Construction of a nomogram for preoperative deep vein thrombosis in pelvic fracture patients.

Background: In recent years, the incidence of pelvic fractures has been on the rise, predominantly affecting the elderly population. Deep vein thrombosis may lead to poor prognosis in patients. monocyte-to-lymphocyte ratio is novel biomarkers of inflammation, and this study aims to verify their predictive effect and construct the nomogram model.
Method: This study used binary logistic regression analysis to predict the predictive effect of MLR on the occurrence of DVT in pelvic fractures patients. And use R studio to construct nomogram model.
Result: The results showed that Age (1.04 [1.01, 1.07], p = 0.006), WBC (1.44 [1.28, 1.61], p < 0.001), and MLR (2.11 [1.08, 4.13], p = 0.029) were independent predictive factors. The nomogram demonstrated good predictive performance with small errors in both the training and validation groups, and most clinical patients could benefit from them.
Conclusion: The nomogram constructed based on MLR can assist clinicians in early assessment of the probability of DVT occurrence.
(© 2024. The Author(s).)