ArticleIntensive care medicine2017
External validation of a biomarker and clinical prediction model for hospital mortality in acute respiratory distress syndrome.
Article in Intensive care medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.
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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
24 citing papers in PubMed, 1 synthesis or guideline pooled it, 41 citations in OpenAlex.
- Early Prediction of Mortality Risk in Acute Respiratory Distress Syndrome: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2025Pooled it
- Predicting mortality with machine learning & biomarkers: A cohort analysis from aerosolized β₂-agonist for treatment of acute lung injury (ALTA) trial.Physiological reports · 2026Trial
- Plasma matrix metalloproteinase-3 predicts mortality in acute respiratory distress syndrome: a biomarker analysis of a randomized controlled trial.Respiratory research · 2023Trial
- Development and validation of a clinical risk model to predict the hospital mortality in ventilated patients with acute respiratory distress syndrome: a population-based study.BMC pulmonary medicine · 2022Trial
- Predictive model for acute respiratory distress syndrome events in ICU patients in China using machine learning algorithms: a secondary analysis of a cohort study.Journal of translational medicine · 2019Trial
- Bronchoalveolar Lavage Fluid Microbial and Metabolic Alterations Associated with Acute Respiratory Distress Syndrome in Hospitalized Patients with Community-Acquired Pneumonia.Journal of inflammation research · 2026Article
- Association Between Temperature During Intensive Care Unit and Mortality in Patients With Acute Respiratory Distress Syndrome.Therapeutic hypothermia and temperature management · 2024Article
- Early predictive values of clinical assessments for ARDS mortality: a machine-learning approach.Scientific reports · 2024Observational
- Increased Alveolar Epithelial Damage Markers and Inflammasome-Regulated Cytokines Are Associated with Pulmonary Superinfection in ARDS.Journal of clinical medicine · 2023Article
- Prediction model for in-hospital mortality in patients at high altitudes with ARDS due to COVID-19.PloS one · 2023Article
- SARS-CoV-2-Infection (COVID-19): Clinical Course, Viral Acute Respiratory Distress Syndrome (ARDS) and Cause(s) of Death.Medical sciences (Basel, Switzerland) · 2022Review
- Phenotyping in acute respiratory distress syndrome: state of the art and clinical implications.Current opinion in critical care · 2022Review
- Identification and Validation of Autophagy-Related Genes in Sepsis-Induced Acute Respiratory Distress Syndrome and Immune Infiltration.Journal of inflammation research · 2022Article
- Advanced development and mechanism of sepsis-related acute respiratory distress syndrome.Frontiers in medicine · 2022Review
- Clinical and biological markers for predicting ARDS and outcome in septic patients.Scientific reports · 2021Observational
- Novel Perspectives Regarding the Pathology, Inflammation, and Biomarkers of Acute Respiratory Distress Syndrome.International journal of molecular sciences · 2020Review
- Refining the Syndrome.Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies · 2020Article
- Bioinformatics analysis of the potential biomarkers for acute respiratory distress syndrome.Bioscience reports · 2020Article
- Article
- Injury Characteristics and von Willebrand Factor for the Prediction of Acute Respiratory Distress Syndrome in Patients With Burn Injury: Development and Internal Validation.Annals of surgery · 2019Article
Corrections and comments
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Authors and funding
9 authors at 3 institutions in 1 country.
Funding
Abstract
purposeMortality prediction in ARDS is important for prognostication and risk stratification. However, no prediction models have been independently validated. A combination of two biomarkers with age and APACHE III was superior in predicting mortality in the NHLBI ARDSNet ALVEOLI trial. We validated this prediction tool in two clinical trials and an observational cohort.
methodsThe validation cohorts included 849 patients from the NHLBI ARDSNet Fluid and Catheter Treatment Trial (FACTT), 144 patients from a clinical trial of sivelestat for ARDS (STRIVE), and 545 ARDS patients from the VALID observational cohort study. To evaluate the performance of the prediction model, the area under the receiver operating characteristic curve (AUC), model discrimination, and calibration were assessed, and recalibration methods were applied.
resultsThe biomarker/clinical prediction model performed well in all cohorts. Performance was better in the clinical trials with an AUC of 0.74 (95% CI 0.70-0.79) in FACTT, compared to 0.72 (95% CI 0.67-0.77) in VALID, a more heterogeneous observational cohort. The AUC was 0.73 (95% CI 0.70-0.76) when FACTT and VALID were combined.
conclusionWe validated a mortality prediction model for ARDS that includes age, APACHE III, surfactant protein D, and interleukin-8 in a variety of clinical settings. Although the model performance as measured by AUC was lower than in the original model derivation cohort, the biomarker/clinical model still performed well and may be useful for risk assessment for clinical trial enrollment, an issue of increasing importance as ARDS mortality declines, and better methods are needed for selection of the most severely ill patients for inclusion.
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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.