ArticleCritical care medicine2011
Short-term mortality prediction for acute lung injury patients: external validation of the Acute Respiratory Distress Syndrome Network prediction model.
Article in Critical care medicine, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 22 citations in OpenAlex.
- 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
- APACHE III Outcome Prediction in Patients Admitted to the Intensive Care Unit with Sepsis Associated Acute Lung Injury.PloS one · 2015Trial
- External Validation of a Risk Score for Daily Prediction of Atrial Fibrillation among Critically Ill Patients with Sepsis.Annals of the American Thoracic Society · 2022Article
- Development and Verification of a Digital Twin Patient Model to Predict Specific Treatment Response During the First 24 Hours of Sepsis.Critical care explorations · 2020Article
- Macrophage TLR4 and PAR2 Signaling: Role in Regulating Vascular Inflammatory Injury and Repair.Frontiers in immunology · 2020Review
- Article
- Disruption of staphylococcal aggregation protects against lethal lung injury.The Journal of clinical investigation · 2018Article
- A mortality score for acute respiratory distress syndrome: predicting the future without a crystal ball.Journal of thoracic disease · 2016Article
- Integrative assessment of chlorine-induced acute lung injury in mice.American journal of respiratory cell and molecular biology · 2012Article
- Derecruitment test and surfactant therapy in patients with acute lung injury.Critical care research and practice · 2012Article
- Acute respiratory distress syndrome: A clinical review.Pulmonary circulationArticle
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Authors and funding
9 authors at 3 institutions in 1 country.
Funding
Abstract
objectiveAn independent cohort of patients with acute lung injury was used to evaluate the external validity of a simple prediction model for short-term mortality previously developed using data from Acute Respiratory Distress Syndrome Network (ARDSNet) trials.
designData for external validation were obtained from a prospective cohort study of patients with acute lung injury.
settingThirteen intensive care units at four teaching hospitals in Baltimore, MD. PATIENTS: Five hundred and eight nontrauma patients with acute lung injury.
interventionsNone. MEASUREMENTS AND MAIN
resultsOf the 508 patients eligible for this analysis, 234 (46%) died inhospital. Discrimination of the ARDSNet prediction model for inhospital mortality, evaluated by the area under the receiver operator characteristic curves, was 0.67 for our external validation data set vs. 0.70 and 0.68 using Acute Physiology and Chronic Health Evaluation II and the ARDSNet validation data set, respectively. In evaluating calibration of the model, predicted vs. observed inhospital mortality for the external validation data set was similar for both low-risk (ARDSNet model score = 0) and high-risk (score = 3 or 4+) patient strata. However, for intermediate-risk (score = 1 or 2) patients, observed inhospital mortality was substantially higher than predicted mortality (25.3% vs. 16.5% and 40.6% vs. 31.0% for score = 1 and 2, respectively). Sensitivity analyses limiting our external validation data set to only those patients meeting the ARDSNet trial eligibility criteria and to those who received mechanical ventilation in compliance with the ARDSNet ventilation protocol did not substantially change the model's discrimination or improve its calibration.
conclusionsEvaluation of the ARDSNet prediction model using an external acute lung injury cohort demonstrated similar discrimination of the model as was observed with the ARDSNet validation data set. However, there were substantial differences in observed vs. predicted mortality among intermediate-risk patients with acute lung injury. The ARDSNet model provided reasonable, but imprecise, estimates of predicted mortality when applied to our external validation cohort of patients with acute lung injury.
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