ArticleAEM education and training2023
The impact of a smartphone-based cognitive aid on clinical performance during cardiac arrest simulations: A randomized controlled trial.
Article in AEM education and training, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 7 citations in OpenAlex.
- Cognitive aids used in simulated resuscitation: A systematic review.Resuscitation plus · 2024Review
- ChatGPT's Performance in Cardiac Arrest and Bradycardia Simulations Using the American Heart Association's Advanced Cardiovascular Life Support Guidelines: Exploratory Study.Journal of medical Internet research · 2024Article
- The impact of a smartphone-based cognitive aid on clinical performance during cardiac arrest simulations: A randomized controlled trial.AEM education and training · 2023Article
- Validation of a Novel Mobile Application for Assessing Pediatric Tracheostomy Emergency Simulations.OTO openArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objectives: In-hospital cardiac arrests are common and associated with high mortality. Smartphone applications offer quick access to algorithms and timers but often lack real-time guidance. This study assesses the impact of the Code Blue Leader application on the performance of providers leading cardiac arrest simulations. Methods: This open-label randomized controlled trial included Advanced Cardiac Life Support (ACLS)-trained medical doctors (MD) and registered nurses (RN). Participants were randomized to lead the same ACLS simulation with or without the app. The primary outcome, "performance score," was assessed by a trained rater using a validated ACLS scoring system. Secondary outcomes included percentage of critical actions performed, number of incorrect actions, and chest compression fraction (percentage of time spent performing chest compressions). A sample size of 30 participants was calculated to detect a difference of 20% at the 0.05 alpha level with 90% power. Results: Fifteen MDs and 15 RNs underwent stratified randomization. The median (interquartile range) performance score in the app group was 95.3% (93.0%-100.0%) compared to 81.4% (60.5%-88.4%) in the control group, demonstrating an effect size of Conclusions: The Code Blue Leader smartphone app significantly improved the performance of ACLS-trained providers in cardiac arrest simulations.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.