Teaching fiberoptic-assisted tracheoscopy in very low birth weight infants: A randomized controlled simulator study

Abstract

ObjectiveWe developed a fiberoptic-assisted tracheoscopy (FAST) method to avoid direct laryngoscopy during surfactant replacement therapy and compared two training approaches on a very low birth weight (VLBW) infant simulator.DesignThis prospective randomized controlled study was conducted at the Department of Neonatology and Pediatric Intensive Care Medicine of the University Medical Center Hamburg-Eppendorf, Germany.ParticipantsWe recruited physicians, trainees, students, and nurses without prior experience in endoscopic techniques.InterventionsParticipants were assigned randomly to a group that received instructions according to Peyton’s Four-Step Approach and a control group that received standard bedside teaching only.Main outcome measuresPrimary endpoints were the total and the component times required to place the bronchoscope and the method success.ResultsWe recruited 186 participants. Compared with the control group, the Peyton group had a lower mean (±standard deviation) FAST completion time (33.2 ± 27.5 s vs. 79.5 ± 47.9 s, p < 0.001; d = 1.12) and a higher FAST success rate (95% vs. 84%, p = 0.036, V = 0.18).ConclusionAfter standardized training, the vast majority of novices completed FAST successfully. Peyton’s four-step approach resulted in faster and more successful performance than standardized training.

Advancing arrhythmia education through the CDIO approach: a new paradigm in nursing student training

“…Given the limitations of the LBL method, it is imperative that we seek innovative teaching approaches. It has been shown that the new methods significantly elevate the caliber of nursing education by promoting active engagement and critical analysis, and also positively impact patient care [33][34][35][36]. Our study indicates that the CDIO model group participants outperformed the control group in both theoretical knowledge assessment and application capability evaluation, with a statistically significant difference after training (F = 12.116, p = 0.001 for theoretical knowledge; F = 23.681, p < 0.001 for application capability; Table S2).…”