Abstract
Background
The success of cardiopulmonary resuscitation (CPR) in newborns largely depends on effective lung ventilation; however, a direct randomized comparison using different available devices has not yet been performed.
Methods
Thirty-six professionals were exposed to a realistic newborn CPR scenario. Ventilation with either a bag-valve mask (BVM), T-piece, or ventilator was applied in a randomized manner during CPR using a Laerdal manikin. The primary outcome was the number of unimpaired inflations, defined as the peak of the inflation occurring after chest compression and lasting at least 0.35 s before the following chest compression takes place. The secondary outcomes were tidal volume delivered and heart compression rate. To simulate potential distractions, the entire scenario was performed with or without a quiz. Statistically, a mixed model assessing fixed effects for experience, profession, device, and distraction was used to analyze the data. For direct comparison, one-way ANOVA with Bonferroni‘s correction was applied.
Results
The number of unimpaired inflations was highest in health care professionals using the BVM with a mean ± standard deviation of 12.8 ± 2.8 (target: 15 within 30 s). However, the tidal volumes were too large in this group with a tidal volume of 42.5 ± 10.9 ml (target: 25–30 ml). The number of unimpaired breaths with the mechanical ventilator and the T-piece system were 11.6 (±3.6) and 10.1 (±3.7), respectively. Distraction did not change these outcomes, except for the significantly lower tidal volumes with the T-piece during the quiz.
Conclusions
In summary, for our health care professionals, ventilation using the mechanical ventilator seemed to provide the best approach during CPR, especially in a population of preterm infants prone to volutrauma.
Acknowledgements
We thank Laerdal Medical GmbH® (Puchheim, Germany) for providing the resuscitation manikin for this study. We thank all participants in this resuscitation simulation study. We would like to thank Prof. Benjamin Mayer, Medical Biometry, Ulm University, for his help with statistical analysis of our data. The publication costs are kindly covered by Short Grant 2023__SG_027 provided by the University of Zurich.
Disclosure statement
None of the authors has any conflict of interest to declare.
Data availability statement
Data will be available upon request.