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Lung ultrasound in heart failure: Lessons from re‐analysis of Lung Ultrasound 2011 database
Author(s) -
Baker Kylie,
Mitchell Geoffrey,
Thompson Angus G,
Stieler Geoffrey,
Rippey James
Publication year - 2015
Publication title -
australasian journal of ultrasound in medicine
Language(s) - English
Resource type - Journals
eISSN - 2205-0140
pISSN - 1836-6864
DOI - 10.1002/j.2205-0140.2015.tb00018.x
Subject(s) - medicine , lung ultrasound , lung , ultrasound , diagnostic accuracy , false positive paradox , protocol (science) , radiology , emergency department , first line , pathology , artificial intelligence , alternative medicine , psychiatry , computer science
Abstract Introduction : In the setting of patients presenting with shortness of breath to an Emergency Department a simple lung ultrasound protocol aimed at detecting pulmonary oedema has been shown to have diagnostic accuracy of 85%. This article reviews data from the original study, in an attempt to determine whether adjusting the protocol and/or interpretive criteria would improve results. Method : A large lung ultrasound project provided the dataset. Inter‐rater and intertest discrepancies were reviewed. Then original stored images and comments were retrospectively analysed using alternate interpretive criteria. Specific variations included changing the number of B‐lines required to define ‘wet lung’ and assessing other pleural line abnormalities. Where they had been acquired cardiac loops were reviewed in addition to the lung images. Results : The 204 original studies available were reviewed. Some disagreement could be attributed to inexperience and unclear definitions. Adjusting the number of B‐lines did not improve diagnostic accuracy. All positive scans, with numerous B‐lines were reviewed using more advanced diagnostic criteria (pleural line abnormalities) and the number of false positives was decreased. In cases where cardiac views were available, their inclusion was beneficial. Conclusion : A simple lung ultrasound protocol to assess for ‘wet lung’ in patients presenting to Emergency Departments provides diagnostic accuracy of around 85% in the hands of relative novices. More advanced interpretation of the same_ultrasound images, and the addition of cardiac views, is likely to further improve diagnostic accuracy.