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2636. Distinguishing Pertussis from Viral Mimickers: Development and Validation of a Clinical Prediction Score

BACKGROUND: Pertussis is often confused with respiratory viral infections, leading to misdiagnosis and overuse of antibiotics. Distinguishing the two entities more accurately can help optimize care. METHODS: We reviewed the charts of children under 18 years of age who presented to Sultan Qaboos Univ...

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Autores principales: Al-Barwani, Lamya, Al-Busaidi, Muna, Alhinai, Zaid, Al-Shibli, Naema
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6811138/
http://dx.doi.org/10.1093/ofid/ofz360.2314
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author Al-Barwani, Lamya
Al-Busaidi, Muna
Alhinai, Zaid
Al-Shibli, Naema
author_facet Al-Barwani, Lamya
Al-Busaidi, Muna
Alhinai, Zaid
Al-Shibli, Naema
author_sort Al-Barwani, Lamya
collection PubMed
description BACKGROUND: Pertussis is often confused with respiratory viral infections, leading to misdiagnosis and overuse of antibiotics. Distinguishing the two entities more accurately can help optimize care. METHODS: We reviewed the charts of children under 18 years of age who presented to Sultan Qaboos University Hospital in Muscat, Oman and were tested for Bordetella pertussis by PCR between 2013 and 2018 (discovery cohort). Clinical and laboratory data were collected from the electronic patient record and analyzed. Backward conditional logistic regression was used to identify independent predictors of laboratory-confirmed pertussis cases. The Muscat Pertussis Index (MPI) score was developed based on the logistic regression model. The MPI score was retrospectively validated on a separate cohort of pediatric patients who presented to the Royal Hospital- Oman’s largest pediatric center- between 2017 and 2018, and were similarly tested for pertussis (validation cohort). Ethical approval of the study was obtained formally for both sites. RESULTS: 354 patients were enrolled in the discovery cohort. 196 (55%) were male, and the median age was 10 weeks (IQR, 6–16). 57 (16%) patients tested positive for B. pertussis by PCR, while 266 (75%) tested positive for respiratory viruses. 32 (9%) patients had both pertussis and a viral co-infection and 63 (18%) were negative for both. 255 (72%) patients received macrolide antibiotics. Younger age, fewer vaccine doses, contact with a sick adult, longer symptom duration, paroxysmal cough, cyanosis, post-tussive emesis, apnea, lymphocytosis and thrombocytosis were significantly associated with pertussis (Table 1). After logistic regression, independent predictors of pertussis were longer symptom duration, lymphocytosis, paroxysmal cough, lack of fever, cyanosis and age under 8 weeks. This formed the basis for creating the MPI score (Table 2). The MPI score was validated on a cohort of 122 patients. Higher MPI scores correlated significantly with confirmed pertussis cases (area under the receiver operating characteristics curve = 0.899, P < 0.001, Figure 1 and Table 3). CONCLUSION: The majority of suspected pertussis cases were actually due to viral mimickers. The MPI score can predict likely cases of pertussis before laboratory confirmation. Future validation in more diverse settings would help expand its applicability. [Image: see text] [Image: see text] [Image: see text] [Image: see text] DISCLOSURES: All authors: No reported disclosures.
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spelling pubmed-68111382019-10-29 2636. Distinguishing Pertussis from Viral Mimickers: Development and Validation of a Clinical Prediction Score Al-Barwani, Lamya Al-Busaidi, Muna Alhinai, Zaid Al-Shibli, Naema Open Forum Infect Dis Abstracts BACKGROUND: Pertussis is often confused with respiratory viral infections, leading to misdiagnosis and overuse of antibiotics. Distinguishing the two entities more accurately can help optimize care. METHODS: We reviewed the charts of children under 18 years of age who presented to Sultan Qaboos University Hospital in Muscat, Oman and were tested for Bordetella pertussis by PCR between 2013 and 2018 (discovery cohort). Clinical and laboratory data were collected from the electronic patient record and analyzed. Backward conditional logistic regression was used to identify independent predictors of laboratory-confirmed pertussis cases. The Muscat Pertussis Index (MPI) score was developed based on the logistic regression model. The MPI score was retrospectively validated on a separate cohort of pediatric patients who presented to the Royal Hospital- Oman’s largest pediatric center- between 2017 and 2018, and were similarly tested for pertussis (validation cohort). Ethical approval of the study was obtained formally for both sites. RESULTS: 354 patients were enrolled in the discovery cohort. 196 (55%) were male, and the median age was 10 weeks (IQR, 6–16). 57 (16%) patients tested positive for B. pertussis by PCR, while 266 (75%) tested positive for respiratory viruses. 32 (9%) patients had both pertussis and a viral co-infection and 63 (18%) were negative for both. 255 (72%) patients received macrolide antibiotics. Younger age, fewer vaccine doses, contact with a sick adult, longer symptom duration, paroxysmal cough, cyanosis, post-tussive emesis, apnea, lymphocytosis and thrombocytosis were significantly associated with pertussis (Table 1). After logistic regression, independent predictors of pertussis were longer symptom duration, lymphocytosis, paroxysmal cough, lack of fever, cyanosis and age under 8 weeks. This formed the basis for creating the MPI score (Table 2). The MPI score was validated on a cohort of 122 patients. Higher MPI scores correlated significantly with confirmed pertussis cases (area under the receiver operating characteristics curve = 0.899, P < 0.001, Figure 1 and Table 3). CONCLUSION: The majority of suspected pertussis cases were actually due to viral mimickers. The MPI score can predict likely cases of pertussis before laboratory confirmation. Future validation in more diverse settings would help expand its applicability. [Image: see text] [Image: see text] [Image: see text] [Image: see text] DISCLOSURES: All authors: No reported disclosures. Oxford University Press 2019-10-23 /pmc/articles/PMC6811138/ http://dx.doi.org/10.1093/ofid/ofz360.2314 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of Infectious Diseases Society of America. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Abstracts
Al-Barwani, Lamya
Al-Busaidi, Muna
Alhinai, Zaid
Al-Shibli, Naema
2636. Distinguishing Pertussis from Viral Mimickers: Development and Validation of a Clinical Prediction Score
title 2636. Distinguishing Pertussis from Viral Mimickers: Development and Validation of a Clinical Prediction Score
title_full 2636. Distinguishing Pertussis from Viral Mimickers: Development and Validation of a Clinical Prediction Score
title_fullStr 2636. Distinguishing Pertussis from Viral Mimickers: Development and Validation of a Clinical Prediction Score
title_full_unstemmed 2636. Distinguishing Pertussis from Viral Mimickers: Development and Validation of a Clinical Prediction Score
title_short 2636. Distinguishing Pertussis from Viral Mimickers: Development and Validation of a Clinical Prediction Score
title_sort 2636. distinguishing pertussis from viral mimickers: development and validation of a clinical prediction score
topic Abstracts
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6811138/
http://dx.doi.org/10.1093/ofid/ofz360.2314
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