Predicting venous thromboembolism in non-surgical hospitalized patients with type 2 diabetes mellitus: development and validation of a nomogram.

BACKGROUND

Due to confounders like hyperglycemia, patients with type 2 diabetes mellitus (T2DM) have an increased susceptibility to venous thromboembolism (VTE). However, formal risk assessment models, such as using the Padua score, do not include all T2DM-associated risk factors for VTE. Therefore, this study aims to develop and validate a predictive nomogram for VTE in non-surgical inpatients with T2DM.

METHODS

We retrospectively analyzed the clinical and biochemical data of 420 non-surgical inpatients with T2DM between 2017 and 2021 from three centers (the PLA 474 hospital, the Second Affiliated Hospital of Xinjiang Medical University and the Fifth Affiliated Hospital of Xinjiang Medical University). A multivariate analysis based on logistic regression model was performed to identify independent risk factors and construct a nomogram. The predictive values were compared by calculating the integrated discrimination improvement (IDI) and net reclassification improvement (NRI), and by decision curve analysis (DCA).

RESULTS

Old age, BMI, D-dimer, hypoproteinemia, acute infection, acute myocardial infarction, cerebral ischemic stroke, reduced mobility, and heart/respiratory failure were independent risk factors for VTE in non-surgical inpatients with T2DM, as indicated by the multivariate analysis. The nomogram demonstrated superior discriminative ability compared to the Padua score (area under the curve: 0.923 vs. 0.849). NRI and IDI were also observed, and the DCA identified the greater net benefit and clinical utilization of the new nomogram.

CONCLUSIONS

A predictive nomogram for VTE in non-surgical inpatients with T2DM was developed and validated in this study. The nomogram is highly predictive and easy to operate, but external data verification is required before it can be further used.