Prediction of unsuccessful treatment in patients with severe acute asthma
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Goodacre, Steve
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Bradburn, Mike
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Univ Sheffield, Sch Hlth & Related Res ScHARR, Sheffield S1 4DA, S Yorkshire, EnglandUniv Sheffield, Sch Hlth & Related Res ScHARR, Sheffield S1 4DA, S Yorkshire, England
Bradburn, Mike
[1
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Cohen, Judith
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Univ Sheffield, Sch Hlth & Related Res ScHARR, Sheffield S1 4DA, S Yorkshire, EnglandUniv Sheffield, Sch Hlth & Related Res ScHARR, Sheffield S1 4DA, S Yorkshire, England
Cohen, Judith
[1
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Gray, Alasdair
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Royal Infirm Edinburgh NHS Trust, Emergency Dept, Edinburgh, Midlothian, ScotlandUniv Sheffield, Sch Hlth & Related Res ScHARR, Sheffield S1 4DA, S Yorkshire, England
Gray, Alasdair
[2
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Benger, Jonathan
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Univ W England, Fac Hlth & Life Sci, Bristol BS16 1QY, Avon, EnglandUniv Sheffield, Sch Hlth & Related Res ScHARR, Sheffield S1 4DA, S Yorkshire, England
Benger, Jonathan
[3
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Coats, Tim
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Leicester Royal Infirm, Emergency Dept, Leicester, Leics, EnglandUniv Sheffield, Sch Hlth & Related Res ScHARR, Sheffield S1 4DA, S Yorkshire, England
Coats, Tim
[4
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[1] Univ Sheffield, Sch Hlth & Related Res ScHARR, Sheffield S1 4DA, S Yorkshire, England
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.
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Assistance Publ Hop Paris, Hop Univ Bicetre, Serv Med Interne, Unite Pneumol, Le Kremlin Bicetre, FranceAssistance Publ Hop Paris, Hop Univ Bicetre, Serv Med Interne, Unite Pneumol, Le Kremlin Bicetre, France
Salmeron, S
Bard, M
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机构:Assistance Publ Hop Paris, Hop Univ Bicetre, Serv Med Interne, Unite Pneumol, Le Kremlin Bicetre, France
Bard, M
Blanc, FX
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机构:Assistance Publ Hop Paris, Hop Univ Bicetre, Serv Med Interne, Unite Pneumol, Le Kremlin Bicetre, France
Blanc, FX
Ellrodt, A
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机构:Assistance Publ Hop Paris, Hop Univ Bicetre, Serv Med Interne, Unite Pneumol, Le Kremlin Bicetre, France