Evidence map›Paper›PMID 42596010›Full record

Trial reportScandinavian journal of trauma, resuscitation and emergency medicine2026

Effect of an app-guided advanced cardiac life support algorithm on teamwork, non-technical skills, and workload in simulated in-hospital cardiac arrest: a randomized controlled feasibility trial.

Anne Kamphausen, Maximilian Pilz, Matthias Baumgärtel, Jens Christian Kubitz, Christian Engelen

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in Scandinavian journal of trauma, resuscitation and emergency medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Anne KamphausenDepartment of Anesthesia and Intensive Care Medicine, General Hospital Nuremberg, Paracelsus Medical University, Prof. Ernst-Nathan Straße 1, 90419, Nuremberg, Germany. anne.kamphausen@klinikum-nuernberg.de.ORCID https://orcid.org/0000-0002-2647-5202
Maximilian PilzGeorg Simon Ohm University of Applied Sciences Nuremberg, Nürnberg School of Health, Nuremberg, Germany.ORCID http://orcid.org/0000-0002-9685-1613
Matthias BaumgärtelDepartment of Pulmonology, Paracelsus Medical University, Nuremberg, Germany.
Jens Christian KubitzDepartment of Anesthesia and Intensive Care Medicine, General Hospital Nuremberg, Paracelsus Medical University, Prof. Ernst-Nathan Straße 1, 90419, Nuremberg, Germany.ORCID http://orcid.org/0000-0001-6634-5843
Christian EngelenEmergency Department, Lauf/Pegnitz Hospital, Lauf/Pegnitz, Germany.ORCID http://orcid.org/0009-0000-2647-1183

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn-hospital cardiac arrest carries high mortality despite advances in monitoring, rapid response systems, and adherence to advanced life support (ALS) guidelines. Digital decision-support tools, including mobile applications, are increasingly explored to improve guideline adherence, yet their impact on cognitive workload, team performance, and ALS performance remains uncertain.

methodsWe conducted a prospective, randomized, simulation-based controlled feasibility trial with 40 interprofessional teams (80 participants) comparing ALS performance with and without the use of the 'CPR Leader' app. Two-person teams were randomized 1:1 to intervention or control and followed standardized in-hospital cardiac arrest scenarios (asystole and ventricular fibrillation). Primary outcomes included team performance (TEAM), non-technical skills (ANTS), and subjective workload (NASA-TLX). Secondary outcomes comprised objective resuscitation metrics, including time to rhythm analysis, defibrillation, medication administration, and chest compression quality.

resultsOverall NASA-TLX scores were high but comparable between intervention and control group (mean 49.2 ± 13.6 vs. 54.1 ± 14.6; p = 0.2), with higher effort reported in the app group and higher frustration in the control group. TEAM and ANTS scores showed no evidence of meaningful between-group differences. Across the two scenarios types, ALS performance metrics-including rhythm analysis, defibrillation, medication administration, and chest compression quality-were similar between groups, with the exception of earlier chest compression initiation in the control group during ventricular fibrillation.

conclusionsIn this exploratory randomized simulation study involving predominantly experienced in-hospital healthcare professionals, the use of a resuscitation support application did not demonstrate a clear improvement in adherence to guideline-recommended ALS algorithms or resuscitation performance compared with standard practice. These findings likely reflect the high level of participants' clinical experience and should not be generalized to novice providers, mixed-experience teams, prehospital settings, or training environments. Further studies are warranted to evaluate the potential benefits of cognitive aids in less experienced populations and in real-world clinical practice. TRIAL NUMBER: None.

Indexed as

Advanced Cardiac Life SupportAlgorithmsClinical CompetenceHeart ArrestMobile ApplicationsPatient Care TeamWorkloadFeasibility StudiesFemaleHumansMaleProspective StudiesAdvanced life supportCognitive workloadIn-hospital cardiac arrestResuscitation appTeamwork

Identifiers

PMID42596010
PMCPMC13474723

What OpenQuestion holds

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Registered trials

None linked

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.