Nomogram for Prediction of Isolated Calf Deep Vein Thrombosis in Internal Medicine Patients

Abstract

This study aims to construct a nomogram anticipating the occurrence of isolated calf deep vein thrombosis (ICDVT), specifically in patients receiving internal medicine care. This case-control study enrolled 610 internal medicine patients admitted to the Jinan Municipal Hospital of Traditional Chinese Medicine between December 2019 and July 2022. Of the total number of patients who participated in the study, 147 were assigned to the ICDVT group, whereas 463 were assigned to the non-ICDVT group. The least absolute shrinkage and selection operator (LASSO) regression was employed to perform feature selection. A prediction model was constructed using a multivariable logistic regression analysis. The validity and practicality of the nomogram were assessed using several statistical measures, including concordance index (C-index), receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA). Gender, age, D-dimer, and diabetes mellitus were correlated with the presence of ICDVT in the considered internal medicine patients. The predictive nomogram revealed acceptable performance with a C-index of 0.883 (95% confidence interval [CI]: 0.822–0.914) in the internal verification. The area under the ROC curve was 0.883 (95% CI: 0.853–0.914), and the Hosmer–Lemeshow goodness-of-fit p value was 0.888. DCA findings indicated that the ICDVT nomogram exhibited a favorable clinical net benefit. The created nomogram has the potential to help clinicians identify high-risk groups of ICDVT among patients in the field of internal medicine, thus enabling early intervention strategies.