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<p>Intranasal dexmedetomidine (IN DEX) is being increasingly used for sedation in children undergoing nonpainful diagnostic procedures. Successful procedural sedation facilitates rapid and accurate clinical diagnosis and treatment, thereby improving clinical management efficiency. As the success rate of sedation is influenced by multiple factors, enhancing sedation success, reducing procedure-related risks, and minimizing adverse events are critical clinical priorities. In this study, children aged 12–72 months (1–6 years) who underwent outpatient examinations requiring sedation with IN DEX were included. Data were extracted from the electronic medical records system of the outpatient sedation suite. The training dataset was analysed using least absolute shrinkage and selection operator (LASSO) and multivariable logistic regression to develop a nomogram-based clinical predictive model. Model performance was evaluated via receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA), with validation performed using a separate validation dataset. The developed nomogram, which incorporates napping before sedation, respiratory diseases, snotty before sedation, neurological diseases, sedation history, sedation duration, and sedation method, exhibited moderate predictive value (AUC = 0.833), favourable calibration, and enhanced clinical benefit. This study establishes a clinical prediction nomogram that can assist anaesthesiologists in the outpatient sedation suite to customize and optimize sedation plans, thereby improving the sedation success rate of IN DEX, enhancing the efficiency of nonpainful diagnostic procedures, and providing substantial clinical benefits.</p>

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Nomogram for predicting the success rate of sedation with intranasal dexmedetomidine in paediatric nonpainful diagnostic procedures: a retrospective study

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年9月29日

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  • Huatian Lin,
  • Lihua Gao,
  • Ningning Cui,
  • Guangwu Liao,
  • Xueqing Wang,
  • Taohua Peng,
  • Yuetao Xie

摘要

Intranasal dexmedetomidine (IN DEX) is being increasingly used for sedation in children undergoing nonpainful diagnostic procedures. Successful procedural sedation facilitates rapid and accurate clinical diagnosis and treatment, thereby improving clinical management efficiency. As the success rate of sedation is influenced by multiple factors, enhancing sedation success, reducing procedure-related risks, and minimizing adverse events are critical clinical priorities. In this study, children aged 12–72 months (1–6 years) who underwent outpatient examinations requiring sedation with IN DEX were included. Data were extracted from the electronic medical records system of the outpatient sedation suite. The training dataset was analysed using least absolute shrinkage and selection operator (LASSO) and multivariable logistic regression to develop a nomogram-based clinical predictive model. Model performance was evaluated via receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA), with validation performed using a separate validation dataset. The developed nomogram, which incorporates napping before sedation, respiratory diseases, snotty before sedation, neurological diseases, sedation history, sedation duration, and sedation method, exhibited moderate predictive value (AUC = 0.833), favourable calibration, and enhanced clinical benefit. This study establishes a clinical prediction nomogram that can assist anaesthesiologists in the outpatient sedation suite to customize and optimize sedation plans, thereby improving the sedation success rate of IN DEX, enhancing the efficiency of nonpainful diagnostic procedures, and providing substantial clinical benefits.