ArticleFrontiers in public health2025
Impact of antidote quantity, timing and prehospital strategies in nerve agent mass casualty events: a simulation study.
Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Mass casualty incidents (MCIs) involving nerve agents pose major challenges for emergency medical response due to rapid symptom onset, hazardous environments, and operational uncertainties. Several gaps remain in the knowledge about the prehospital response to nerve agent MCI treatment strategies and logistical decision-making. To address these gaps, this study uses Discrete Event Simulation to evaluate the impact of advanced medical stabilization (AMS) team arrival time, antidote availability, and evacuation policy on patient survival during an urban chemical-traumatic MCI with a subway sarin release scenario. Methods: A validated simulation model (SIMEDIS) was adapted to represent the full prehospital response chain, including triage, antidote administration, AMS, dry decontamination, further on-site stabilization in the forward medical post and transport to categorized hospitals. Two transport policies were modeled: Scoop&Run (rapid transport of victims to hospitals) and Stay&Play (on-site stabilization before transport). We simulated various AMS team arrival times and antidote availability scenarios to assess their impact on survival. Locations of deaths were analyzed to identify critical points of failure in the medical response chain. Results: AMS team arrival time, antidote availability, and evacuation policy significantly influenced mortality among the 25 salvageable victims. The number of deaths ranged from 8.0 (32%) in the most favorable case to 23.8 (95.2%) in the least favorable. Earlier AMS team arrival and greater antidote availability were associated with fewer deaths, particularly under the Scoop&Run policy. Stay&Play resulted in more deaths unless medical and transport capacity were significantly enhanced. Location-of-death analysis revealed preventable bottlenecks, especially during decontamination and hospital transport under the Stay&Play model. Discussion: The results highlight the importance of rapid hospital transport, swift antidote availability and administration during urban chemical MCIs. AMS team arrival time emerged as the strongest predictor of preventable mortality, showing a sigmoid-shaped curve where delays beyond 11 min led to sharp increases in death. Antidote supply showed a dose-dependent effect, but the impact diminishes with delayed administration, underscoring the need for timely delivery over sheer volume. To reduce preventable deaths in chemical MCIs, policy makers should focus on streamlining AMS team deployment, prioritizing rapid evacuation, and addressing logistical bottlenecks in decontamination and transport.
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.