The University of Southampton
University of Southampton Institutional Repository

Prospectively predicting Pseudomonas aeruginosa infection/s using routine data from the UK cystic fibrosis register

Prospectively predicting Pseudomonas aeruginosa infection/s using routine data from the UK cystic fibrosis register
Prospectively predicting Pseudomonas aeruginosa infection/s using routine data from the UK cystic fibrosis register

RATIONALE AND AIMS: Lung health of people with cystic fibrosis (PwCF) can be preserved by daily use of inhaled therapy. Adherence to inhaled therapy, therefore, provides an important process measure to understand the success of care and can be used as a quality indicator. Defining adherence is problematic, however, since the number of prescribed treatments varies considerably between PwCF. The problem is less pronounced among those with Pseudomonas aeruginosa (PA), for whom at least three daily doses of nebulized therapy should be prescribed and who thus constitute a more homogeneous group. The UK CF Registry provides routine data on PA status, but data are only available 12 months after collection. In this study, we aim to prospectively identify contemporary PA status from historic registry data.

METHOD: UK CF Registry data from 2011 to 2015 for PwCF aged ≥16 was used to determine a pragmatic prediction rule for identifying contemporary PA status using historic registry data. Accuracy of three different prediction rules was assessed using the positive predictive value (PPV). The number and proportion of adults predicted to have PA infection were determined overall and per center for the selected prediction rule. Known characteristics linked to PA status were explored to ensure the robustness of the prediction rule.

RESULTS: Having CF Registry defined chronic PA status in the two previous years is the selected definition to predict a patient will have PA infection within the current year (population-level PPV = 96%-97%, centre level PPV = 85%-100%). This approach provides a subset of data between 1852 and 1872 patients overall and a range of 8 to 279 patients per center.

CONCLUSION: Historic registry data can be used to contemporaneously identify a subgroup of patients with chronic PA. Since this patient group has a narrower treatment schedule, this can facilitate a better benchmarking of adherence across centers.

pseudomonas aeruginosa, cystic Fibrosis, infection
2398-8835
e381
Totton, Nikki
76f8c5b2-5377-4906-89aa-37f16c7bbba0
Bradburn, Mike
c845a405-6815-49e3-a94d-b7489263d0f0
Hoo, Zhe Hui
5eec4611-31e3-4b40-aee5-ac0ca2bb4042
Lewis, Jen
07d5756c-b1d5-4354-b64d-ba22c9313290
Hind, Daniel
d0246cbf-e8b6-45c2-9412-76e0988852f3
Girling, Carla
74871d40-c7d1-4eec-9ac7-5c6eb53f7159
Shepherd, Elizabeth
7919760b-1221-46c5-9792-5cae3b0ca571
Nightingale, Julia
1dedb0e5-7490-4b0d-8159-2bc5087513c1
Daniels, Thomas
d635a2fb-96a1-46ec-8cdf-8eb44a4bd0f5
Dewar, Jane
96800813-c562-485e-a0e3-8e856932e686
Dawson, Sophie
2d36ce04-b715-460d-946a-8934bee0a83d
Carroll, Mary
b836d262-6b07-4006-9c81-26653a26588b
Allenby, Mark
33adb37c-916a-483c-afe8-6647d70b7e2b
Edenborough, Frank
d9abf157-19ee-4bec-b7b7-f6907b3fa9d9
Curley, Rachael
293e9fcd-b886-475a-add9-1dd65d83eceb
Carolan, Charlotte
b43dfeac-9356-454a-823c-345de558b8cf
Wildman, Martin
7b79195c-4254-4fa7-bd79-3738f3dd1747
Totton, Nikki
76f8c5b2-5377-4906-89aa-37f16c7bbba0
Bradburn, Mike
c845a405-6815-49e3-a94d-b7489263d0f0
Hoo, Zhe Hui
5eec4611-31e3-4b40-aee5-ac0ca2bb4042
Lewis, Jen
07d5756c-b1d5-4354-b64d-ba22c9313290
Hind, Daniel
d0246cbf-e8b6-45c2-9412-76e0988852f3
Girling, Carla
74871d40-c7d1-4eec-9ac7-5c6eb53f7159
Shepherd, Elizabeth
7919760b-1221-46c5-9792-5cae3b0ca571
Nightingale, Julia
1dedb0e5-7490-4b0d-8159-2bc5087513c1
Daniels, Thomas
d635a2fb-96a1-46ec-8cdf-8eb44a4bd0f5
Dewar, Jane
96800813-c562-485e-a0e3-8e856932e686
Dawson, Sophie
2d36ce04-b715-460d-946a-8934bee0a83d
Carroll, Mary
b836d262-6b07-4006-9c81-26653a26588b
Allenby, Mark
33adb37c-916a-483c-afe8-6647d70b7e2b
Edenborough, Frank
d9abf157-19ee-4bec-b7b7-f6907b3fa9d9
Curley, Rachael
293e9fcd-b886-475a-add9-1dd65d83eceb
Carolan, Charlotte
b43dfeac-9356-454a-823c-345de558b8cf
Wildman, Martin
7b79195c-4254-4fa7-bd79-3738f3dd1747

Totton, Nikki, Bradburn, Mike, Hoo, Zhe Hui, Lewis, Jen, Hind, Daniel, Girling, Carla, Shepherd, Elizabeth, Nightingale, Julia, Daniels, Thomas, Dewar, Jane, Dawson, Sophie, Carroll, Mary, Allenby, Mark, Edenborough, Frank, Curley, Rachael, Carolan, Charlotte and Wildman, Martin (2021) Prospectively predicting Pseudomonas aeruginosa infection/s using routine data from the UK cystic fibrosis register. Health Science Reports, 4 (4), e381. (doi:10.1002/hsr2.381).

Record type: Article

Abstract

RATIONALE AND AIMS: Lung health of people with cystic fibrosis (PwCF) can be preserved by daily use of inhaled therapy. Adherence to inhaled therapy, therefore, provides an important process measure to understand the success of care and can be used as a quality indicator. Defining adherence is problematic, however, since the number of prescribed treatments varies considerably between PwCF. The problem is less pronounced among those with Pseudomonas aeruginosa (PA), for whom at least three daily doses of nebulized therapy should be prescribed and who thus constitute a more homogeneous group. The UK CF Registry provides routine data on PA status, but data are only available 12 months after collection. In this study, we aim to prospectively identify contemporary PA status from historic registry data.

METHOD: UK CF Registry data from 2011 to 2015 for PwCF aged ≥16 was used to determine a pragmatic prediction rule for identifying contemporary PA status using historic registry data. Accuracy of three different prediction rules was assessed using the positive predictive value (PPV). The number and proportion of adults predicted to have PA infection were determined overall and per center for the selected prediction rule. Known characteristics linked to PA status were explored to ensure the robustness of the prediction rule.

RESULTS: Having CF Registry defined chronic PA status in the two previous years is the selected definition to predict a patient will have PA infection within the current year (population-level PPV = 96%-97%, centre level PPV = 85%-100%). This approach provides a subset of data between 1852 and 1872 patients overall and a range of 8 to 279 patients per center.

CONCLUSION: Historic registry data can be used to contemporaneously identify a subgroup of patients with chronic PA. Since this patient group has a narrower treatment schedule, this can facilitate a better benchmarking of adherence across centers.

This record has no associated files available for download.

More information

Accepted/In Press date: 22 July 2021
e-pub ahead of print date: 1 October 2021
Additional Information: © 2021 The Authors. Health Science Reports published by Wiley Periodicals LLC.
Keywords: pseudomonas aeruginosa, cystic Fibrosis, infection

Identifiers

Local EPrints ID: 484098
URI: http://eprints.soton.ac.uk/id/eprint/484098
ISSN: 2398-8835
PURE UUID: a835a760-762f-4b94-a53f-9c744018eeb2

Catalogue record

Date deposited: 09 Nov 2023 18:20
Last modified: 17 Mar 2024 05:41

Export record

Altmetrics

Contributors

Author: Nikki Totton
Author: Mike Bradburn
Author: Zhe Hui Hoo
Author: Jen Lewis
Author: Daniel Hind
Author: Carla Girling
Author: Elizabeth Shepherd
Author: Julia Nightingale
Author: Thomas Daniels
Author: Jane Dewar
Author: Sophie Dawson
Author: Mary Carroll
Author: Mark Allenby
Author: Frank Edenborough
Author: Rachael Curley
Author: Charlotte Carolan
Author: Martin Wildman

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 http://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.

×