Risk Factors for Digital Replantation Failure: A Nomogram Prediction Model.

Abstract

Study design: A Retrospective study.

Objective: Digital necrosis (DN) after replantation can cause some serious complication. Few articles focused on the risk factors of DN; therefore, we aim to investigate the risk factors of necrosis after multiple digital replantation.

Methods: We collected the data of patients receiving multiple digital replantation in our hospital between Jan. 2017 and Jan. 2024. Based on the necrosis or not after replantation, patients with DN were as necrosis group (NG), and patients without DN were as success group (SG). The demographics, comorbidities, and admission laboratory examinations of patients were computed by univariate analysis, logistic regression analysis, and receiver operating characteristic (ROC) curve analysis. We then construct a nomogram prediction model, plot ROC curves, calibration curves, and DCA decision curves using R language software.

Results: The survival rate in our study was 83.7% (278 of 332). Univariate analysis indicated that there were significant differences in the level of D-dimer, white blood cell, neutrophil, monocyte, monocyte-to-lymphocyte ratio, systemic immune-inflammation index, system inflammation response index, C-reactive protein (CRP), neutrophils/high density lipoprotein (HDL), monocytes/HDL were significantly higher in NG than in SG. However, logistic regression analysis showed that D-dimer and CRP were independent risk factors of DN, and we identified their cut-off values. Then, we constructed a nomogram prediction model with 0.7538 in AUC of the prediction model with good consistency in the correction curve and good clinical practicality by decision curve analysis.

Conclusion: The level of D-dimer and CRP was found to be closely related to DN. We constructed a nomogram prediction model that can effectively predict DN in patients with multiple digital replantation.