Nomogram Prediction Model for Deep Venous Thrombosis in Traumatic Cervical Spinal Cord Injury Patients During...

Area of Science:

• Medical research
• Clinical diagnostics
• Thrombosis studies

Background:

• Deep venous thrombosis (DVT) is a significant complication in patients with traumatic cervical spinal cord injury (SCI).
• Identifying risk factors is crucial for timely prevention and management during hospitalization.

Purpose of the Study:

• To identify independent risk factors for DVT in patients with traumatic cervical SCI.
• To develop and validate a predictive nomogram model for DVT risk in this population.

Main Methods:

• A cohort of 580 patients with traumatic cervical SCI was analyzed.
• Logistic regression identified independent risk factors, including American Spinal Cord Injury Association grade, combined craniocerebral injury, neutrophil-to-lymphocyte ratio, and D-dimer.
• A nomogram model was constructed and validated using ROC curve, calibration curve, and decision curve analysis.

Main Results:

• The American Spinal Cord Injury Association grade, combined craniocerebral injury, neutrophil-to-lymphocyte ratio, and D-dimer were identified as independent risk factors for DVT.
• The nomogram demonstrated good predictive ability with an area under the ROC curve of 0.808 in the training cohort and 0.785 in the validation cohort.
• The model showed excellent accuracy and clinical effectiveness.

Conclusions:

• The identified factors are significant predictors of DVT in hospitalized patients with traumatic cervical SCI.
• The developed nomogram model offers a robust tool for assessing DVT risk in this vulnerable patient group.