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Development of a primary care screening algorithm for the early detection of patients at risk of primary antibody deficiency

BACKGROUND: Primary antibody deficiencies (PAD) are characterized by a heterogeneous clinical presentation and low prevalence, contributing to a median diagnostic delay of 3–10 years. This increases the risk of morbidity and mortality from undiagnosed PAD, which may be prevented with adequate therap...

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Autores principales: Messelink, Marianne A., Berbers, Roos M., van Montfrans, Joris M., Ellerbroek, Pauline M., Gladiator, André, Welsing, Paco M. J., Leavis, Helen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10224324/
https://www.ncbi.nlm.nih.gov/pubmed/37245042
http://dx.doi.org/10.1186/s13223-023-00790-7
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author Messelink, Marianne A.
Berbers, Roos M.
van Montfrans, Joris M.
Ellerbroek, Pauline M.
Gladiator, André
Welsing, Paco M. J.
Leavis, Helen
author_facet Messelink, Marianne A.
Berbers, Roos M.
van Montfrans, Joris M.
Ellerbroek, Pauline M.
Gladiator, André
Welsing, Paco M. J.
Leavis, Helen
author_sort Messelink, Marianne A.
collection PubMed
description BACKGROUND: Primary antibody deficiencies (PAD) are characterized by a heterogeneous clinical presentation and low prevalence, contributing to a median diagnostic delay of 3–10 years. This increases the risk of morbidity and mortality from undiagnosed PAD, which may be prevented with adequate therapy. To reduce the diagnostic delay of PAD, we developed a screening algorithm using primary care electronic health record (EHR) data to identify patients at risk of PAD. This screening algorithm can be used as an aid to notify general practitioners when further laboratory evaluation of immunoglobulins should be considered, thereby facilitating a timely diagnosis of PAD. METHODS: Candidate components for the algorithm were based on a broad range of presenting signs and symptoms of PAD that are available in primary care EHRs. The decision on inclusion and weight of the components in the algorithm was based on the prevalence of these components among PAD patients and control groups, as well as clinical rationale. RESULTS: We analyzed the primary care EHRs of 30 PAD patients, 26 primary care immunodeficiency patients and 58,223 control patients. The median diagnostic delay of PAD patients was 9.5 years. Several candidate components showed a clear difference in prevalence between PAD patients and controls, most notably the mean number of antibiotic prescriptions in the 4 years prior to diagnosis (5.14 vs. 0.48). The final algorithm included antibiotic prescriptions, diagnostic codes for respiratory tract and other infections, gastro-intestinal complaints, auto-immune symptoms, malignancies and lymphoproliferative symptoms, as well as laboratory values and visits to the general practitioner. CONCLUSIONS: In this study, we developed a screening algorithm based on a broad range of presenting signs and symptoms of PAD, which is suitable to implement in primary care. It has the potential to considerably reduce diagnostic delay in PAD, and will be validated in a prospective study. Trial registration The consecutive prospective study is registered at clinicaltrials.gov under NCT05310604 SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13223-023-00790-7.
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spelling pubmed-102243242023-05-28 Development of a primary care screening algorithm for the early detection of patients at risk of primary antibody deficiency Messelink, Marianne A. Berbers, Roos M. van Montfrans, Joris M. Ellerbroek, Pauline M. Gladiator, André Welsing, Paco M. J. Leavis, Helen Allergy Asthma Clin Immunol Research BACKGROUND: Primary antibody deficiencies (PAD) are characterized by a heterogeneous clinical presentation and low prevalence, contributing to a median diagnostic delay of 3–10 years. This increases the risk of morbidity and mortality from undiagnosed PAD, which may be prevented with adequate therapy. To reduce the diagnostic delay of PAD, we developed a screening algorithm using primary care electronic health record (EHR) data to identify patients at risk of PAD. This screening algorithm can be used as an aid to notify general practitioners when further laboratory evaluation of immunoglobulins should be considered, thereby facilitating a timely diagnosis of PAD. METHODS: Candidate components for the algorithm were based on a broad range of presenting signs and symptoms of PAD that are available in primary care EHRs. The decision on inclusion and weight of the components in the algorithm was based on the prevalence of these components among PAD patients and control groups, as well as clinical rationale. RESULTS: We analyzed the primary care EHRs of 30 PAD patients, 26 primary care immunodeficiency patients and 58,223 control patients. The median diagnostic delay of PAD patients was 9.5 years. Several candidate components showed a clear difference in prevalence between PAD patients and controls, most notably the mean number of antibiotic prescriptions in the 4 years prior to diagnosis (5.14 vs. 0.48). The final algorithm included antibiotic prescriptions, diagnostic codes for respiratory tract and other infections, gastro-intestinal complaints, auto-immune symptoms, malignancies and lymphoproliferative symptoms, as well as laboratory values and visits to the general practitioner. CONCLUSIONS: In this study, we developed a screening algorithm based on a broad range of presenting signs and symptoms of PAD, which is suitable to implement in primary care. It has the potential to considerably reduce diagnostic delay in PAD, and will be validated in a prospective study. Trial registration The consecutive prospective study is registered at clinicaltrials.gov under NCT05310604 SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13223-023-00790-7. BioMed Central 2023-05-27 /pmc/articles/PMC10224324/ /pubmed/37245042 http://dx.doi.org/10.1186/s13223-023-00790-7 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Messelink, Marianne A.
Berbers, Roos M.
van Montfrans, Joris M.
Ellerbroek, Pauline M.
Gladiator, André
Welsing, Paco M. J.
Leavis, Helen
Development of a primary care screening algorithm for the early detection of patients at risk of primary antibody deficiency
title Development of a primary care screening algorithm for the early detection of patients at risk of primary antibody deficiency
title_full Development of a primary care screening algorithm for the early detection of patients at risk of primary antibody deficiency
title_fullStr Development of a primary care screening algorithm for the early detection of patients at risk of primary antibody deficiency
title_full_unstemmed Development of a primary care screening algorithm for the early detection of patients at risk of primary antibody deficiency
title_short Development of a primary care screening algorithm for the early detection of patients at risk of primary antibody deficiency
title_sort development of a primary care screening algorithm for the early detection of patients at risk of primary antibody deficiency
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10224324/
https://www.ncbi.nlm.nih.gov/pubmed/37245042
http://dx.doi.org/10.1186/s13223-023-00790-7
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