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...
Autores principales: | , , , , , , , |
---|---|
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 |