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Objective <p>Postoperative tracheostomy is a significant complication following medulloblastoma (MB) resection. This study aimed to develop a predictive model for postoperative tracheostomy requirement in children undergoing MB surgical resection. This model was derived as a side product of a larger research project analyzing surgical outcomes in pediatric MB patients.</p> Results <p>Forty-five patients (26%) required tracheostomy postoperatively. Using multivariable logistic regression, five models were developed, and the final model was selected based on performance and simplicity. The simplified version included two predictors: preoperative brainstem invasion and postoperative brainstem contusion, each contributing equally to the score. The model demonstrated an AUC of 0.845. Predicted risks of requiring a tracheostomy were 5.8%, 57.7%, and 75% for scores of 0, 1, and 2, respectively. This tool provides clinicians with a quantitative approach to assess tracheostomy risk, improving decision-making and patient management.</p>

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Development of a simple prediction model for tracheostomy requirement after surgical resection of medulloblastoma in children

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年1月10日

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  • Sina Zoghi,
  • Zahra Tabesh,
  • Ali Ansari,
  • Omid Yousefi,
  • Mohammad Sadegh Masoudi,
  • Reza Taheri

摘要

Objective

Postoperative tracheostomy is a significant complication following medulloblastoma (MB) resection. This study aimed to develop a predictive model for postoperative tracheostomy requirement in children undergoing MB surgical resection. This model was derived as a side product of a larger research project analyzing surgical outcomes in pediatric MB patients.

Results

Forty-five patients (26%) required tracheostomy postoperatively. Using multivariable logistic regression, five models were developed, and the final model was selected based on performance and simplicity. The simplified version included two predictors: preoperative brainstem invasion and postoperative brainstem contusion, each contributing equally to the score. The model demonstrated an AUC of 0.845. Predicted risks of requiring a tracheostomy were 5.8%, 57.7%, and 75% for scores of 0, 1, and 2, respectively. This tool provides clinicians with a quantitative approach to assess tracheostomy risk, improving decision-making and patient management.