口腔疾病防治 (Oct 2023)

Development and validation of a postoperative delirium prediction model for patients with head and neck cancer resection and free flap repair

  • ZHAO Shan,
  • ZHANG Chunli,
  • XU Feng,
  • WU Yaxing,
  • LI Xiaodong ,
  • MENG Jian

DOI
https://doi.org/10.12016/j.issn.2096⁃1456.2023.10.007
Journal volume & issue
Vol. 31, no. 10
pp. 733 – 738

Abstract

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Objective To establish and validate a risk prediction model for postoperative delirium (POD) in patients with head and neck cancer (HNC) resection with free flap repair and to provide a reference for clinical practice. Methods This study has been reviewed and approved by the Ethics Committee, and informed consent has been obtained from patients. This study retrospectively collected and evaluated the risk factors and vital signs of patients undergoing head and neck cancer free flap reconstruction in the Department of Oromaxillofacial Head and Neck Oncology, Xuzhou Central Hospital from January 1, 2016, to January 1, 2022. A total of 241 cases were included, of which 171 cases were used to establish the prediction model, and 70 cases were collected for internal verification. Univariate and multivariate logistic analyses and the R Studio software package were used for modeling and statistical analysis. Results The research model finally included five risk factors: age, blood transfusion, postoperative sleep disorder and postoperative VAS pain value. The area under the working characteristic curve (AUC) of the subjects in the training set of the model was 0.869 (95% CI: 0.789-0.948), the Youden index was 0.692, the predictive value was 0.215, the sensitivity was 85.3%, the specificity was 83.9%, and the goodness of fit of the Hosmer Lemeshow test was 10.336 (P = 0.242). The model fit well. The validation set was verified according to the model. The C index was 0.827 (95% CI: 0.681-0.973), and the model prediction effect was very good. Conclusion This model may be applied to predict postoperative delirium for patients with head and neck cancer resection and free flap repair, which has a high predictive value for the risk of HNC-POD at admission. The use of this model may help to better implement preventive treatment and nursing measures.

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