Trial reportCritical care (London, England)2017
Does training improve diagnostic accuracy and inter-rater agreement in applying the Berlin radiographic definition of acute respiratory distress syndrome? A multicenter prospective study.
Trial report in Critical care (London, England), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01704066 (Interobserver Variation in Applying a Radiographic Definition for ARDS), which is not on this map. Cited by 23 papers.
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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.
Interobserver Variation in Applying a Radiographic Definition for ARDS: Impact of a Training Set of Berlin ARDS Definition
Who cites it
23 citing papers in PubMed.
- Agreement between chest radiograph and computed tomography for the diagnosis of acute respiratory distress syndrome: A retrospective observational study.Annals of intensive care · 2026Article
- Nanomedicine for Acute Respiratory Distress Syndrome: From Pathophysiological Mechanisms and Disease Heterogeneity to Precision Therapy.International journal of nanomedicine · 2026Review
- Advances in acute respiratory distress syndrome: focusing on heterogeneity, pathophysiology, and therapeutic strategies.Signal transduction and targeted therapy · 2025Review
- Leveraging Multi-Annotator Label Uncertainties as Privileged Information for Acute Respiratory Distress Syndrome Detection in Chest X-ray Images.Bioengineering (Basel, Switzerland) · 2024Article
- The Global Definition of Acute Respiratory Distress Syndrome: Ready for Prime Time?American journal of respiratory and critical care medicine · 2024Article
- Article
- Generative Artificial Intelligence for Chest Radiograph Interpretation in the Emergency Department.JAMA network open · 2023Article
- The Subgroup Imperative: Chest Radiograph Classifier Generalization Gaps in Patient, Setting, and Pathology Subgroups.Radiology. Artificial intelligence · 2023Article
- Inter-rater reliability of the Silverman and Andersen index-a measure of respiratory distress in preterm infants.PloS one · 2023Article
- Respiratory Subsets in Patients with Moderate to Severe Acute Respiratory Distress Syndrome for Early Prediction of Death.Journal of clinical medicine · 2022Review
- The effect of a training webinar on decreasing inter-observer variability in making a radiologic diagnosis of bronchiectasis.BMC medical imaging · 2022Article
- Improvement of an interobserver agreement of ARDS diagnosis by adding additional imaging and a confidence scale.Frontiers in medicine · 2022Article
- Development and evaluation of a survey instrument to assess veterinary medical record suitability for multi-center research studies.Frontiers in veterinary science · 2022Article
- Automated detection of acute respiratory distress syndrome from chest X-Rays using Directionality Measure and deep learning features.Computers in biology and medicine · 2021Article
- Deep learning to detect acute respiratory distress syndrome on chest radiographs: a retrospective study with external validation.The Lancet. Digital health · 2021Article
- The relationship of tidal volume and driving pressure with mortality in hypoxic patients receiving mechanical ventilation.PloS one · 2021Article
- Prognostic relevance and inter-observer reliability of chest-imaging in pediatric ARDS: a pediatric acute respiratory distress incidence and epidemiology (PARDIE) study.Intensive care medicine · 2020Observational
- Clinician Recognition of the Acute Respiratory Distress Syndrome: Risk Factors for Under-Recognition and Trends Over Time.Critical care medicine · 2020Article
- Time to stop randomized and large pragmatic trials for intensive care medicine syndromes: the case of sepsis and acute respiratory distress syndrome.Journal of thoracic disease · 2020Review
- Differences between Patients in Whom Physicians Agree and Disagree about the Diagnosis of Acute Respiratory Distress Syndrome.Annals of the American Thoracic Society · 2019Article
Corrections and comments
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Authors and funding
26 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPoor inter-rater reliability in chest radiograph interpretation has been reported in the context of acute respiratory distress syndrome (ARDS), although not for the Berlin definition of ARDS. We sought to examine the effect of training material on the accuracy and consistency of intensivists' chest radiograph interpretations for ARDS diagnosis.
methodsWe conducted a rater agreement study in which 286 intensivists (residents 41.3%, junior attending physicians 35.3%, and senior attending physician 23.4%) independently reviewed the same 12 chest radiographs developed by the ARDS Definition Task Force ("the panel") before and after training. Radiographic diagnoses by the panel were classified into the consistent (n = 4), equivocal (n = 4), and inconsistent (n = 4) categories and were used as a reference. The 1.5-hour training course attended by all 286 intensivists included introduction of the diagnostic rationale, and a subsequent in-depth discussion to reach consensus for all 12 radiographs.
resultsOverall diagnostic accuracy, which was defined as the percentage of chest radiographs that were interpreted correctly, improved but remained poor after training (42.0 ± 14.8% before training vs. 55.3 ± 23.4% after training, p < 0.001). Diagnostic sensitivity and specificity improved after training for all diagnostic categories (p < 0.001), with the exception of specificity for the equivocal category (p = 0.883). Diagnostic accuracy was higher for the consistent category than for the inconsistent and equivocal categories (p < 0.001). Comparisons of pre-training and post-training results revealed that inter-rater agreement was poor and did not improve after training, as assessed by overall agreement (0.450 ± 0.406 vs. 0.461 ± 0.575, p = 0.792), Fleiss's kappa (0.133 ± 0.575 vs. 0.178 ± 0.710, p = 0.405), and intraclass correlation coefficient (ICC; 0.219 vs. 0.276, p = 0.470).
conclusionsThe radiographic diagnostic accuracy and inter-rater agreement were poor when the Berlin radiographic definition was used, and were not significantly improved by the training set of chest radiographs developed by the ARDS Definition Task Force.
trial registrationThe study was registered at ClinicalTrials.gov (registration number NCT01704066 ) on 6 October 2012.
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