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Full Length Article| Volume 224, P21-31, April 2023

A nomogram model to predict the acute venous thromboembolism risk after surgery in patients with glioma

  • Author Footnotes
    1 Chuanhao Zhang and Zhenghai Deng contributed equally to this work.
    Chuanhao Zhang
    Footnotes
    1 Chuanhao Zhang and Zhenghai Deng contributed equally to this work.
    Affiliations
    Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
    Search for articles by this author
  • Author Footnotes
    1 Chuanhao Zhang and Zhenghai Deng contributed equally to this work.
    Zhenghai Deng
    Footnotes
    1 Chuanhao Zhang and Zhenghai Deng contributed equally to this work.
    Affiliations
    Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
    Search for articles by this author
  • Author Footnotes
    1 Chuanhao Zhang and Zhenghai Deng contributed equally to this work.
    Zuocheng Yang
    Footnotes
    1 Chuanhao Zhang and Zhenghai Deng contributed equally to this work.
    Affiliations
    Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
    Search for articles by this author
  • Author Footnotes
    2 Jian Xie and Zonggang Hou are co-corresponding authors.
    Jian Xie
    Correspondence
    Corresponding authors at: Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, No.119 of South 4th Ring Road, Fengtai District, Beijing, China.
    Footnotes
    2 Jian Xie and Zonggang Hou are co-corresponding authors.
    Affiliations
    Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
    Search for articles by this author
  • Author Footnotes
    2 Jian Xie and Zonggang Hou are co-corresponding authors.
    Zonggang Hou
    Correspondence
    Corresponding authors at: Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, No.119 of South 4th Ring Road, Fengtai District, Beijing, China.
    Footnotes
    2 Jian Xie and Zonggang Hou are co-corresponding authors.
    Affiliations
    Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
    Search for articles by this author
  • Author Footnotes
    1 Chuanhao Zhang and Zhenghai Deng contributed equally to this work.
    2 Jian Xie and Zonggang Hou are co-corresponding authors.
Published:February 08, 2023DOI:https://doi.org/10.1016/j.thromres.2023.02.002
A nomogram model to predict the acute venous thromboembolism risk after surgery in patients with glioma
Previous ArticleCharacteristics associated with diagnostic yield of imaging for deep venous thrombosis and pulmonary embolism in the emergency department, hospital, and office settings: An Optum Clinformatics claims database study (2015–2019)
Next ArticleEstimating the measurement uncertainties of the international sensitivity index of 12 thromboplastins through Monte Carlo simulation

      Abstract

      Introduction

      Postoperative venous thromboembolism (VTE) is a common complication for glioma patients, with an incidence rate of about 20 %. The purpose of this study was to explore the risk factors of acute VTE after glioma surgery, which may provide an essential reference for clinical guidance on the prevention of acute VTE.

      Materials and methods

      A total of 435 patients who underwent glioma surgery from 2012 to 2021 were included in this study. Duplex ultrasonography was performed routinely 3–5 days after the surgery to define VTE. Univariate and multivariate logistic regression analyses were performed to explore the independent predictor of acute VTE after glioma surgery and use these selected risk factors to construct and validate a nomogram.

      Results

      Several risk factors for predicting acute VTE after glioma surgery were identified and used to build the nomogram: age, operation time, systemic immune-inflammation index (SII), hypertension, and diabetes mellitus. The area under the curve of the nomogram was 0.834, indicating good discrimination. Hosmer-Lemeshow of the calibration curve was 3.05 (P = 0.98), showing a high degree of agreement between the prediction and actual outcome. Decision curve analysis indicated that the nomogram model was helpful when the incidence of VTE was 5–80 %.

      Conclusions

      A nomogram to predict acute VTE after glioma surgery was constructed and validated. Clinicians can use this predictive model to achieve risk assessment and take different treatment measures to prevent acute postoperative VTE and improve patients' quality of life effectively.

      Keywords

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      Article info

      Publication history

      Published online: February 08, 2023
      Accepted: February 3, 2023
      Received in revised form: January 24, 2023
      Received: November 4, 2022

      Identification

      DOI: https://doi.org/10.1016/j.thromres.2023.02.002

      Copyright

      © 2023 Published by Elsevier Ltd.

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