Evidence map›Paper›PMID 33206233›Full record

ArticleEuropean journal of trauma and emergency surgery : official publication of the European Trauma Society2022

Mass Casualty Incident (MCI) training in a metropolitan university hospital: short-term experience with MAss Casualty SIMulation system MACSIM

Laura Castoldi, Massimiliano Greco, Michele Carlucci, Kristina Lennquist Montán, Roberto Faccincani

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Article in European journal of trauma and emergency surgery : official publication of the European Trauma Society, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

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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

7 citing papers in PubMed.

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  7. Hospital preparedness for mass gathering events and mass casualty incidents in Matera, Italy, European Capital of Culture 2019.European journal of trauma and emergency surgery : official publication of the European Trauma Society · 2022
    Article
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.

Laura CastoldiDepartment of Emergency Surgery, Foundation IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy. laura.castoldi@policlinico.mi.it.
Massimiliano GrecoDepartment of Anesthesia and Intensive Care, Humanitas Clinical and Research Center - IRCCS, Rozzano, Milan, Italy.
Michele CarlucciDepartment of General and Emergency Surgery, IRCCS San Raffaele, Milan, Italy.
Kristina Lennquist MontánDepartment of Public Health Sciences, Karolinska Institute, Stockholm, Sweden.
Roberto FaccincaniDepartment of General and Emergency Surgery, IRCCS San Raffaele, Milan, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimThe aim of this study was to test and validate a new hospital Mass Casualty Incident (MCI) training using MACSIM

methodsThe original MCI training format called MACSIM-PEMAF (Piano di Emergenza per il Massiccio Afflusso di Feriti, i.e., hospital disaster plan for massive influx of casualties) was developed for the Italian Society for Trauma and Emergency Surgery (SICUT) in 2016. It uses MACSIM

resultsMACSIM-PEMAF was tested over 7 courses, with a total of 258 participants. Pre- and post-course questionnaires showed a significant improvement for hospital staff in self-reported perceptions of knowledge and skills in MCI management. In total, on a 1-10 scale, all the staff increased their competencies from a value of 4.4 ± 2.5 to 7.5 ± 1.9 (p < 0.001).

conclusionMACSIM-PEMAF demonstrated efficacy in fulfilling the requirements of Italian law for PEMAF implementation, testing local resources and resilience, as well as increasing the self-reported perception of the hospital staff ability to respond to a MCI.

Indexed as

Disaster PlanningMass Casualty IncidentsComputer SimulationEmergency Service, HospitalHospitalsHumansPersonnel, HospitalTriageDisaster managementEmergency responseMCIMRMIPreparedness

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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.