Objectives: To develop a nomogram for predicting calf muscle veins thrombosis (CMVT) in stroke patients during rehabilitation. Methods: We enrolled 360 stroke patients from the Rehabilitation Medicine Center from December 2015 to February 2019. Of the participants, 123 were included in the CMVT group and 237 in the no CMVT group. The least absolute shrinkage and selection operator (LASSO) regression model was applied to optimize feature selection for the model. Multivariable logistic regression analysis was applied to construct a predictive model. Performance and clinical utility of the nomogram were generated using the Harrell's concordance index, calibration curve, and decision curve analysis (DCA). Results: Age, Brunnstrom stage (lower extremity), D-dimer, and antiplatelet therapy were associated with the occurrence of CMVT. The prediction nomogram showed satisfactory performance with a concordance index of 0.718 (95% CI: 0.663-0.773) in internal verification. The Hosmer–Lemeshow test, P = .217, suggested that the model was of goodness-of-fit. In addition, the DCA demonstrated that the CMVT nomogram had a good clinical net benefit. Conclusions: We developed a nomogram that could help clinicians identify high-risk groups of CMVT in stroke patients during rehabilitation for early intervention.

目的：开发一个列线图，用于预测中风患者康复期间的小腿肌肉静脉血栓形成 (CMVT)。方法：我们于 2015 年 12 月至 2019 年 2 月从康复医学中心招募了 360 名脑卒中患者，其中 CMVT 组 123 人，非 CMVT 组 237 人。应用最小绝对收缩和选择算子 (LASSO) 回归模型来优化模型的特征选择。应用多变量逻辑回归分析构建预测模型。列线图的性能和临床效用是使用 Harrell 的一致性指数、校准曲线和决策曲线分析 (DCA) 生成的。结果：年龄、Brunnstrom 分期（下肢）、D-二聚体和抗血小板治疗与 CMVT 的发生有关。预测列线图在内部验证中表现出令人满意的性能，一致性指数为 0.718（95% CI：0.663-0.773）。Hosmer-Lemeshow 检验，P  = .217，表明该模型具有拟合优度。此外，DCA 证明 CMVT 列线图具有良好的临床净效益。结论：我们开发了一个列线图，可以帮助临床医生在康复期间识别中风患者的高危 CMVT 组，以进行早期干预。