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Prediction of unsuccessful treatment in patients with severe acute asthma
  1. Steve Goodacre1,
  2. Mike Bradburn1,
  3. Judith Cohen1,
  4. Alasdair Gray2,
  5. Jonathan Benger3,
  6. Tim Coats4
  7. on behalf of the 3Mg Research Team
  1. 1School of Health and Related Research (ScHARR), University of Sheffield, Sheffield, UK
  2. 2Emergency Department, Royal Infirmary of Edinburgh, Edinburgh, UK
  3. 3Faculty of Health and Life Sciences, University of the West of England, Bristol, UK
  4. 4Emergency Department, Leicester Royal Infirmary, Leicester, UK
  1. Correspondence to Professor Steve Goodacre, School of Health and Related Research (ScHARR), University of Sheffield, Regent Court, 30 Regent Street, Sheffield S1 4DA, UK; s.goodacre{at}sheffield.ac.uk

Abstract

Background Clinical assessment can be used to identify which patients with acute asthma are at risk of unsuccessful initial treatment.

Objective To determine which elements of clinical assessment predict unsuccessful treatment, defined as needing critical care or any unplanned additional treatment.

Methods We analysed data from a large multicentre trial (the 3Mg trial). Adults with severe acute asthma underwent standardised clinical assessment, including peak expiratory flow rate (PEFR), up to 2 h after initiation of treatment. Standard care was provided other than blinded random allocation to trial treatment or placebo. Patients were followed up by record review up to 30 days. Unsuccessful treatment was defined as needing (1) critical care or (2) critical care or any unplanned additional treatment within 7 days of presentation. Logistic regression was used to identify predictors and derive a prediction model for each outcome.

Results Out of 1084 patients analysed, 81 (7%) received critical care and 157 (14%) received critical care or unplanned additional treatment. Baseline PEFR (p=0.017), baseline heart rate (p<0.001), other serious illness (p=0.019), PEFR change (p=0.015) and heart rate change (p<0.001) predicted need for critical care. Baseline PEFR (p=0.010), baseline heart rate (p<0.001), baseline respiratory rate (p=0.017), other serious illness (p=0.023), PEFR change (p=0.003) and heart rate change (p=0.001) predicted critical care or additional treatment. Models based on these characteristics had c-statistics of 0.77 and 0.69, respectively.

Conclusions PEFR, heart rate and other serious illnesses are the best predictors of unsuccessful treatment, but models based on these variables provide modest predictive value.

  • Asthma
  • Clinical Assessment
  • Respiratory

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