ArticleNPJ digital medicine2022
Effectiveness of automated alerting system compared to usual care for the management of sepsis.
Article in NPJ digital medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 2 of them syntheses that pooled it.
What it found
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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
35 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- The Effect of Early Warning Systems for Sepsis on Mortality: A Systematic Review and Meta-analysis.Journal of general internal medicine · 2025Pooled it
- Sepsis Alert Systems, Mortality, and Adherence in Emergency Departments: A Systematic Review and Meta-Analysis.JAMA network open · 2024Pooled it
- A randomized controlled trial of artificial intelligence-based analytics for clinical deterioration.Scientific reports · 2026Trial
- Accuracy and Systematic Biases of Heart Rate Measurements by Consumer-Grade Fitness Trackers in Postoperative Patients: Prospective Clinical Trial.Journal of medical Internet research · 2022Trial
- Diagnostic Uncertainty and Antibiotic Timing in Sepsis: Observational Validation of a Dual-Axis Decision Model.Critical care explorations · 2026Observational
- Systems Bioengineering of Septic Shock Metabolism: Citrulline, β-Hydroxybutyrate and Plasma Biomarker-Based Phenotyping.Biomolecules · 2026Review
- Hour-1 Sepsis Bundle: Updated Evidence.Journal of clinical medicine · 2026Review
- How Can Clinicians Decide if AI-Enabled Risk Prediction Models Are Fit for Purpose for Real World Use?Journal of evaluation in clinical practice · 2026Article
- Evaluating deep learning sepsis prediction models in ICUs under distribution shift: a multi-centre retrospective cohort study.NPJ digital medicine · 2026Article
- An artificial intelligence-powered learning health system to improve sepsis detection and quality of care: a before-and-after study.NPJ digital medicine · 2026Article
- Rethinking sepsis prediction in the era of large language models.npj health systems · 2026Article
- Artificial intelligence for improving decision-making in bacterial infection management: a narrative review.The Journal of antimicrobial chemotherapy · 2026Review
- Progress in sepsis prediction models: from traditional scoring systems to multimodal intelligence and clinical translation.Frontiers in medicine · 2026Review
- Digital Transformation in Critical Care: Implications for Quality of Care, Infection Control, and Clinical Outcomes.Journal of clinical medicine · 2025Article
- External validation of a widely available, localizable sepsis early detection model in the emergency department setting.The American journal of emergency medicine · 2025Article
- Transforming sepsis management: AI-driven innovations in early detection and tailored therapies.Critical care (London, England) · 2025Review
- AI-powered skin spectral imaging enables instant sepsis diagnosis and outcome prediction in critically ill patients.Science advances · 2025Observational
- Portable wireless monitoring of vital signs in hospital wards.BJA education · 2025Review
- Impact of the National Early Warning Score-based sepsis response system on hospital-onset sepsis in a tertiary hospital in South Korea.Acute and critical care · 2025Article
- A methodological systematic review of validation and performance of sepsis real-time prediction models.NPJ digital medicine · 2025Article
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
There is a large body of evidence showing that delayed initiation of sepsis bundle is associated with adverse clinical outcomes in patients with sepsis. However, it is controversial whether electronic automated alerts can help improve clinical outcomes of sepsis. Electronic databases are searched from inception to December 2021 for comparative effectiveness studies comparing automated alerts versus usual care for the management of sepsis. A total of 36 studies are eligible for analysis, including 6 randomized controlled trials and 30 non-randomized studies. There is significant heterogeneity in these studies concerning the study setting, design, and alerting methods. The Bayesian meta-analysis by using pooled effects of non-randomized studies as priors shows a beneficial effect of the alerting system (relative risk [RR]: 0.71; 95% credible interval: 0.62 to 0.81) in reducing mortality. The automated alerting system shows less beneficial effects in the intensive care unit (RR: 0.90; 95% CI: 0.73-1.11) than that in the emergency department (RR: 0.68; 95% CI: 0.51-0.90) and ward (RR: 0.71; 95% CI: 0.61-0.82). Furthermore, machine learning-based prediction methods can reduce mortality by a larger magnitude (RR: 0.56; 95% CI: 0.39-0.80) than rule-based methods (RR: 0.73; 95% CI: 0.63-0.85). The study shows a statistically significant beneficial effect of using the automated alerting system in the management of sepsis. Interestingly, machine learning monitoring systems coupled with better early interventions show promise, especially for patients outside of the intensive care unit.
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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.