Literature DB >> 29656607

Expert Agreement in the Interpretation of Lung Ultrasound Studies Performed on Mechanically Ventilated Patients.

Scott J Millington1, Robert T Arntfield1, Robert Jie Guo1, Seth Koenig1, Pierre Kory1, Vicki Noble1, Haney Mallemat1, Jordan R Schoenherr1.   

Abstract

OBJECTIVES: Although lung ultrasound (US) has been shown to have high diagnostic accuracy in patients presenting with acute dyspnea, its precision in critically ill patients is unknown. We investigated common areas of agreement and disagreement by studying 6 experts as they interpreted lung US studies in a cohort of intensive care unit (ICU) patients.
METHODS: A previous study by our group asked experts to rate the quality of 150 lung US studies performed by 10 novices in a population of mechanically ventilated patients. For this study, experts were asked to interpret them without the clinical context, reporting the presence of pneumothorax, interstitial syndrome, consolidation, atelectasis, or pleural effusion.
RESULTS: The rate of expert agreement depended on how it was defined, ranging from 51% (with a strict definition of agreement) to 57% (with a more liberal definition). Removing cases involving lung consolidation (the most common source of disagreement) improved the rates of agreement to 69% and 86%, respectively.
CONCLUSIONS: The frequency of agreement was lower than might have been expected in this study. Several potential reasons are identified, chief among them the fact that ICU patients often develop multiple pulmonary insults, making agreement on a specific primary diagnosis challenging. This finding suggests that the utility of lung US in identifying the main contributing lung condition in ICU patients may be lower than in dyspneic patients encountered in the emergency department. It also raises the possibility that the clinical context is more important for lung US than other imaging modalities.
© 2018 by the American Institute of Ultrasound in Medicine.

Entities:  

Keywords:  critical care; lung ultrasound; medical education; point-of-care ultrasound

Mesh:

Year:  2018        PMID: 29656607     DOI: 10.1002/jum.14627

Source DB:  PubMed          Journal:  J Ultrasound Med        ISSN: 0278-4297            Impact factor:   2.153


  5 in total

1.  The Inter-Rater Reliability of Pediatric Point-of-Care Lung Ultrasound Interpretation in Children With Acute Respiratory Failure.

Authors:  Ryan L DeSanti; Eileen A Cowan; Pierre D Kory; Michael R Lasarev; Jessica Schmidt; Awni M Al-Subu
Journal:  J Ultrasound Med       Date:  2021-08-11       Impact factor: 2.754

2.  Pulmonary consolidation alters the ultrasound estimate of pleural fluid volume when considering chest drainage in patients on ECMO.

Authors:  Martin Balik; Masego Candy Mokotedi; Michal Maly; Michal Otahal; Zdenek Stach; Eva Svobodova; Marek Flaksa; Jan Rulisek; Tomas Brozek; Michal Porizka
Journal:  Crit Care       Date:  2022-05-18       Impact factor: 19.334

3.  Development of a convolutional neural network to differentiate among the etiology of similar appearing pathological B lines on lung ultrasound: a deep learning study.

Authors:  Robert Arntfield; Blake VanBerlo; Thamer Alaifan; Nathan Phelps; Matthew White; Rushil Chaudhary; Jordan Ho; Derek Wu
Journal:  BMJ Open       Date:  2021-03-05       Impact factor: 2.692

4.  Interobserver Agreement of Lung Ultrasound Findings of COVID-19.

Authors:  Andre Kumar; Yingjie Weng; Sally Graglia; Sukyung Chung; Youyou Duanmu; Farhan Lalani; Kavita Gandhi; Viveta Lobo; Trevor Jensen; Jeffrey Nahn; John Kugler
Journal:  J Ultrasound Med       Date:  2021-01-11       Impact factor: 2.754

5.  Human-to-AI Interrater Agreement for Lung Ultrasound Scoring in COVID-19 Patients.

Authors:  Noreen Fatima; Federico Mento; Alessandro Zanforlin; Andrea Smargiassi; Elena Torri; Tiziano Perrone; Libertario Demi
Journal:  J Ultrasound Med       Date:  2022-07-07       Impact factor: 2.754

  5 in total

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