Canadian Internal Medicine Ultrasound (CIMUS) Expert Consensus Statement on the Use of Lung Ultrasound for the Assessment of Medical Inpatients With Known or Suspected Coronavirus Disease 2019. Academic Article uri icon

Overview

abstract

  • OBJECTIVES: To develop a consensus statement on the use of lung ultrasound (LUS) in the assessment of symptomatic general medical inpatients with known or suspected coronavirus disease 2019 (COVID-19). METHODS: Our LUS expert panel consisted of 14 multidisciplinary international experts. Experts voted in 3 rounds on the strength of 26 recommendations as "strong," "weak," or "do not recommend." For recommendations that reached consensus for do not recommend, a fourth round was conducted to determine the strength of those recommendations, with 2 additional recommendations considered. RESULTS: Of the 26 recommendations, experts reached consensus on 6 in the first round, 13 in the second, and 7 in the third. Four recommendations were removed because of redundancy. In the fourth round, experts considered 4 recommendations that reached consensus for do not recommend and 2 additional scenarios; consensus was reached for 4 of these. Our final recommendations consist of 24 consensus statements; for 2 of these, the strength of the recommendations did not reach consensus. CONCLUSIONS: In symptomatic medical inpatients with known or suspected COVID-19, we recommend the use of LUS to: (1) support the diagnosis of pneumonitis but not diagnose COVID-19, (2) rule out concerning ultrasound features, (3) monitor patients with a change in the clinical status, and (4) avoid unnecessary additional imaging for patients whose pretest probability of an alternative or superimposed diagnosis is low. We do not recommend the use of LUS to guide admission and discharge decisions. We do not recommend routine serial LUS in patients without a change in their clinical condition.

publication date

  • December 4, 2020

Research

keywords

  • COVID-19
  • Inpatients

Identity

Scopus Document Identifier

  • 85097201934

Digital Object Identifier (DOI)

  • 10.1002/jum.15571

PubMed ID

  • 33274782

Additional Document Info

volume

  • 40

issue

  • 9