2026-10-12T11:26:37Z https://api.figshare.com/v2/oai

oai:figshare.com:article/34072000 2026-10-05T17:31:35Z category_7 category_64 category_132 category_134 category_135 portal_5 item_type_3 month_year_10_2026

pone.0359954.t002 - <p> </p> Nandakumar Ravichandran (21300281) Etimbuk Umana (12680938) Tomas Breslin (11667586) Aoife Cotter (3180996) Walter Cullen (3480263) Medicine Cancer Infectious Diseases Virology Computational Biology threatening condition associated suspected severe infection multivariable logistic regression include demographic characteristics identify factors associated hour sampling periods xlink "> sepsis irish emergency department existing national datasets early sepsis recognition acquired acute infection sectional observational study ed clinical documentation clinical documentation sepsis cases possible sepsis emergency departments administrative datasets clinical presentation substantial morbidity retrospective cross resource planning referral pathways patients presenting patient outcomes mortality worldwide manual review including patients improved understanding hospital mortality ed presentations detailed evaluation data collected adverse outcomes <div><p>Sepsis is a life-threatening condition associated with substantial morbidity and mortality worldwide. In Ireland, the majority of sepsis cases are community-acquired; however, patients presenting to emergency departments (EDs) with suspected severe infection remain poorly characterised, particularly those not captured in administrative datasets. This retrospective cross-sectional observational study will be conducted in the ED of Mater Misericordiae University Hospital, Dublin. Adult (non-maternity) ED presentations across eight predefined 24-hour sampling periods will be reviewed. Community-acquired acute infection will be identified through manual review of ED clinical documentation, and possible sepsis will be identified using the ED triage sepsis discriminator supported by clinical documentation. Data collected will include demographic characteristics, referral pathways, clinical presentation, and patient outcomes. Multivariable logistic regression will be used to identify factors associated with adverse outcomes, defined as intensive care unit admission or in-hospital mortality. This study will provide a detailed evaluation of ED presentations with suspected severe infection in Ireland, including patients not captured in existing national datasets. Findings will contribute to improved understanding of early sepsis recognition, referral pathways, and resource planning in emergency care.</p></div> 2026-10-05T17:31:34Z Dataset Dataset 10.1371/journal.pone.0359954.t002 https://figshare.com/articles/dataset/pone_0359954_t002_-_p_p_/34072000 CC BY 4.0