Literature DB >> 29248620

Interobserver Reliability of the Berlin ARDS Definition and Strategies to Improve the Reliability of ARDS Diagnosis.

Michael W Sjoding1, Timothy P Hofer2, Ivan Co3, Anthony Courey4, Colin R Cooke5, Theodore J Iwashyna6.   

Abstract

BACKGROUND: Failure to reliably diagnose ARDS may be a major driver of negative clinical trials and underrecognition and treatment in clinical practice. We sought to examine the interobserver reliability of the Berlin ARDS definition and examine strategies for improving the reliability of ARDS diagnosis.
METHODS: Two hundred five patients with hypoxic respiratory failure from four ICUs were reviewed independently by three clinicians, who evaluated whether patients had ARDS, the diagnostic confidence of the reviewers, whether patients met individual ARDS criteria, and the time when criteria were met.
RESULTS: Interobserver reliability of an ARDS diagnosis was "moderate" (kappa = 0.50; 95% CI, 0.40-0.59). Sixty-seven percent of diagnostic disagreements between clinicians reviewing the same patient was explained by differences in how chest imaging studies were interpreted, with other ARDS criteria contributing less (identification of ARDS risk factor, 15%; cardiac edema/volume overload exclusion, 7%). Combining the independent reviews of three clinicians can increase reliability to "substantial" (kappa = 0.75; 95% CI, 0.68-0.80). When a clinician diagnosed ARDS with "high confidence," all other clinicians agreed with the diagnosis in 72% of reviews. There was close agreement between clinicians about the time when a patient met all ARDS criteria if ARDS developed within the first 48 hours of hospitalization (median difference, 5 hours).
CONCLUSIONS: The reliability of the Berlin ARDS definition is moderate, driven primarily by differences in chest imaging interpretation. Combining independent reviews by multiple clinicians or improving methods to identify bilateral infiltrates on chest imaging are important strategies for improving the reliability of ARDS diagnosis.
Copyright © 2017 American College of Chest Physicians. All rights reserved.

Entities:  

Keywords:  ARDS; acute lung injury; clinical trials; diagnosis

Mesh:

Year:  2017        PMID: 29248620      PMCID: PMC5815873          DOI: 10.1016/j.chest.2017.11.037

Source DB:  PubMed          Journal:  Chest        ISSN: 0012-3692            Impact factor:   9.410


  29 in total

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4.  The threshold approach to clinical decision making.

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Review 5.  Computerised tomography scan imaging in acute respiratory distress syndrome.

Authors:  A Pesenti; P Tagliabue; N Patroniti; R Fumagalli
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6.  Interobserver variability in applying a radiographic definition for ARDS.

Authors:  G D Rubenfeld; E Caldwell; J Granton; L D Hudson; M A Matthay
Journal:  Chest       Date:  1999-11       Impact factor: 9.410

7.  The Berlin definition of ARDS: an expanded rationale, justification, and supplementary material.

Authors:  Niall D Ferguson; Eddy Fan; Luigi Camporota; Massimo Antonelli; Antonio Anzueto; Richard Beale; Laurent Brochard; Roy Brower; Andrés Esteban; Luciano Gattinoni; Andrew Rhodes; Arthur S Slutsky; Jean-Louis Vincent; Gordon D Rubenfeld; B Taylor Thompson; V Marco Ranieri
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8.  Acute respiratory distress syndrome: the Berlin Definition.

Authors:  V Marco Ranieri; Gordon D Rubenfeld; B Taylor Thompson; Niall D Ferguson; Ellen Caldwell; Eddy Fan; Luigi Camporota; Arthur S Slutsky
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9.  Pulmonary ultrasound and pulse oximetry versus chest radiography and arterial blood gas analysis for the diagnosis of acute respiratory distress syndrome: a pilot study.

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10.  Does training improve diagnostic accuracy and inter-rater agreement in applying the Berlin radiographic definition of acute respiratory distress syndrome? A multicenter prospective study.

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Journal:  Crit Care       Date:  2017-01-20       Impact factor: 9.097

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Journal:  Anal Bioanal Chem       Date:  2019-08-01       Impact factor: 4.142

2.  Rethinking pneumonia: A paradigm shift with practical utility.

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Authors:  Daniel Kotok; Libing Yang; John W Evankovich; William Bain; Daniel G Dunlap; Faraaz Shah; Yingze Zhang; Dimitris V Manatakis; Panayiotis V Benos; Ian J Barbash; Sarah F Rapport; Janet S Lee; Alison Morris; Bryan J McVerry; Georgios D Kitsios
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5.  Validating Measures of Disease Severity in Acute Respiratory Distress Syndrome.

Authors:  Yub Raj Sedhai; Mengdan Yuan; Scott W Ketcham; Ivan Co; Dru D Claar; Jakob I McSparron; Hallie C Prescott; Michael W Sjoding
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6.  A Computable Phenotype for Acute Respiratory Distress Syndrome Using Natural Language Processing and Machine Learning.

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7.  Clinician Recognition of the Acute Respiratory Distress Syndrome: Risk Factors for Under-Recognition and Trends Over Time.

Authors:  Matthew Schwede; Robert Y Lee; Hanjing Zhuo; Kirsten N Kangelaris; Alejandra Jauregui; Kathryn Vessel; Annika Belzer; Thomas Deiss; Michael A Matthay; Kathleen D Liu; Carolyn S Calfee
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8.  Electronic "Sniffer" Systems to Identify the Acute Respiratory Distress Syndrome.

Authors:  Max T Wayne; Thomas S Valley; Colin R Cooke; Michael W Sjoding
Journal:  Ann Am Thorac Soc       Date:  2019-04

9.  Differences between Patients in Whom Physicians Agree and Disagree about the Diagnosis of Acute Respiratory Distress Syndrome.

Authors:  Michael W Sjoding; Timothy P Hofer; Ivan Co; Jakob I McSparron; Theodore J Iwashyna
Journal:  Ann Am Thorac Soc       Date:  2019-02

10.  Rapidly Improving ARDS in Therapeutic Randomized Controlled Trials.

Authors:  Edward J Schenck; Clara Oromendia; Lisa K Torres; David A Berlin; Augustine M K Choi; Ilias I Siempos
Journal:  Chest       Date:  2018-10-22       Impact factor: 9.410

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