PICADAR: a diagnostic predictive tool for primary ciliary dyskinesia
PICADAR: a diagnostic predictive tool for primary ciliary dyskinesia
Symptoms of primary ciliary dyskinesia (PCD) are nonspecific and guidance on whom to refer for testing is limited. Diagnostic tests for PCD are highly specialised, requiring expensive equipment and experienced PCD scientists. This study aims to develop a practical clinical diagnostic tool to identify patients requiring testing.Patients consecutively referred for testing were studied. Information readily obtained from patient history was correlated with diagnostic outcome. Using logistic regression, the predictive performance of the best model was tested by receiver operating characteristic curve analyses. The model was simplified into a practical tool (PICADAR) and externally validated in a second diagnostic centre.Of 641 referrals with a definitive diagnostic outcome, 75 (12%) were positive. PICADAR applies to patients with persistent wet cough and has seven predictive parameters: full-term gestation, neonatal chest symptoms, neonatal intensive care admittance, chronic rhinitis, ear symptoms, situs inversus and congenital cardiac defect. Sensitivity and specificity of the tool were 0.90 and 0.75 for a cut-off score of 5 points. Area under the curve for the internally and externally validated tool was 0.91 and 0.87, respectively.PICADAR represents a simple diagnostic clinical prediction rule with good accuracy and validity, ready for testing in respiratory centres referring to PCD centres.
1103-1112
Behan, Laura
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Dimitrov, Borislav D.
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Kuehni, Claudia E.
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Hogg, Claire
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Carroll, Mary
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Evans, Hazel J.
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Goutaki, Myrofora
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Harris, Amanda
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Packham, Samantha
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Walker, Woolf T.
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Lucas, Jane S.
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25 February 2016
Behan, Laura
cf1a7b5e-64c5-4b02-8db2-7ad96781d40d
Dimitrov, Borislav D.
366d715f-ffd9-45a1-8415-65de5488472f
Kuehni, Claudia E.
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Hogg, Claire
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Carroll, Mary
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Evans, Hazel J.
b852cf27-9c11-403b-8e70-c54967c5c089
Goutaki, Myrofora
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Harris, Amanda
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Packham, Samantha
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Walker, Woolf T.
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Lucas, Jane S.
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Behan, Laura, Dimitrov, Borislav D., Kuehni, Claudia E., Hogg, Claire, Carroll, Mary, Evans, Hazel J., Goutaki, Myrofora, Harris, Amanda, Packham, Samantha, Walker, Woolf T. and Lucas, Jane S.
(2016)
PICADAR: a diagnostic predictive tool for primary ciliary dyskinesia.
European Respiratory Journal, 47, .
(doi:10.1183/13993003.01551-2015).
(PMID:26917608)
Abstract
Symptoms of primary ciliary dyskinesia (PCD) are nonspecific and guidance on whom to refer for testing is limited. Diagnostic tests for PCD are highly specialised, requiring expensive equipment and experienced PCD scientists. This study aims to develop a practical clinical diagnostic tool to identify patients requiring testing.Patients consecutively referred for testing were studied. Information readily obtained from patient history was correlated with diagnostic outcome. Using logistic regression, the predictive performance of the best model was tested by receiver operating characteristic curve analyses. The model was simplified into a practical tool (PICADAR) and externally validated in a second diagnostic centre.Of 641 referrals with a definitive diagnostic outcome, 75 (12%) were positive. PICADAR applies to patients with persistent wet cough and has seven predictive parameters: full-term gestation, neonatal chest symptoms, neonatal intensive care admittance, chronic rhinitis, ear symptoms, situs inversus and congenital cardiac defect. Sensitivity and specificity of the tool were 0.90 and 0.75 for a cut-off score of 5 points. Area under the curve for the internally and externally validated tool was 0.91 and 0.87, respectively.PICADAR represents a simple diagnostic clinical prediction rule with good accuracy and validity, ready for testing in respiratory centres referring to PCD centres.
Text
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Accepted/In Press date: 8 January 2016
e-pub ahead of print date: 25 February 2016
Published date: 25 February 2016
Organisations:
Clinical & Experimental Sciences
Identifiers
Local EPrints ID: 388805
URI: http://eprints.soton.ac.uk/id/eprint/388805
ISSN: 0903-1936
PURE UUID: 028f0a40-0549-4c7c-a86d-fa77c6d572e6
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Date deposited: 03 Mar 2016 13:39
Last modified: 15 Mar 2024 03:12
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Contributors
Author:
Laura Behan
Author:
Borislav D. Dimitrov
Author:
Claudia E. Kuehni
Author:
Claire Hogg
Author:
Mary Carroll
Author:
Hazel J. Evans
Author:
Myrofora Goutaki
Author:
Amanda Harris
Author:
Samantha Packham
Author:
Woolf T. Walker
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