Trial reportNature communications2025
Machine learning for risk stratification in the emergency department (MARS-ED): a randomized controlled trial.
Trial report in Nature communications, 2025. 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
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
4 citing papers in PubMed.
- Assessing Risk of Early ICU Admission or Death at Emergency Department Triage: Clinical Judgment Versus Early Warning Scores.Academic emergency medicine : official journal of the Society for Academic Emergency Medicine · 2026Observational
- Letter to the Editor: 'Using data and artificial intelligence to improve care pathways of older people experiencing falls and frailty: Opportunities, challenges and practical considerations for clinicians'.Clinical medicine (London, England) · 2026Article
- Using data and artificial intelligence to improve care pathways of older people experiencing falls and frailty: Opportunities, challenges and practical considerations for clinicians.Clinical medicine (London, England) · 2026Review
- Analysis of the predictive value of heart rate variability analysis combined with SOFA and APACHE II scores for the 28-day mortality risk of patients in the emergency intensive care unit.Frontiers in medicine · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Emergency department (ED) crowding necessitates rapid, accurate risk stratification to optimize care and resource allocation. Traditional clinical prediction tools like NEWS, APACHE II, and SOFA score have limited generalizability or rely on extensive inputs, including vitals. We developed RISK
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.