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Prediction of Clinical Factors Associated with Pandemic Influenza A (H1N1) 2009 in Pakistan

BACKGROUND: Influenza is a viral infection that can lead to serious complications and death(s) in vulnerable groups if not diagnosed and managed in a timely manner. This study was conducted to improve the accuracy of predicting influenza through various clinical and statistical models. METHODOLOGY:...

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Autores principales: Nisar, Nadia, Aamir, Uzma Bashir, Badar, Nazish, Mehmood, Muhammad Rashid, Alam, Muhammad Masroor, Kazi, Birjees Mazher, Zaidi, Syed Sohail Zahoor
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3933350/
https://www.ncbi.nlm.nih.gov/pubmed/24586575
http://dx.doi.org/10.1371/journal.pone.0089178
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author Nisar, Nadia
Aamir, Uzma Bashir
Badar, Nazish
Mehmood, Muhammad Rashid
Alam, Muhammad Masroor
Kazi, Birjees Mazher
Zaidi, Syed Sohail Zahoor
author_facet Nisar, Nadia
Aamir, Uzma Bashir
Badar, Nazish
Mehmood, Muhammad Rashid
Alam, Muhammad Masroor
Kazi, Birjees Mazher
Zaidi, Syed Sohail Zahoor
author_sort Nisar, Nadia
collection PubMed
description BACKGROUND: Influenza is a viral infection that can lead to serious complications and death(s) in vulnerable groups if not diagnosed and managed in a timely manner. This study was conducted to improve the accuracy of predicting influenza through various clinical and statistical models. METHODOLOGY: A retrospective cross sectional analysis was done on demographic and epidemiological data collected from March 2009 to March 2010. Patients were classified as ILI or SARI using WHO case definitions. Respiratory specimens were tested by RT-PCR. Clinical symptoms and co-morbid conditions were analyzed using binary logistic regression models. RESULTS: In the first approach, analysis compared children (≤12) and adults (>12). Of 1,243 cases, 262 (21%) tested positive for A(H1N1)pdm09 and the proportion of children (≤12) and adults (>12) were 27% and 73% respectively. Four symptoms predicted influenza in children: fever (OR 2.849, 95% CI 1.931–8.722), cough (OR 1.99, 95% CI 1.512–3.643), diarrhea (OR 2.100, 95% CI 2.040–3.25) and respiratory disease (OR 3.269, 95% CI 2.128–12.624). In adults, the strongest clinical predictor was fever (OR 2.80, 95% CI 1.025–3.135) followed by cough (OR 1.431, 95% CI 1.032–2.815). In the second instance, patients were separated into two groups: SARI 326 (26%) and ILI 917 (74%) cases. Male to female ratio was 1.41∶1.12 for SARI and 2∶1.5 for ILI cases. Chi-square test showed that fever, cough and sore throat were significant factors for A(H1N1)pdm09 infections (p = 0.008). CONCLUSION: Studies in a primary care setting should be encouraged focused on patients with influenza-like illness to develop sensitive clinical case definition that will help to improve accuracy of detecting influenza infections. Formulation of a standard “one size fits all” case definition that best correlates with influenza infections can help guide decisions for additional diagnostic testing and also discourage unjustified antibiotic prescription and usage in clinical practice.
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spelling pubmed-39333502014-02-25 Prediction of Clinical Factors Associated with Pandemic Influenza A (H1N1) 2009 in Pakistan Nisar, Nadia Aamir, Uzma Bashir Badar, Nazish Mehmood, Muhammad Rashid Alam, Muhammad Masroor Kazi, Birjees Mazher Zaidi, Syed Sohail Zahoor PLoS One Research Article BACKGROUND: Influenza is a viral infection that can lead to serious complications and death(s) in vulnerable groups if not diagnosed and managed in a timely manner. This study was conducted to improve the accuracy of predicting influenza through various clinical and statistical models. METHODOLOGY: A retrospective cross sectional analysis was done on demographic and epidemiological data collected from March 2009 to March 2010. Patients were classified as ILI or SARI using WHO case definitions. Respiratory specimens were tested by RT-PCR. Clinical symptoms and co-morbid conditions were analyzed using binary logistic regression models. RESULTS: In the first approach, analysis compared children (≤12) and adults (>12). Of 1,243 cases, 262 (21%) tested positive for A(H1N1)pdm09 and the proportion of children (≤12) and adults (>12) were 27% and 73% respectively. Four symptoms predicted influenza in children: fever (OR 2.849, 95% CI 1.931–8.722), cough (OR 1.99, 95% CI 1.512–3.643), diarrhea (OR 2.100, 95% CI 2.040–3.25) and respiratory disease (OR 3.269, 95% CI 2.128–12.624). In adults, the strongest clinical predictor was fever (OR 2.80, 95% CI 1.025–3.135) followed by cough (OR 1.431, 95% CI 1.032–2.815). In the second instance, patients were separated into two groups: SARI 326 (26%) and ILI 917 (74%) cases. Male to female ratio was 1.41∶1.12 for SARI and 2∶1.5 for ILI cases. Chi-square test showed that fever, cough and sore throat were significant factors for A(H1N1)pdm09 infections (p = 0.008). CONCLUSION: Studies in a primary care setting should be encouraged focused on patients with influenza-like illness to develop sensitive clinical case definition that will help to improve accuracy of detecting influenza infections. Formulation of a standard “one size fits all” case definition that best correlates with influenza infections can help guide decisions for additional diagnostic testing and also discourage unjustified antibiotic prescription and usage in clinical practice. Public Library of Science 2014-02-24 /pmc/articles/PMC3933350/ /pubmed/24586575 http://dx.doi.org/10.1371/journal.pone.0089178 Text en © 2014 Nisar et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Nisar, Nadia
Aamir, Uzma Bashir
Badar, Nazish
Mehmood, Muhammad Rashid
Alam, Muhammad Masroor
Kazi, Birjees Mazher
Zaidi, Syed Sohail Zahoor
Prediction of Clinical Factors Associated with Pandemic Influenza A (H1N1) 2009 in Pakistan
title Prediction of Clinical Factors Associated with Pandemic Influenza A (H1N1) 2009 in Pakistan
title_full Prediction of Clinical Factors Associated with Pandemic Influenza A (H1N1) 2009 in Pakistan
title_fullStr Prediction of Clinical Factors Associated with Pandemic Influenza A (H1N1) 2009 in Pakistan
title_full_unstemmed Prediction of Clinical Factors Associated with Pandemic Influenza A (H1N1) 2009 in Pakistan
title_short Prediction of Clinical Factors Associated with Pandemic Influenza A (H1N1) 2009 in Pakistan
title_sort prediction of clinical factors associated with pandemic influenza a (h1n1) 2009 in pakistan
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3933350/
https://www.ncbi.nlm.nih.gov/pubmed/24586575
http://dx.doi.org/10.1371/journal.pone.0089178
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