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SIMULATION-BASED TRAINING FOR NEONATAL ENDOTRACHEAL INTUBATION: A NARRATIVE REVIEW

Objective: To analyze the impact of simulation-based training on the efficacy of neonatal endotracheal intubation, with an emphasis on simulation methodologies such as high-fidelity mannequins, 3D printing, virtual and augmented reality, and to discuss the comparison between different intubation devices. Methodology: A literature review based on articles indexed in the PubMed database. The descriptors used in the search included "endotracheal intubation" OR "airway management" AND simulation OR "mannequin-based training" OR "simulation-based training" OR "high-fidelity simulation". Twenty articles were selected for detailed analysis, considering their relevance to the topic.  Discussion: Simulation-based training has been shown to be highly effective in improving neonatal intubation performance, particularly in terms of reducing execution time and increasing the success rate on the first attempt. Methodologies such as high-fidelity simulators, 3D printing, and virtual and augmented reality approaches have shown positive results in terms of technical precision and minimizing complications. However, the scarcity of resources and the need for large-scale clinical validation still represent challenges for the universal implementation of these technologies. Final considerations: Simulation-based training is an essential tool in the training of health professionals, helping to improve technical skills and safety in neonatal airway management. We recommend expanding the use of these methodologies, as well as developing standardized guidelines for training and encouraging longitudinal studies to optimize clinical results and improve the quality of neonatal care.

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SIMULATION-BASED TRAINING FOR NEONATAL ENDOTRACHEAL INTUBATION: A NARRATIVE REVIEW

  • DOI: https://doi.org/10.22533/at.ed.1595212512059

  • Palavras-chave: Neonatal; Endotracheal intubation; Airway management; Simulation; Training with mannequins; High-fidelity simulation.

  • Keywords: Neonatal; Endotracheal intubation; Airway management; Simulation; Training with mannequins; High-fidelity simulation.

  • Abstract:

    Objective: To analyze the impact of simulation-based training on the efficacy of neonatal endotracheal intubation, with an emphasis on simulation methodologies such as high-fidelity mannequins, 3D printing, virtual and augmented reality, and to discuss the comparison between different intubation devices. Methodology: A literature review based on articles indexed in the PubMed database. The descriptors used in the search included "endotracheal intubation" OR "airway management" AND simulation OR "mannequin-based training" OR "simulation-based training" OR "high-fidelity simulation". Twenty articles were selected for detailed analysis, considering their relevance to the topic.  Discussion: Simulation-based training has been shown to be highly effective in improving neonatal intubation performance, particularly in terms of reducing execution time and increasing the success rate on the first attempt. Methodologies such as high-fidelity simulators, 3D printing, and virtual and augmented reality approaches have shown positive results in terms of technical precision and minimizing complications. However, the scarcity of resources and the need for large-scale clinical validation still represent challenges for the universal implementation of these technologies. Final considerations: Simulation-based training is an essential tool in the training of health professionals, helping to improve technical skills and safety in neonatal airway management. We recommend expanding the use of these methodologies, as well as developing standardized guidelines for training and encouraging longitudinal studies to optimize clinical results and improve the quality of neonatal care.

  • Sergio Seiti Nakamura Junior
  • Amanda de Oliveira Jorge
  • Andrei Euclides Andreatta
  • Sarah Maria de Souza Fernandes
  • Marcos Henrique Soares Cunha
  • Bárbara Carolina Demetrio Melo
  • Victor Araujo de Morais 
  • Bruna da Silva Soares
  • Carolina Barbosa Araujo
  • Esthefani Zenaide da Silva
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