Pilot study of an interprofessional pediatric mechanical ventilation educational initiative in two intensive care units.

INTRODUCTION: Inappropriate ventilator settings, non-adherence to a lung-protective ventilation strategy, and inadequate patient monitoring during mechanical ventilation can potentially expose critically ill children to additional risks. We set out to improve team theoretical knowledge and practical skills regarding pediatric mechanical ventilation and to increase compliance with treatment goals. METHODS: An educational initiative was conducted from August 2019 to July 2021 in a neonatal and pediatric intensive care unit of the University Children's Hospital, Hamburg-Eppendorf, Germany. We tested baseline theoretical knowledge using a multiple choice theory test (TT) and practical skills using a practical skill test (PST), consisting of four sequential Objective Structured Clinical Examinations of physicians and nurses. We then implemented an educational bundle that included video self-training, checklists, pocket cards, and reevaluated team performance. Ventilators and monitor settings were randomly checked in all ventilated patients. We used a process control chart and a mixed-effects model to analyze the primary outcome. RESULTS: A total of 47 nurses and 20 physicians underwent assessment both before and after the implementation of the initiative using TT. Additionally, 34 nurses and 20 physicians were evaluated using the PST component of the initiative. The findings revealed a significant improvement in staff performance for both TT and PST (TT: 80% [confidence interval (CI): 77.2-82.9] vs. 86% [CI: 83.1-88.0]; PST: 73% [CI: 69.7-75.5] vs. 95% [CI: 93.8-97.1]). Additionally, there was a notable increase in self-confidence among participants, and compliance with mechanical ventilation treatment goals also saw a substantial rise, increasing from 87.8% to 94.5%. DISCUSSION: Implementing a pediatric mechanical ventilation education bundle improved theoretical knowledge and practical skills among interprofessional pediatric intensive care staff and increased treatment goal compliance in ventilated children.

Clustering by fuzzy neural gas and evaluation of fuzzy clusters.

We consider some modifications of the neural gas algorithm. First, fuzzy assignments as known from fuzzy c-means and neighborhood cooperativeness as known from self-organizing maps and neural gas are combined to obtain a basic Fuzzy Neural Gas. Further, a kernel variant and a simulated annealing approach are derived. Finally, we introduce a fuzzy extension of the ConnIndex to obtain an evaluation measure for clusterings based on fuzzy vector quantization.