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A simple tool to predict hospital admissions in bronchiectasis

Waleed Salih, Lucy Popellwell, Richard Stretton, James Chalmers, Thomas Fardon
European Respiratory Journal 2013 42: 4644; DOI:
Waleed Salih
1Tayside Respiratory Research Group, Ninewells Hospital and Medical School, Dundee, United Kingdom
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Lucy Popellwell
1Tayside Respiratory Research Group, Ninewells Hospital and Medical School, Dundee, United Kingdom
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Richard Stretton
1Tayside Respiratory Research Group, Ninewells Hospital and Medical School, Dundee, United Kingdom
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James Chalmers
1Tayside Respiratory Research Group, Ninewells Hospital and Medical School, Dundee, United Kingdom
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Thomas Fardon
1Tayside Respiratory Research Group, Ninewells Hospital and Medical School, Dundee, United Kingdom
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Abstract

Introduction

Hospital admissions for bronchiectasis are increasing. Identifying patients at risk may help guide treatment and prevention strategies. Although diseases such as COPD have well established severity scores, there are no prognostic tools in bronchiectasis. The aim of this study was to identify risk factors predicting hospitalisation for severe exacerbations of bronchiectasis.

Methods

100 consecutive patients attending a specialist bronchiectasis clinic were studied. Variables recorded: FEV1, age, gender,sputum microbiology,MRC dysnoea score, smoking status,body mass index and the Reiff radiology severity score. Independent risk factors for hospitalisation during follow-up were identified.Data are presented as odds ratios(OR)with 95% confidence intervals.

Results

Patients' median age was 66 years(IQR 58-73) with 27% of patients hospitalised during follow-up. Significant risk factors for hospitalisation were MRC dyspnoea score > 3 OR 2.9(1.7-7.2,p=0.02),FEV1 <50% OR 3.3(1.1-10.4,p=0.04),>3 lobes involved on CT or cystic bronchiectasis OR 7.7(2.8-21.3,p<0.0001)and Pseudomonas aeruginosa colonization OR 4.5(1.3-15.8,p=0.01). A scoring system awarding 1 point for each of these risk factors accurately identified risk of hospital admissions.

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The area under the receiver operator characteristic curve for the score was 0.78(0.73-0.83),p<0.0001.

Conclusion

Bronchiectasis associated hospital admissions can be predicted using simple severity criteria.

  • Bronchiectasis
  • Infections
  • Spirometry
  • © 2013 ERS
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A simple tool to predict hospital admissions in bronchiectasis
Waleed Salih, Lucy Popellwell, Richard Stretton, James Chalmers, Thomas Fardon
European Respiratory Journal Sep 2013, 42 (Suppl 57) 4644;

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A simple tool to predict hospital admissions in bronchiectasis
Waleed Salih, Lucy Popellwell, Richard Stretton, James Chalmers, Thomas Fardon
European Respiratory Journal Sep 2013, 42 (Suppl 57) 4644;
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