JOURNAL OF CLINICAL SURGERY ›› 2024, Vol. 32 ›› Issue (7): 701-705.doi: 10.3969/j.issn.1005-6483.2024.07.009

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Prognostic nomogram for predicting lower limb venous thrombosis in patients after craniocerebral surgery

GE Zhiqiang,ZUO Gang,XU Qian,LIANG Jiyao,CHEN Yibin,HUO Junjie,JIANG Ming   

  1. Department of Neurosurgery,Taicang First People’s Hospital,Taicang,Jiangsu 215400,China
  • Received:2023-09-27 Online:2024-07-20 Published:2024-07-20

Abstract: Objective To explore the risk factors for lower limb venous thrombosis in patients after craniocerebral surgery,and establish a prognostic nomogram for the occurrence of lower limb venous thrombosis. Methods A total of 427 patients who underwent craniotomy for craniocerebral trauma and met the inclusion criteria in the First People’s Hospital of Taicang from January 2018 to December 2020 were collected as training group, and the nomogram was drawn and verified internally. And 106 patients who underwent surgery from January 2021 to June 2021 were used as test group, and the model was externally verified set. The nomogram was established and internally validated with the data of the training group,and externally validated with the data of the test group. For the training group,multivariate Logistic regression analysis was performed by including all variables with P<0.05 in univariate analysis,and established the prognostic nomogram by R software. In the training group and the test group,the performance of the nomogram was verified by C-index,calibration chart and decision curve analysis respectively. Results In the training group of 427 people,107 had lower limb venous thrombosis,with an incidence rate of 25.1%. Among the 106 people in the test group,33 developed lower limb venous thrombosis,with an incidence rate of 31.1%. Multivariate logistic regression analysis showed that age,lower preoperative GCS score,postoperative lower limb muscle strength<3,hypertension,and diabetes were independent risk factors for the occurrence of lower limb vein thrombosis after craniocerebral surgery. The C-index of this nomogram in the training group and the test group was 0.837 (95%CI:0.796-0.878) and 0.933 (95% CI:0.886-0.979),respectively. Conclusion The nomogram including the age,preoperative GCS score,postoperative lower limb muscle strength<3,hypertension,and diabetes can predict the probability of lower limb vein thrombosis after craniocerebral surgery with convenient discrimination and clinical utility.

Key words: post craniocerebral surgery, lower limb venous thrombosis, nomogram, predictive model

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[4] . [J]. JOURNAL OF CLINICAL SURGERY, 2016, 24(10): 744 .
[5] . [J]. JOURNAL OF CLINICAL SURGERY, 2016, 24(10): 747 .
[6] . [J]. JOURNAL OF CLINICAL SURGERY, 2016, 24(10): 764 .
[7] . [J]. JOURNAL OF CLINICAL SURGERY, 2016, 24(10): 766 .
[8] . [J]. JOURNAL OF CLINICAL SURGERY, 2016, 24(10): 774 .
[9] . [J]. JOURNAL OF CLINICAL SURGERY, 2016, 24(10): 780 .
[10] . [J]. JOURNAL OF CLINICAL SURGERY, 2016, 24(10): 783 .