ArticleJournal of critical care2013
Improving risk classification of critical illness with biomarkers: a simulation study.
Article in Journal of critical care, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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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.
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Who cites it
13 citing papers in PubMed.
- Availability of suPAR in emergency departments may improve risk stratification: a secondary analysis of the TRIAGE III trial.Scandinavian journal of trauma, resuscitation and emergency medicine · 2019Trial
- Early Discharge from the Emergency Department Based on Soluble Urokinase Plasminogen Activator Receptor (suPAR) Levels: A TRIAGE III Substudy.Disease markers · 2019Trial
- Use of the prognostic biomarker suPAR in the emergency department improves risk stratification but has no effect on mortality: a cluster-randomized clinical trial (TRIAGE III).Scandinavian journal of trauma, resuscitation and emergency medicine · 2018Trial
- The Copenhagen Triage Algorithm: a randomized controlled trial.Scandinavian journal of trauma, resuscitation and emergency medicine · 2016Trial
- Introduction of a prognostic biomarker to strengthen risk stratification of acutely admitted patients: rationale and design of the TRIAGE III cluster randomized interventional trial.Scandinavian journal of trauma, resuscitation and emergency medicine · 2016Trial
- Utilization of Prognostic Biomarker Soluble Urokinase Plasminogen Activator Receptor in the Emergency Department: A Tool for Safe and More Efficient Decision-making.Biomarker insights · 2022Article
- Associations between molecular characteristics of colorectal serrated polyps and subsequent advanced colorectal neoplasia.Cancer causes & control : CCC · 2020Article
- Germline variants in IL4, MGMT and AKT1 are associated with prostate cancer-specific mortality: An analysis of 12,082 prostate cancer cases.Prostate cancer and prostatic diseases · 2018Article
- Routine blood tests are associated with short term mortality and can improve emergency department triage: a cohort study of >12,000 patients.Scandinavian journal of trauma, resuscitation and emergency medicine · 2017Observational
- The formation and design of the TRIAGE study--baseline data on 6005 consecutive patients admitted to hospital from the emergency department.Scandinavian journal of trauma, resuscitation and emergency medicine · 2015Observational
- Charting a roadmap for heart failure biomarker studies.JACC. Heart failure · 2014Review
- Circulating levels of liver enzymes and incidence of atrial fibrillation: the Atherosclerosis Risk in Communities cohort.Heart (British Cardiac Society) · 2014Article
- Pre-resuscitation lactate and hospital mortality in prehospital patients.Prehospital emergency careObservational
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
purposeOptimal triage of patients at risk for critical illness requires accurate risk prediction, yet few data on the performance criteria required of a potential biomarker to be clinically useful exists. MATERIALS AND
methodsWe studied an adult cohort of nonarrest, nontrauma emergency medical services encounters transported to a hospital from 2002 to 2006. We simulated hypothetical biomarkers increasingly associated with critical illness during hospitalization and determined the biomarker strength and sample size necessary to improve risk classification beyond a best clinical model.
resultsOf 57,647 encounters, 3121 (5.4%) were hospitalized with critical illness and 54,526 (94.6%) without critical illness. The addition of a moderate-strength biomarker (odds ratio, 3.0, for critical illness) to a clinical model improved discrimination (c statistic, 0.85 vs 0.8; P<.01) and reclassification (net reclassification improvement, 0.15; 95% confidence interval, 0.13-0.18) and increased the proportion of cases in the highest-risk category by +8.6% (95% confidence interval, 7.5%-10.8%). Introducing correlation between the biomarker and physiological variables in the clinical risk score did not modify the results. Statistically significant changes in net reclassification required a sample size of at least 1000 subjects.
conclusionsClinical models for triage of critical illness could be significantly improved by incorporating biomarkers, yet substantial sample sizes and biomarker strength may be required.
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