Journal of oral and maxillofacial surgery : official journal of the American Association of Oral and Maxillofacial Surgeons · 2026
Establishment and External Validation of a Nomogram for Predicting In-Hospital Mortality in Patients With Maxillary Fractures Combined With Basilar Skull Fractures.
СтатьяВалидационное исследованиеНазвание и аннотация: Перевод в очереди
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Sun Yutong, Wu Meng, Zhang Wei, Liu Jiawu
Аннотация
BACKGROUND: Maxillary fractures rarely cause death alone; when combined with basilar skull fractures, they indicate high-energy craniofacial trauma and are often accompanied by severe intracranial, airway, and systemic injuries.
PURPOSE: The purpose of this study was to develop and validate a nomogram for predicting in-hospital mortality in patients with maxillary fractures combined with basilar skull fractures.
STUDY DESIGN, SETTING, AND SAMPLE: A retrospective cohort study utilized a training set from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database (US, 2008-2022) and an external validation set from Huai'an First People's Hospital (China, 2016-2024). Adult intensive care unit (ICU) patients with concomitant maxillary and basilar skull fractures and ICU stays of ≥24 hours were included.
PREDICTOR VARIABLES: Candidate predictors included demographics (eg, age, sex), vital signs (eg, heart rate), laboratory results (eg, bicarbonate, serum creatinine), therapeutic interventions (eg, mechanical ventilation), comorbidities (eg, hypertension), fracture features (eg, open fracture), disease indices (eg, Glasgow Coma Scale [GCS]), and craniocerebral injuries (eg, concussion).
MAIN OUTCOME VARIABLE: The primary outcome was in-hospital mortality, defined as death from any cause occurring between ICU admission and hospital discharge.
COVARIATES: None.
ANALYSES: Predictor selection used the least absolute shrinkage and selection operator (LASSO), followed by multivariable logistic regression. Model performance was evaluated using the area under the curve (AUC), the Hosmer-Lemeshow test, calibration plots, and decision curve analysis.
RESULTS: The training cohort (n = 145) had a median age of 55.90 (interquartile range [IQR], 32.55, 68.62) years, and 106 (73.1%) were male. The in-hospital mortality rate was 9.0%. The final model retained 5 predictors: age, bicarbonate, serum creatinine, cerebral laceration and contusion, and mechanical ventilation. It showed excellent discrimination in development (AUC, 0.94) with good calibration (Hosmer-Lemeshow P = .4; calibration plot close to the ideal line) and provided net benefit over treat-all or treat-none strategies across a broad range of threshold probabilities. In external validation (n = 95), discrimination remained strong (AUC, 0.89) with similar calibration (Hosmer-Lemeshow P = .053) and sustained net benefit on decision curve analysis.
CONCLUSIONS AND RELEVANCE: The study developed and validated a nomogram for early risk stratification and care planning in patients with maxillary and basilar skull fractures in emergency and critical care.
PURPOSE: The purpose of this study was to develop and validate a nomogram for predicting in-hospital mortality in patients with maxillary fractures combined with basilar skull fractures.
STUDY DESIGN, SETTING, AND SAMPLE: A retrospective cohort study utilized a training set from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database (US, 2008-2022) and an external validation set from Huai'an First People's Hospital (China, 2016-2024). Adult intensive care unit (ICU) patients with concomitant maxillary and basilar skull fractures and ICU stays of ≥24 hours were included.
PREDICTOR VARIABLES: Candidate predictors included demographics (eg, age, sex), vital signs (eg, heart rate), laboratory results (eg, bicarbonate, serum creatinine), therapeutic interventions (eg, mechanical ventilation), comorbidities (eg, hypertension), fracture features (eg, open fracture), disease indices (eg, Glasgow Coma Scale [GCS]), and craniocerebral injuries (eg, concussion).
MAIN OUTCOME VARIABLE: The primary outcome was in-hospital mortality, defined as death from any cause occurring between ICU admission and hospital discharge.
COVARIATES: None.
ANALYSES: Predictor selection used the least absolute shrinkage and selection operator (LASSO), followed by multivariable logistic regression. Model performance was evaluated using the area under the curve (AUC), the Hosmer-Lemeshow test, calibration plots, and decision curve analysis.
RESULTS: The training cohort (n = 145) had a median age of 55.90 (interquartile range [IQR], 32.55, 68.62) years, and 106 (73.1%) were male. The in-hospital mortality rate was 9.0%. The final model retained 5 predictors: age, bicarbonate, serum creatinine, cerebral laceration and contusion, and mechanical ventilation. It showed excellent discrimination in development (AUC, 0.94) with good calibration (Hosmer-Lemeshow P = .4; calibration plot close to the ideal line) and provided net benefit over treat-all or treat-none strategies across a broad range of threshold probabilities. In external validation (n = 95), discrimination remained strong (AUC, 0.89) with similar calibration (Hosmer-Lemeshow P = .053) and sustained net benefit on decision curve analysis.
CONCLUSIONS AND RELEVANCE: The study developed and validated a nomogram for early risk stratification and care planning in patients with maxillary and basilar skull fractures in emergency and critical care.