Cargando…

Clinical signs predictive of severe illness in young Pakistani infants

OBJECTIVE: Early detection of specific signs and symptoms to predict severe illness is essential to prevent infant mortality. As a continuation of the results from the multicenter Young Infants Clinical Signs and Symptoms (YICSS) study, we present here the performance of the seven-sign algorithm in...

Descripción completa

Detalles Bibliográficos
Autores principales: Shahid, Shahira, Tikmani, Shiyam Sunder, Nayani, Kanwal, Munir, Ayesha, Brown, Nick, Zaidi, Anita K. M., Jehan, Fyezah, Nisar, Muhammad Imran
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7903754/
https://www.ncbi.nlm.nih.gov/pubmed/33627174
http://dx.doi.org/10.1186/s13104-021-05486-y
_version_ 1783654799180300288
author Shahid, Shahira
Tikmani, Shiyam Sunder
Nayani, Kanwal
Munir, Ayesha
Brown, Nick
Zaidi, Anita K. M.
Jehan, Fyezah
Nisar, Muhammad Imran
author_facet Shahid, Shahira
Tikmani, Shiyam Sunder
Nayani, Kanwal
Munir, Ayesha
Brown, Nick
Zaidi, Anita K. M.
Jehan, Fyezah
Nisar, Muhammad Imran
author_sort Shahid, Shahira
collection PubMed
description OBJECTIVE: Early detection of specific signs and symptoms to predict severe illness is essential to prevent infant mortality. As a continuation of the results from the multicenter Young Infants Clinical Signs and Symptoms (YICSS) study, we present here the performance of the seven-sign algorithm in 3 age categories (0–6 days, 7–27 days and 28–59 days) in Pakistani infants aged 0–59 days. RESULTS: From September 2003 to November 2004, 2950 infants were enrolled (age group 0–6 days = 1633, 7–27 days = 817, 28–59 days = 500). The common reason for seeking care was umbilical redness or discharge (29.2%) in the 0–6 days group. Older age groups presented with cough (16.9%) in the 7–27 age group and (26.9%) infants in the 28–59 days group. Severe infection/sepsis was the most common primary diagnoses in infants requiring hospitalization across all age groups. The algorithm performed well in every age group, with a sensitivity of 85.9% and specificity of 71.6% in the 0–6 days age group and a sensitivity of 80.5% and specificity of 80.2% in the 28–59 days group; the sensitivity was slightly lower in the 7–27 age group (72.4%) but the specificity remained high (83.1%).
format Online
Article
Text
id pubmed-7903754
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-79037542021-03-01 Clinical signs predictive of severe illness in young Pakistani infants Shahid, Shahira Tikmani, Shiyam Sunder Nayani, Kanwal Munir, Ayesha Brown, Nick Zaidi, Anita K. M. Jehan, Fyezah Nisar, Muhammad Imran BMC Res Notes Research Note OBJECTIVE: Early detection of specific signs and symptoms to predict severe illness is essential to prevent infant mortality. As a continuation of the results from the multicenter Young Infants Clinical Signs and Symptoms (YICSS) study, we present here the performance of the seven-sign algorithm in 3 age categories (0–6 days, 7–27 days and 28–59 days) in Pakistani infants aged 0–59 days. RESULTS: From September 2003 to November 2004, 2950 infants were enrolled (age group 0–6 days = 1633, 7–27 days = 817, 28–59 days = 500). The common reason for seeking care was umbilical redness or discharge (29.2%) in the 0–6 days group. Older age groups presented with cough (16.9%) in the 7–27 age group and (26.9%) infants in the 28–59 days group. Severe infection/sepsis was the most common primary diagnoses in infants requiring hospitalization across all age groups. The algorithm performed well in every age group, with a sensitivity of 85.9% and specificity of 71.6% in the 0–6 days age group and a sensitivity of 80.5% and specificity of 80.2% in the 28–59 days group; the sensitivity was slightly lower in the 7–27 age group (72.4%) but the specificity remained high (83.1%). BioMed Central 2021-02-24 /pmc/articles/PMC7903754/ /pubmed/33627174 http://dx.doi.org/10.1186/s13104-021-05486-y Text en © The Author(s) 2021 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/. The Creative Commons Public Domain Dedication waiver (http://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 Note
Shahid, Shahira
Tikmani, Shiyam Sunder
Nayani, Kanwal
Munir, Ayesha
Brown, Nick
Zaidi, Anita K. M.
Jehan, Fyezah
Nisar, Muhammad Imran
Clinical signs predictive of severe illness in young Pakistani infants
title Clinical signs predictive of severe illness in young Pakistani infants
title_full Clinical signs predictive of severe illness in young Pakistani infants
title_fullStr Clinical signs predictive of severe illness in young Pakistani infants
title_full_unstemmed Clinical signs predictive of severe illness in young Pakistani infants
title_short Clinical signs predictive of severe illness in young Pakistani infants
title_sort clinical signs predictive of severe illness in young pakistani infants
topic Research Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7903754/
https://www.ncbi.nlm.nih.gov/pubmed/33627174
http://dx.doi.org/10.1186/s13104-021-05486-y
work_keys_str_mv AT shahidshahira clinicalsignspredictiveofsevereillnessinyoungpakistaniinfants
AT tikmanishiyamsunder clinicalsignspredictiveofsevereillnessinyoungpakistaniinfants
AT nayanikanwal clinicalsignspredictiveofsevereillnessinyoungpakistaniinfants
AT munirayesha clinicalsignspredictiveofsevereillnessinyoungpakistaniinfants
AT brownnick clinicalsignspredictiveofsevereillnessinyoungpakistaniinfants
AT zaidianitakm clinicalsignspredictiveofsevereillnessinyoungpakistaniinfants
AT jehanfyezah clinicalsignspredictiveofsevereillnessinyoungpakistaniinfants
AT nisarmuhammadimran clinicalsignspredictiveofsevereillnessinyoungpakistaniinfants