ArticleNature2019
A clinically applicable approach to continuous prediction of future acute kidney injury.
Article in Nature, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05735288 (Pilot-scale, Single-arm, Observational Study to Assess the Utility of a Machine Learning Algorithm in Assessing Fluid Status in Haemodialysis Patients), which is not on this map. Cited by 509 papers, 7 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.
Pilot-scale, Single-arm, Observational Study to Assess the Utility of a Machine Learning Algorithm in Assessing Fluid Status in Haemodialysis Patients
Who cites it
509 citing papers in PubMed, 7 syntheses or guidelines pooled it.
- AI Models for Predicting Acute Kidney Injury (AKI) and Post-AKI Mortality: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2026Pooled it
- Application of machine learning for the diagnosis and prognosis of sepsis-induced acute respiratory distress syndrome: a systematic review and meta-analysis.BMC medical informatics and decision making · 2026Pooled it
- Applications of Machine Learning for Cognitive Health in Older Individuals With HIV: Rapid Systematic Review.JMIR aging · 2025Pooled it
- Digital management of diabetes global research trends: a bibliometric study.Frontiers in medicine · 2025Pooled it
- A bibliometric analysis of artificial intelligence research in critical illness: a quantitative approach and visualization study.Frontiers in medicine · 2025Pooled it
- The application of machine learning in predicting post-cardiac surgery acute kidney injury in pediatric patients: a systematic review.Frontiers in pediatrics · 2025Pooled it
- Electronic Alert Systems for Patients With Acute Kidney Injury: A Systematic Review and Meta-Analysis.JAMA network open · 2024Pooled it
- Algorithm-assisted personalized risk communication to encourage flu vaccination in the USA: three randomized field trials.Nature human behaviour · 2026Article
- Prediction of Acute Kidney Injury in Oncology: From Clinical Risk Scores to AI-Enabled Precision Onco-Nephrology.Cancers · 2026Review
- Perspectives on the Limits and Clinical Alignment of Medical AI from Population Statistics to Individual Care.Bioengineering (Basel, Switzerland) · 2026Article
- Prediction of maternal and infant outcomes from longitudinal electronic health records with a mother-child AI agent.Nature medicine · 2026Article
- Article
- Risk analysis and warning model of post-noncardiac surgery acute kidney injury: A retrospective observational study.Medicine · 2026Observational
- Beyond eGFR and Albuminuria: Biological Pathways and Multiomics in Cardiovascular-Kidney-Metabolic Disease.Kidney international reports · 2026Review
- Large language model driven multicenter prediction and explainable risk attribution of acute kidney injury.Nature communications · 2026Article
- A lesson from the past and the future of artificial intelligence in medical decision-making.Journal of perinatology : official journal of the California Perinatal Association · 2026Review
- Development and External Validation of an Interpretable Machine Learning Framework for Predicting Pneumothorax-Associated Acute Kidney Injury: A Multicenter Retrospective Study.Journal of clinical medicine · 2026Article
- Artificial intelligence in nephrology: predicting CKD progression and personalizing treatment.International urology and nephrology · 2026Review
- Development and validation of an interpretable machine learning model for predicting sepsis risk in pleural effusion patients.Journal of thoracic disease · 2026Article
- Risk factors and predictive models for perioperative acute kidney injury in children: a narrative review.Translational pediatrics · 2026Review
449 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
27 authors.
Funding
Abstract
The early prediction of deterioration could have an important role in supporting healthcare professionals, as an estimated 11% of deaths in hospital follow a failure to promptly recognize and treat deteriorating patients
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.