Development of a prediction tool for patients presenting with acute cough in primary care: A prognostic study spanning six European countries
Development of a prediction tool for patients presenting with acute cough in primary care: A prognostic study spanning six European countries
Background: Accurate prediction of the course of an acute cough episode could curb antibiotic overprescribing, but is still a major challenge in primary care.
Aim: The authors set out to develop a new prediction rule for poor outcome (re-consultation with new or worsened symptoms, or hospital admission) in adults presenting to primary care with acute cough.
Design and setting: Data were collected from 2604 adults presenting to primary care with acute cough or symptoms suggestive of lower respiratory tract infection (LRTI) within the Genomics to combat Resistance against Antibiotics in Community-acquired LRTI in Europe (GRACE; www.grace-lrti.org) Network of Excellence.
Method: Important signs and symptoms for the new prediction rule were found by combining random forest and logistic regression modelling. Performance to predict poor outcome in acute cough patients was compared with that of existing prediction rules, using the models' area under the receiver operator characteristic curve (AUC), and any improvement obtained by including additional test results (C-reactive protein [CRP], blood urea nitrogen [BUN], chest radiography, or aetiology) was evaluated using the same methodology.
Results: The new prediction rule, included the baseline Risk of poor outcome, Interference with daily activities, number of years stopped Smoking (> or <4 5 years), severity of Sputum, presence of Crackles, and diastolic blood pressure (> or <8 5 mmHg) (RISSC85). Though performance of RISSC85 was moderate (sensitivity 62%, specificity 59%, positive predictive value 27%, negative predictive value 86%, AUC 0.63, 95% confidence interval [CI] = 0.61 to 0.67), it outperformed all existing prediction rules used today (highest AUC 0.53, 95% CI = 0.51 to 0.56), and could not be significantly improved by including additional test results (highest AUC 0.64, 95% CI = 0.62 to 0.68).
Conclusion: The new prediction rule outperforms all existing alternatives in predicting poor outcome in adult patients presenting to primary care with acute cough and could not be improved by including additional test results.
Acute cough, Clinical prediction rule, Primary care, Prognosis
e342-e350
Bruyndonckx, Robin
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Hens, Niel
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Verheij, Theo J.M.
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Aerts, Marc
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Ieven, Margareta
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Butler, Christopher C.
c8cc70b1-5fb9-4b03-bb80-11c6aabb7e6f
Little, Paul
1bf2d1f7-200c-47a5-ab16-fe5a8756a777
Goossens, Herman
31f8e1ae-7da0-473c-bd49-f911c2187451
Coenen, Samuel
3d0dc4e0-e5ba-4d66-ba92-15900ccc551e
1 May 2018
Bruyndonckx, Robin
f4de37c8-5255-4d22-936b-62a7c900c81a
Hens, Niel
e3027832-a075-49d4-a5e0-d9405e20ee11
Verheij, Theo J.M.
0164f6e4-2c95-4233-8c2e-29b616c8ff66
Aerts, Marc
2fe1344f-69b0-442d-b4ab-cc5811775e3a
Ieven, Margareta
c138048d-d838-4c8e-848d-a43e309f4cf0
Butler, Christopher C.
c8cc70b1-5fb9-4b03-bb80-11c6aabb7e6f
Little, Paul
1bf2d1f7-200c-47a5-ab16-fe5a8756a777
Goossens, Herman
31f8e1ae-7da0-473c-bd49-f911c2187451
Coenen, Samuel
3d0dc4e0-e5ba-4d66-ba92-15900ccc551e
Bruyndonckx, Robin, Hens, Niel, Verheij, Theo J.M., Aerts, Marc, Ieven, Margareta, Butler, Christopher C., Little, Paul, Goossens, Herman and Coenen, Samuel
(2018)
Development of a prediction tool for patients presenting with acute cough in primary care: A prognostic study spanning six European countries.
British Journal of General Practice, 68 (670), .
(doi:10.3399/bjgp18X695789).
Abstract
Background: Accurate prediction of the course of an acute cough episode could curb antibiotic overprescribing, but is still a major challenge in primary care.
Aim: The authors set out to develop a new prediction rule for poor outcome (re-consultation with new or worsened symptoms, or hospital admission) in adults presenting to primary care with acute cough.
Design and setting: Data were collected from 2604 adults presenting to primary care with acute cough or symptoms suggestive of lower respiratory tract infection (LRTI) within the Genomics to combat Resistance against Antibiotics in Community-acquired LRTI in Europe (GRACE; www.grace-lrti.org) Network of Excellence.
Method: Important signs and symptoms for the new prediction rule were found by combining random forest and logistic regression modelling. Performance to predict poor outcome in acute cough patients was compared with that of existing prediction rules, using the models' area under the receiver operator characteristic curve (AUC), and any improvement obtained by including additional test results (C-reactive protein [CRP], blood urea nitrogen [BUN], chest radiography, or aetiology) was evaluated using the same methodology.
Results: The new prediction rule, included the baseline Risk of poor outcome, Interference with daily activities, number of years stopped Smoking (> or <4 5 years), severity of Sputum, presence of Crackles, and diastolic blood pressure (> or <8 5 mmHg) (RISSC85). Though performance of RISSC85 was moderate (sensitivity 62%, specificity 59%, positive predictive value 27%, negative predictive value 86%, AUC 0.63, 95% confidence interval [CI] = 0.61 to 0.67), it outperformed all existing prediction rules used today (highest AUC 0.53, 95% CI = 0.51 to 0.56), and could not be significantly improved by including additional test results (highest AUC 0.64, 95% CI = 0.62 to 0.68).
Conclusion: The new prediction rule outperforms all existing alternatives in predicting poor outcome in adult patients presenting to primary care with acute cough and could not be improved by including additional test results.
Text
Prognosis paper GRACE_22-12-17
- Accepted Manuscript
More information
Accepted/In Press date: 2 January 2018
e-pub ahead of print date: 26 April 2018
Published date: 1 May 2018
Keywords:
Acute cough, Clinical prediction rule, Primary care, Prognosis
Identifiers
Local EPrints ID: 421154
URI: http://eprints.soton.ac.uk/id/eprint/421154
ISSN: 0960-1643
PURE UUID: 04e0678c-cb39-49a2-91bc-6b7aad91d7af
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Date deposited: 23 May 2018 16:30
Last modified: 12 Jul 2024 04:03
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Contributors
Author:
Robin Bruyndonckx
Author:
Niel Hens
Author:
Theo J.M. Verheij
Author:
Marc Aerts
Author:
Margareta Ieven
Author:
Christopher C. Butler
Author:
Herman Goossens
Author:
Samuel Coenen
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