A Nomogram to Predict Mortality in Patients With Severe Oral and Maxillofacial Space Infections

Objective: This study aimed to explore the risk factors for death in extremely severe oral and maxillofacial space infection (OMSI) patients and to use these findings to establish a nomogram model that can be used to predict individual patient prognosis.

Methods: Patients with extremely severe OMSI seen between 2020 and 2024 were enrolled (N = 102). Univariate and multivariate logistic regression were used to analyse the associations between clinical factors and the risk of death, and a nomogram was developed to visualise the model. Model accuracy and clinical utility of the nomogram was evaluated using receiver operating characteristic (ROC) curves, calibration curve and decision curve analysis (DCA).

Results: Six variables were associated with death. Three independent risk factors for death were identified by multivariate logistic regression: history of rheumatoid arthritis (RA) (OR: 7.716; 95% CI: 0.988-52.122; p = 0.050), D-dimer (OR: 1.162; 95% CI: 1.048-1.28; p = 0.004), and serum creatinine level (OR: 1.011; 95% CI: 1.002-1.020; p = 0.018). The nomogram had an area under the receiver operating characteristic curve (AUC) of 0.819.

Conclusion: A history of RA, D-dimer and serum creatinine are independent prognostic factors for overall survival in OMSI patients. The nomogram model showed good concordance and accuracy.