Construction of a Risk Score Model for Predicting Airway Management in Maxillofacial and Neck Region Space Infections Using Inflammatory Markers.

Purpose: Patients with oral and maxillofacial space infections (OMSI) often experience rapidly progressing disease that can result in acute hypoxia, leading to severe complications such as cerebral hypoxia and cardiac arrest. Effective airway management (intubation or tracheotomy) is crucial in these cases. However, no validated tools currently exist to predict which patients require airway intervention. This study aimed to develop and validate a risk scoring system to predict the need for airway management in patients with OMSI. Patients and Methods: We conducted a retrospective study of OMSI patients treated between January 2020 and December 2022 and divided them into training and validation cohorts. A risk prediction model was developed using LASSO and logistic regression analyses in the training cohort, and its discrimination and calibration were verified in the validation cohort. Results: A total of 215 patients (150 for training and 65 for validation) were analyzed. Six independent predictors were identified: dyspnea (OR 3.95, 95% CI 1.38-11.35, p = 0.011), BMI (OR 1.14, 95% CI 1.04-1.25, p = 0.006), body temperature (OR 2.92, 95% CI 1.34-6.37, p = 0.007), sIL-2R level (OR 1.01, 95% CI 1.01-1.01, p = 0.007), CRP level (OR 1.01, 95% CI 1.01-1.01, p = 0.047), and retropharyngeal space involvement (OR 15.71, 95% CI 3.36-73.40, p < 0.001). Internal validation revealed good discrimination (AUC 0.91) and calibration (HL test, p = 0.061), with similar performance in the validation cohort (AUC 0.86; HL test, p = 0.133). Decision curve analysis demonstrated clinical utility in both cohorts. Conclusion: The proposed risk scoring system reliably predicts the need for airway management in OMSI patients, which enables clinicians to identify high-risk patients early and implement preventive strategies to improve outcomes.