Prediction of unsuccessful treatment in patients with severe acute asthma. Issue Volume 31:Issue e1(2014) (29th August 2013)

• Record Type: Journal Article
• Authors: Goodacre, Steve; Bradburn, Mike; Cohen, Judith; Gray, Alasdair; Benger, Jonathan; Coats, Tim
• Is Part Of: Emergency medicine journal. Volume 31:Issue e1(2014)
• Page Start: e40
• Page End: e45
• Publication Date: 2013-08-29
• Subjects: Asthma -- Clinical Assessment -- Respiratory; Emergency medicine -- Periodicals; 616.02505
• DOI: 10.1136/emermed-2013-203046
• Languages: English
• ISSNs: 1472-0205

Abstract

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.