Abstract
The EMBARC consensus criteria can be used to identify and categorise pulmonary exacerbations (PEs) in clinical trials. This paper describes methods used to independently adjudicate PEs using modified EMBARC criteria in a large multicentre bronchiectasis trial (CLEAR ISRCTN89040295)
Methods
The Respiratory and Systemic Symptoms Questionnaire was used to objectively collect signs and symptoms at the onset of a PE. A mEMBARC PE was defined as ≥3 symptoms, with symptoms present for ≥48 h and prescription of an antibiotic. Individual sites recorded antibiotic use for PEs. An adjudication panel independently adjudicated and then agreed on PEs according to mEMBARC criteria. Data required to determine PEs using modified Fuchs criteria was also collected.
Results
Sites reported 462 PEs from 203 patients reported in the CLEAR trial. The adjudication panel categorised these exacerbations as: 239/462 (52%) fully qualifying mEMBARC pulmonary exacerbations (meeting all mEMBARC criteria), 32/462 (7%) partially qualifying mEMBARC PEs (≤3 symptoms present for ≥48 h or ≥3symptoms present for <48 h and antibiotics prescribed) and 191/462 (41%) non-mEMBARC PEs (antibiotics prescribed but symptoms and duration not met). When data was classified using modified Fuchs criteria a sensitivity analysis produced results that were consistent with the main trial results.
| Original language | English |
|---|---|
| Number of pages | 34 |
| Journal | ERJ Open Research |
| Early online date | 9 Jul 2026 |
| DOIs | |
| Publication status | Published online - 9 Jul 2026 |
Funding
The views expressed are those of the authors and do not necessarily reflect those of the NIHR. The CLEAR Trial was supported by a grant (15/100/01) from the National Institute for Health and Care Research Health Technology Assessment Programme; by the Belfast Health and Social Care Trust Charitable Funds; and by PARI Pharma, which provided in-kind contributions of equipment and consumables (e.g., nebulizer systems, hypertonic saline, and spirometers). JSB works at UCL/UCLH, which receives funding from the Department of Health’s NIHR Biomedical Research Centre’s funding scheme. We acknowledge the Professor John Glover Award for supporting the work of RA.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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