<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Xiong S</submitter><funding>Top Talent Support Program for young and middle-aged people of Wuxi Health Committee</funding><funding>Wuxi Municipal Bureau on Science and Technology</funding><funding>Wuxi Taihu Lake Talent Plan</funding><funding>Natural Science Foundation of Jiangsu Province</funding><pagination>746</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC12492913</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>25(1)</volume><pubmed_abstract>&lt;h4>Background&lt;/h4>Owing to the absence of straightforward and scientifically validated screening and evaluation tools for the timely identification, diagnosis, and treatment of critical influenza A infection in children, this study aimed to construct an effective model for the early identification of patients at high risk of progressing to critical influenza A infection.&lt;h4>Methods&lt;/h4>The prediction model was developed using the registration data of children diagnosed with influenza A who were admitted to Wuxi Children's Hospital, the Children's Hospital Affiliated to Soochow University and the Children's Hospital Affiliated to Fudan University. Patients were randomly divided into a training group and a validation group at a 7:3 ratio. A logistic regression model was established based on</pubmed_abstract><journal>BMC pediatrics</journal><pubmed_title>A simple, rapid, and cost-effective model for predicting critical influenza a infection in children: a multicentre, retrospective cohort study.</pubmed_title><pmcid>PMC12492913</pmcid><funding_grant_id>BK20230189</funding_grant_id><funding_grant_id>K20221033</funding_grant_id><funding_grant_id>DJTD202304</funding_grant_id><funding_grant_id>BJ2023089</funding_grant_id><pubmed_authors>Zhu P</pubmed_authors><pubmed_authors>Qian J</pubmed_authors><pubmed_authors>Jiang L</pubmed_authors><pubmed_authors>Guo Y</pubmed_authors><pubmed_authors>Chen W</pubmed_authors><pubmed_authors>Xiong S</pubmed_authors><pubmed_authors>Bai Z</pubmed_authors><pubmed_authors>Wang Y</pubmed_authors><pubmed_authors>Li L</pubmed_authors></additional><is_claimable>false</is_claimable><name>A simple, rapid, and cost-effective model for predicting critical influenza a infection in children: a multicentre, retrospective cohort study.</name><description>&lt;h4>Background&lt;/h4>Owing to the absence of straightforward and scientifically validated screening and evaluation tools for the timely identification, diagnosis, and treatment of critical influenza A infection in children, this study aimed to construct an effective model for the early identification of patients at high risk of progressing to critical influenza A infection.&lt;h4>Methods&lt;/h4>The prediction model was developed using the registration data of children diagnosed with influenza A who were admitted to Wuxi Children's Hospital, the Children's Hospital Affiliated to Soochow University and the Children's Hospital Affiliated to Fudan University. Patients were randomly divided into a training group and a validation group at a 7:3 ratio. A logistic regression model was established based on</description><dates><release>2025-01-01T00:00:00Z</release><publication>2025 Oct</publication><modification>2026-06-04T02:34:21.388Z</modification><creation>2026-05-31T03:06:29.47Z</creation></dates><accession>S-EPMC12492913</accession><cross_references><pubmed>41039296</pubmed><doi>10.1186/s12887-025-06085-7</doi></cross_references></HashMap>