ReviewCureus2025
Accuracy and Timeliness of Prehospital Global Triage System Protocols in Mass Disasters: A Systematic Review of Systematic Reviews.
Review in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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
1 citing paper in PubMed.
- Performance of Sieve versus SwissPre Prehospital Triage Algorithms in a Simulated Mass-Casualty Incident: A Randomized Open-Label Study.Prehospital and disaster medicine · 2025Trial
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This systematic review evaluated the accuracy and timeliness of global prehospital triage systems in mass disasters, following Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) 2020 guidelines. A comprehensive search of PubMed/MEDLINE, Embase, Scopus, and Cochrane Library up to June 2025 identified 344 records, of which four studies met eligibility criteria after screening and full-text assessment. Included studies analyzed conventional systems such as Simple Triage and Rapid Treatment (START), JumpSTART, Sort, Assess, Lifesaving Interventions, Treatment/Transport (SALT), and Modified Physiological Triage Tool (MPTT), as well as artificial intelligence (AI)-assisted approaches and diagnostic adjuncts like portable ultrasound. Sample sizes ranged from targeted reviews of 30-60 studies (systematic and evidence-based reviews) to practical evaluations of triage innovations involving prehospital and emergency responders. Data extraction captured accuracy, timeliness, and resource allocation, while risk of bias was assessed using the A Measurement Tool to Assess Systematic Reviews version 2 (AMSTAR-2) and the Scale for the Assessment of Narrative Review Articles (SANRA), with ratings ranging from low to moderate. Results demonstrated that traditional systems such as START and SALT provide rapid categorization but remain prone to over- and under-triage depending on responder training and situational factors. AI-driven models and portable diagnostic technologies significantly improved decision speed, diagnostic precision, and prioritization of life-saving interventions, reducing delays in critical care. Overall, while no single algorithm proved universally superior, integration of training, simulation-based preparedness, and emerging AI-supported tools was consistently associated with improved triage performance in chaotic, resource-limited disaster environments.
Indexed as
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.