Nomogram for predicting postoperative deep vein thrombosis in patients with spinal fractures caused by high-energy injuries

Nomogram based on high-density lipoprotein cholesterol for the occurrence of preoperative deep vein thrombosis in patients with intertrochanteric femur fracture: a retrospective study

BACKGROUND

This study aims to develop a nomogram and forecast the incidence of DVT in individuals suffering from an intertrochanteric femur fracture.

METHOD

This work created a nomogram using the R programming language and employed logistic regression to determine independent predicting features. An external validation dataset was used to validate the nomogram.

RESULT

The findings demonstrated the independence of LYM (0.02[0.01-0.09], p < 0.001), ALB (0.83[0.74, 0.94], p = 0.002), and HDL-C (0.18[0.04, 0.71], p = 0.014). Good prediction performance with modest errors was shown by the nomogram in both the training and validation groups.

CONCLUSION

In conclusion, the nomogram that was created using HDL-C, ALB, and LYM can assist medical professionals in determining the likelihood that DVT will occur.