Abstract
Background: To develop and validate a nomogram for prediction of the occurrence of deep venous thrombosis in polytrauma patients with traumatic brain injury.
Methods: A retrospective and observationaltrails were performed from November,2021 to May,2023. The prediction model was developed in a training cohort that consisted of 349 polytrauma patients with traumatic brain injury and data was gathered from November,2021 to August,2022. The baseline clinical characteristics from the electronic medical and nursing records of each patient which include demographics, medical records, laboratory parameters, and clinical outcomes were collected. Multivariable logistic regression analysis was used to develop the predicting model, and this was presented with a nomogram. The performance of the nomogram was assessed with respect to its calibration, discrimination, and clinical usefulness. Internal validation was assessed. An independent validation cohort contained 298 consecutive patients from August,2022 to May,2023.
Result: A total of 647 trauma patients who met the inclusion criteria. Among these, 349 patients were in training cohort and 298 patients were in validation cohort. The incidence of DVT was 32.1% and 31.9% in the trainingand validation cohorts, respectively. Predictors contained in the individualized prediction nomogram the Age, Smoking, ISS, GCS, D-dimer, MV and AVD. The model showed a good discrimination, with a C-index of 0.783 and a good calibration. Calibration curves and decision curve analysis of the DVT-predicting nomogram demonstrated that the nomogram was clinically useful.
Conclusion: This study presents a nomogram that incorporates both the demographic characteristics and clinical risk factors, and can be conveniently used to individualized prediction of DVT in polytrauma patients with traumatic brain injury