Establishment and validation of a nomogram for predicting the risk of syncope after craniomaxillofacial surgery

Abstract

Purpose

To explore the influencing factors of syncope in patients after plastic surgery, establish a syncope risk prediction model, and verify its accuracy.

Methods

A total of 265 patients undergoing craniomaxillofacial surgery were included and divided into a syncope group and non-syncope group. Multivariate logistic regression analysis was used to screen for risk factors of syncope, and R language was used to establish a risk prediction nomogram of syncope in craniomaxillofacial surgery patients. The Hosmer-Lemeshow goodness-of-fit test was used to evaluate the fit of the model, and the receiver operating characteristic (ROC) curve was used to analyze the predictive value of the model.

Results

Syncope occurred in 87 of 265 patients (32.8%), and no syncope occurred in 178 patients (67.8%). Multivariate logistic regression analysis revealed statistical differences in age, orthostatic heart rate, orthostatic diastolic blood pressure, syncope history, weight loss history, and medication history between the 2 groups (P < 0.05). A nomogram was constructed for predicting the risk of syncope after craniomaxillofacial surgery, and the Hosmer-Lemeshow goodness-of-fit test proved that the nomogram fitted well (P = 0.431). The results of ROC curve analysis showed that the alignment graph model had high prediction accuracy; the area under the curve was 0.886 (95% confidence interval, 0.8381–0.9332).

Conclusion

Evaluating the risk of syncope after craniomaxillofacial surgery is helpful and provides guidance for the formulation of preventive strategies.