The University of Southampton
University of Southampton Institutional Repository

PICADAR: a diagnostic predictive tool for primary ciliary dyskinesia

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.
0903-1936
1103-1112
Behan, Laura
cf1a7b5e-64c5-4b02-8db2-7ad96781d40d
Dimitrov, Borislav D.
366d715f-ffd9-45a1-8415-65de5488472f
Kuehni, Claudia E.
ac67c925-ee32-429d-a3b5-c244daa314b4
Hogg, Claire
78881fd2-dbe9-4c28-b050-3387c163df1e
Carroll, Mary
b836d262-6b07-4006-9c81-26653a26588b
Evans, Hazel J.
b852cf27-9c11-403b-8e70-c54967c5c089
Goutaki, Myrofora
60fbeefc-dbb1-429c-b81a-3c35d368db64
Harris, Amanda
7a93d66b-2959-40ea-b32d-dce642947951
Packham, Samantha
8512c637-42ab-40c6-883a-b66991573270
Walker, Woolf T.
58aae223-5b0e-4f34-9ee7-58bb68278c3a
Lucas, Jane S.
5cb3546c-87b2-4e59-af48-402076e25313
Behan, Laura
cf1a7b5e-64c5-4b02-8db2-7ad96781d40d
Dimitrov, Borislav D.
366d715f-ffd9-45a1-8415-65de5488472f
Kuehni, Claudia E.
ac67c925-ee32-429d-a3b5-c244daa314b4
Hogg, Claire
78881fd2-dbe9-4c28-b050-3387c163df1e
Carroll, Mary
b836d262-6b07-4006-9c81-26653a26588b
Evans, Hazel J.
b852cf27-9c11-403b-8e70-c54967c5c089
Goutaki, Myrofora
60fbeefc-dbb1-429c-b81a-3c35d368db64
Harris, Amanda
7a93d66b-2959-40ea-b32d-dce642947951
Packham, Samantha
8512c637-42ab-40c6-883a-b66991573270
Walker, Woolf T.
58aae223-5b0e-4f34-9ee7-58bb68278c3a
Lucas, Jane S.
5cb3546c-87b2-4e59-af48-402076e25313

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, 1103-1112. (doi:10.1183/13993003.01551-2015). (PMID:26917608)

Record type: Article

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
__filestore.soton.ac.uk_users_jlucas1_mydocuments_Documents_Publications in preparation_respiratory writeups_PCD predictive tool-PICADAR_Behan PICADAR.pdf - Version of Record
Download (391kB)

More information

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: https://eprints.soton.ac.uk/id/eprint/388805
ISSN: 0903-1936
PURE UUID: 028f0a40-0549-4c7c-a86d-fa77c6d572e6

Catalogue record

Date deposited: 03 Mar 2016 13:39
Last modified: 02 Dec 2019 20:22

Export record

Altmetrics

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
Author: Jane S. Lucas

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of https://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×