ArticleAmerican journal of respiratory and critical care medicine2021
Detecting Deteriorating Patients in the Hospital: Development and Validation of a Novel Scoring System.
Article in American journal of respiratory and critical care medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 4 of them syntheses that pooled 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.
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
38 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Pooled it
- AI-Powered early warning systems for clinical deterioration significantly improve patient outcomes: a meta-analysis.BMC medical informatics and decision making · 2025Pooled it
- Factors underpinning the performance of implemented artificial intelligence-based patient deterioration prediction systems: reasons for selection and implications for hospitals and researchers.Journal of the American Medical Informatics Association : JAMIA · 2025Pooled it
- Systematic review and longitudinal analysis of implementing Artificial Intelligence to predict clinical deterioration in adult hospitals: what is known and what remains uncertain.Journal of the American Medical Informatics Association : JAMIA · 2024Pooled it
- STREAM: A data-driven framework for physiological state monitoring in ICU patients.PLOS digital health · 2026Article
- Observational
- Predicting ICU transfer for high-risk patients upon medical admission via the medical intensive care prediction score (MICAPS).BMC emergency medicine · 2026Article
- Observational
- Predicting patient deterioration with physiological data using AI: systematic review protocol.BMJ health & care informatics · 2025Article
- Multicenter Development and Prospective Validation of eCARTv5: A Gradient-Boosted Machine-Learning Early Warning Score.Critical care explorations · 2025Observational
- Unlocking opportunities to transform patient care: an expert insight on limitations and opportunities in patient monitoring.Intensive care medicine experimental · 2025Review
- The early warning paradox.NPJ digital medicine · 2025Article
- Mortality and Length of Stay Implications of Deterioration-Associated Transfer to the Intensive Care Unit over Different Time Frames.Health services insights · 2025Article
- New horizons in hospital-associated deconditioning: a global condition of body and mind.Age and ageing · 2024Review
- NEWS-2 Accuracy in Predicting Mortality and Severe Morbidity Among Hospitalized COVID-19 Patients: A Prospective Cohort Study.Journal of clinical medicine · 2024Article
- Intensive care unit admission criteria: a scoping review.Journal of the Intensive Care Society · 2024Article
- Use of artificial intelligence in critical care: opportunities and obstacles.Critical care (London, England) · 2024Review
- Deep Learning-Based Early Warning Score for Predicting Clinical Deterioration in General Ward Cancer Patients.Cancers · 2023Article
- Article
- AI and machine learning in resuscitation: Ongoing research, new concepts, and key challenges.Resuscitation plus · 2023Review
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
PubMed holds no abstract for this paper.
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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.