacial Surgery最新文献

Background: Facial fractures cause morbidity and involve intense resource use. Over the last two decades, several societal developments such as enactment of the Affordable Care Act and the COVID-19 pandemic occurred that could have potentially impacted facial fracture care.

Purpose: The purpose of this study was to present the newest available nationwide epidemiologic data on facial fractures encountered in hospital-based emergency department (ED) settings in the United States (US), for years 2021 and 2022, and narratively compared to 2007, when the last epidemiologic data were published using the same database source.

Study design, setting, and sample: This was a descriptive retrospective case series of the 2021 and 2022 Nationwide Emergency Department Sample database. All ED visits for the years 2021 and 2022 were included in the study, and those with missing data were excluded from analysis.

Predictor variable: Given the descriptive study nature, there were no predictor variables.

Main outcome variable: The primary outcome variable was the frequency of facial fractures. Secondary outcome variables included fracture site, sociodemographic variables (age, sex, race, and insurance status), and patient- and hospital-related factors (disposition and ED charges in 2022 US dollars).

Covariates: There were no covariates.

Analysis: Descriptive statistics, including weighted frequencies, weighted means, standard error, and 95% CI, were calculated.

Results: Between 2021 and 2022, there were 965,750 facial fracture-related ED visits, representing a 9.5% interval increase over the 2 years and up to 24% increase compared to 2007. Mean age (46.6 years, standard error 0.2; 95% CI 46.4-47.3) and female presentation (37.4%) measurably increased compared to 2007, whereas the uninsured population decreased. Nasal bone (58.1%) was the most commonly involved area, followed by the orbit, maxilla, mandible, and zygoma. Most were routinely discharged from the ED (66.5%), and 23.3% were admitted. Mean ED charge was $12,013 (standard error 247; 95% CI 11,527, 12,498) per encounter, with total charges of $10,794,020,671 for 2021 and 2022.

Conclusions and relevance: Recognizing these significant sociodemographic, patient, and hospital-related changes can guide clinical care and policy-making, especially for targeted resource allocation. The findings can also serve as the basis for follow-up studies using complementary data sources.

Background: There are notable differences in facial morphology between obese individuals and those of normal weight. A person's body mass index (BMI) is a key factor, affecting the thickness of facial soft tissues.

Purpose: This study aims to examine the association between BMI and facial anthropometric measurements.

Study design, setting, and sample: This prospective, observational (cross-sectional) study was conducted among undergraduate dental students at the Post Graduate Institute of Dental Sciences (PGIDS), Rohtak, who were originally from Haryana. Subjects with a history of trauma and congenital or chronic diseases affecting craniofacial morphology, facial surgeries, facial deformities, orthodontic treatment, or systemic diseases such as hypothyroidism/hyperthyroidism or diabetes that could influence BMI were excluded.

Predictor variable: BMI (ratio of body weight to the square of standing height) served as the predictor, and participants were categorized into four groups: underweight (BMI <18.5), normal (BMI = 18.5 to 22.9), overweight (BMI = 23 to 24.9), and obese (BMI ≥25).

Main outcome variable(s): Measurements for 12 facial anthropometric parameters were obtained using a digital vernier caliper.

Covariates: The covariates were sex and age.

Analyses: One-way ANOVA, general linear model, and independent sample t test were utilized for statistical analysis. The significance criterion was P < .01.

Results: Among the 202 subjects included, 137 (67.8%) were female, and 65 (32.2%) were male. Participants ranged in age from 18 to 30 years, with a mean age of 21.59 ± 1.82 years. Statistically significant differences were observed in face width (P < .001), lower facial width (P < .001), nose width (P < .001), and lower third face height (P = .002) across BMI categories. The mean BMI showed a statistically significant difference regarding sex; however, this difference was not significant concerning age (≤20 years vs >20 years). There was a statistically significant relationship between sex and the studied facial anthropometric parameters, except for nose length, face height (middle third), and facial index. Subjects ≤20 years versus >20 years showed a statistically significant difference in outercanthal distance, nose length, and mouth width.

Conclusions and relevance: The study results suggest that BMI is associated with facial anthropometric measurements; therefore, it may be important to adjust anthropometric measures for BMI when planning orthodontic treatment, esthetic surgeries, and facial reconstruction.

Background: Odontogenic infections represent a significant yet preventable cause of health care expenditure in the United States. However, their economic burden is not well defined.

Purpose: The purpose of this study was to estimate the per-admission hospital costs of managing odontogenic infections and identify factors associated with increased cost.

Study design, setting, and sample: This was a retrospective cohort study using the National Inpatient Sample database from years 2017 to 2019. Adults admitted for management of an odontogenic infection based on ICD-10 coding were included. Patients under 18 years or missing outcomes data were excluded.

Predictor variable: The predictors were variables categorized into demographic (age, sex), clinical (Charlson comorbidity index), procedural (incision and drainage), and hospital characteristics (teaching status) groups.

Main outcome variable: The outcome was economic burden measured as the total hospital cost of admission, derived by applying hospital-specific cost to charge ratios to reported charges and adjusting for inflation to 2019 dollars.

Covariates: None.

Analyses: Survey-weighted descriptive, bivariate, and generalized linear model statistics were used to evaluate the association between cost and study variables. Costs were log-transformed in analyses to address for right skew. Effects are reported as cost ratios (CRs) or the multiplicative change in expected cost versus the reference group; for continuous variables, the CR reflects the change per one-unit increase.

Results: There were 52,250 weighted admissions (∼17,417/year) with a mean age of 41.8 ± 20.5 years and 24,655 males (47.2%). The mean and median costs per admission were $8,162 ± 10,282 and $5,863 [IQR $3,744 to 9,013], respectively. The total annual national cost was $142 million. In adjusted analysis, higher costs were primarily driven by disease severity with airway intervention (CR 3.04, 95% CI 2.83 to 3.27), mediastinitis (CR 2.50, 95% CI 1.73 to 3.62), necrotizing fasciitis (CR 1.79, 95% CI 1.34 to 2.38), sepsis (CR 1.30, 95% CI 1.25 to 1.35), and incision and drainage (CR 1.20, 95% CI 1.17 to 1.24) having the highest CRs (all P < .001). Time to drainage in days (CR 1.13, 95% CI 1.11 to 1.15) was the only modifiable driver.

Conclusions and relevance: Inpatient management of odontogenic infections imposes substantial national costs, driven largely by markers of disease severity.