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

Abstract

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.