Cargando…
Early identification of pneumonia patients at increased risk of Middle East respiratory syndrome coronavirus infection in Saudi Arabia
BACKGROUND: The rapid and accurate identification of individuals who are at high risk of Middle East respiratory syndrome coronavirus (MERS-CoV) infection remains a major challenge for the medical and scientific communities. The aim of this study was to develop and validate a risk prediction model f...
Autores principales: | , , , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Author(s). Published by Elsevier Ltd on behalf of International Society for Infectious Diseases.
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7110544/ https://www.ncbi.nlm.nih.gov/pubmed/29550445 http://dx.doi.org/10.1016/j.ijid.2018.03.005 |
_version_ | 1783513067820154880 |
---|---|
author | Ahmed, Anwar E. Al-Jahdali, Hamdan Alshukairi, Abeer N. Alaqeel, Mody Siddiq, Salma S. Alsaab, Hanan Sakr, Ezzeldin A. Alyahya, Hamed A. Alandonisi, Munzir M. Subedar, Alaa T. Aloudah, Nouf M. Baharoon, Salim Alsalamah, Majid A. Al Johani, Sameera Alghamdi, Mohammed G. |
author_facet | Ahmed, Anwar E. Al-Jahdali, Hamdan Alshukairi, Abeer N. Alaqeel, Mody Siddiq, Salma S. Alsaab, Hanan Sakr, Ezzeldin A. Alyahya, Hamed A. Alandonisi, Munzir M. Subedar, Alaa T. Aloudah, Nouf M. Baharoon, Salim Alsalamah, Majid A. Al Johani, Sameera Alghamdi, Mohammed G. |
author_sort | Ahmed, Anwar E. |
collection | PubMed |
description | BACKGROUND: The rapid and accurate identification of individuals who are at high risk of Middle East respiratory syndrome coronavirus (MERS-CoV) infection remains a major challenge for the medical and scientific communities. The aim of this study was to develop and validate a risk prediction model for the screening of suspected cases of MERS-CoV infection in patients who have developed pneumonia. METHODS: A two-center, retrospective case–control study was performed. A total of 360 patients with confirmed pneumonia who were evaluated for MERS-CoV infection by real-time reverse transcription polymerase chain reaction (rRT-PCR) between September 1, 2012 and June 1, 2016 at King Abdulaziz Medical City in Riyadh and King Fahad General Hospital in Jeddah, were included. According to the rRT-PCR results, 135 patients were positive for MERS-CoV and 225 were negative. Demographic characteristics, clinical presentations, and radiological and laboratory findings were collected for each subject. RESULTS: A risk prediction model to identify pneumonia patients at increased risk of MERS-CoV was developed. The model included male sex, contact with a sick patient or camel, diabetes, severe illness, low white blood cell (WBC) count, low alanine aminotransferase (ALT), and high aspartate aminotransferase (AST). The model performed well in predicting MERS-CoV infection (area under the receiver operating characteristics curves (AUC) 0.8162), on internal validation (AUC 0.8037), and on a goodness-of-fit test (p = 0.592). The risk prediction model, which produced an optimal probability cut-off of 0.33, had a sensitivity of 0.716 and specificity of 0.783. CONCLUSIONS: This study provides a simple, practical, and valid algorithm to identify pneumonia patients at increased risk of MERS-CoV infection. This risk prediction model could be useful for the early identification of patients at the highest risk of MERS-CoV infection. Further validation of the prediction model on a large prospective cohort of representative patients with pneumonia is necessary. |
format | Online Article Text |
id | pubmed-7110544 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | The Author(s). Published by Elsevier Ltd on behalf of International Society for Infectious Diseases. |
record_format | MEDLINE/PubMed |
spelling | pubmed-71105442020-04-02 Early identification of pneumonia patients at increased risk of Middle East respiratory syndrome coronavirus infection in Saudi Arabia Ahmed, Anwar E. Al-Jahdali, Hamdan Alshukairi, Abeer N. Alaqeel, Mody Siddiq, Salma S. Alsaab, Hanan Sakr, Ezzeldin A. Alyahya, Hamed A. Alandonisi, Munzir M. Subedar, Alaa T. Aloudah, Nouf M. Baharoon, Salim Alsalamah, Majid A. Al Johani, Sameera Alghamdi, Mohammed G. Int J Infect Dis Article BACKGROUND: The rapid and accurate identification of individuals who are at high risk of Middle East respiratory syndrome coronavirus (MERS-CoV) infection remains a major challenge for the medical and scientific communities. The aim of this study was to develop and validate a risk prediction model for the screening of suspected cases of MERS-CoV infection in patients who have developed pneumonia. METHODS: A two-center, retrospective case–control study was performed. A total of 360 patients with confirmed pneumonia who were evaluated for MERS-CoV infection by real-time reverse transcription polymerase chain reaction (rRT-PCR) between September 1, 2012 and June 1, 2016 at King Abdulaziz Medical City in Riyadh and King Fahad General Hospital in Jeddah, were included. According to the rRT-PCR results, 135 patients were positive for MERS-CoV and 225 were negative. Demographic characteristics, clinical presentations, and radiological and laboratory findings were collected for each subject. RESULTS: A risk prediction model to identify pneumonia patients at increased risk of MERS-CoV was developed. The model included male sex, contact with a sick patient or camel, diabetes, severe illness, low white blood cell (WBC) count, low alanine aminotransferase (ALT), and high aspartate aminotransferase (AST). The model performed well in predicting MERS-CoV infection (area under the receiver operating characteristics curves (AUC) 0.8162), on internal validation (AUC 0.8037), and on a goodness-of-fit test (p = 0.592). The risk prediction model, which produced an optimal probability cut-off of 0.33, had a sensitivity of 0.716 and specificity of 0.783. CONCLUSIONS: This study provides a simple, practical, and valid algorithm to identify pneumonia patients at increased risk of MERS-CoV infection. This risk prediction model could be useful for the early identification of patients at the highest risk of MERS-CoV infection. Further validation of the prediction model on a large prospective cohort of representative patients with pneumonia is necessary. The Author(s). Published by Elsevier Ltd on behalf of International Society for Infectious Diseases. 2018-05 2018-03-14 /pmc/articles/PMC7110544/ /pubmed/29550445 http://dx.doi.org/10.1016/j.ijid.2018.03.005 Text en © 2018 The Author(s) Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Ahmed, Anwar E. Al-Jahdali, Hamdan Alshukairi, Abeer N. Alaqeel, Mody Siddiq, Salma S. Alsaab, Hanan Sakr, Ezzeldin A. Alyahya, Hamed A. Alandonisi, Munzir M. Subedar, Alaa T. Aloudah, Nouf M. Baharoon, Salim Alsalamah, Majid A. Al Johani, Sameera Alghamdi, Mohammed G. Early identification of pneumonia patients at increased risk of Middle East respiratory syndrome coronavirus infection in Saudi Arabia |
title | Early identification of pneumonia patients at increased risk of Middle East respiratory syndrome coronavirus infection in Saudi Arabia |
title_full | Early identification of pneumonia patients at increased risk of Middle East respiratory syndrome coronavirus infection in Saudi Arabia |
title_fullStr | Early identification of pneumonia patients at increased risk of Middle East respiratory syndrome coronavirus infection in Saudi Arabia |
title_full_unstemmed | Early identification of pneumonia patients at increased risk of Middle East respiratory syndrome coronavirus infection in Saudi Arabia |
title_short | Early identification of pneumonia patients at increased risk of Middle East respiratory syndrome coronavirus infection in Saudi Arabia |
title_sort | early identification of pneumonia patients at increased risk of middle east respiratory syndrome coronavirus infection in saudi arabia |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7110544/ https://www.ncbi.nlm.nih.gov/pubmed/29550445 http://dx.doi.org/10.1016/j.ijid.2018.03.005 |
work_keys_str_mv | AT ahmedanware earlyidentificationofpneumoniapatientsatincreasedriskofmiddleeastrespiratorysyndromecoronavirusinfectioninsaudiarabia AT aljahdalihamdan earlyidentificationofpneumoniapatientsatincreasedriskofmiddleeastrespiratorysyndromecoronavirusinfectioninsaudiarabia AT alshukairiabeern earlyidentificationofpneumoniapatientsatincreasedriskofmiddleeastrespiratorysyndromecoronavirusinfectioninsaudiarabia AT alaqeelmody earlyidentificationofpneumoniapatientsatincreasedriskofmiddleeastrespiratorysyndromecoronavirusinfectioninsaudiarabia AT siddiqsalmas earlyidentificationofpneumoniapatientsatincreasedriskofmiddleeastrespiratorysyndromecoronavirusinfectioninsaudiarabia AT alsaabhanan earlyidentificationofpneumoniapatientsatincreasedriskofmiddleeastrespiratorysyndromecoronavirusinfectioninsaudiarabia AT sakrezzeldina earlyidentificationofpneumoniapatientsatincreasedriskofmiddleeastrespiratorysyndromecoronavirusinfectioninsaudiarabia AT alyahyahameda earlyidentificationofpneumoniapatientsatincreasedriskofmiddleeastrespiratorysyndromecoronavirusinfectioninsaudiarabia AT alandonisimunzirm earlyidentificationofpneumoniapatientsatincreasedriskofmiddleeastrespiratorysyndromecoronavirusinfectioninsaudiarabia AT subedaralaat earlyidentificationofpneumoniapatientsatincreasedriskofmiddleeastrespiratorysyndromecoronavirusinfectioninsaudiarabia AT aloudahnoufm earlyidentificationofpneumoniapatientsatincreasedriskofmiddleeastrespiratorysyndromecoronavirusinfectioninsaudiarabia AT baharoonsalim earlyidentificationofpneumoniapatientsatincreasedriskofmiddleeastrespiratorysyndromecoronavirusinfectioninsaudiarabia AT alsalamahmajida earlyidentificationofpneumoniapatientsatincreasedriskofmiddleeastrespiratorysyndromecoronavirusinfectioninsaudiarabia AT aljohanisameera earlyidentificationofpneumoniapatientsatincreasedriskofmiddleeastrespiratorysyndromecoronavirusinfectioninsaudiarabia AT alghamdimohammedg earlyidentificationofpneumoniapatientsatincreasedriskofmiddleeastrespiratorysyndromecoronavirusinfectioninsaudiarabia |