Sepsis is a potentially life-threatening condition arising from a dysregulated response to infection. It is characterized by significant morbidity and mortality on a global scale. In Ireland, a striking majority of sepsis cases are classified as community-acquired. Despite this, the profiles of patients presenting to emergency departments (EDs) with suspected severe infections are not well-defined, especially those overlooked in administrative records.
The current retrospective observational study will be implemented at Mater Misericordiae University Hospital, Dublin. It targets adult ED presentations over eight specific 24-hour sampling periods. The study aims to manually identify cases of community-acquired acute infection and evaluate for possible sepsis using established triage tools. Detailed data will include demographic information, referral pathways, clinical manifestations, and patient outcomes.
By employing multivariable logistic regression, the research will examine elements associated with adverse outcomes, including intensive care unit (ICU) admissions and in-hospital mortality. This investigation aims to offer a profound understanding of ED presentations with severe infection in Ireland, especially for individuals not indicated in the current national datasets.
The primary goal of the study is to categorize adults presenting to the emergency department with community-acquired acute infections during predefined sampling periods.
Secondary objectives encompass:
This investigation is characterized by a single-centre retrospective observational methodology focusing on the emergency department of Mater Misericordiae University Hospital, a prominent teaching hospital in Dublin. This urban facility experiences a significant volume of ED presentations, receiving referrals from various sources including primary care and ambulatory services. The study's retrospective design aims to examine all applicable presentations while utilizing an analytical framework to evaluate factors leading to possible sepsis and patient outcomes.
To account for seasonal variations in infection rates, data will encompass eight defined 24-hour sampling periods distributed throughout 2025: January, April, July, and October. This method aims to enhance representativeness while allowing for detailed manual review of clinical data. Since all eligible presentations during the sampling periods will be reviewed, the study serves as a comprehensive cohort analysis rather than a sampled one.
All ED presentations during the predetermined sampling intervals will be assessed. Only patients who meet the defined criteria for community-acquired acute infection will be included in the study. Patients with infections that develop after 48 hours of hospital admission will be excluded. The cases of community-acquired infections will focus on those documented at the time of ED visit.
Data extraction will occur via a standardized case report form. The collection process is expected to commence in mid-May 2026, concluding in December 2026, with results anticipated in February 2027. Two independent reviewers will manage eligibility and data extraction, resolving discrepancies through consensus.
The key outcomes encompass the traits of suspected sepsis presentations and referral pathways for community-acquired infections. Secondary outcomes will include mortality rates at 30 and 90 days, rates of hospital admission, and initiation of sepsis protocols.
Statistical evaluations will leverage tools such as SPSS and Python notebook. Descriptive statistics will summarize patient details and outcomes, while relationships between referral sources and adverse outcomes will be explored through chi-square tests. Further analyses will engage multivariable logistic regression to discern correlations between various clinical factors and potential sepsis.
Approval from the Mater Misericordiae University Hospital Research Ethics Committee has been secured. The study will merely involve retrospective reviews of clinical records, maintaining patient confidentiality with no identifiers being stored in the dataset. Ethical compliance, including adherence to GDPR regulations, will be upheld.
This study aspires to furnish a detailed evaluation of patients with community-acquired acute infections within an Irish emergency department. By analyzing data from extensive sampling periods, the research intends to clarify community-acquired infection traits and associated risk factors.
A significant advantage of this study lies in its focus on early patient presentation phases, often omitted in administrative data like HIPE. Understanding these procedures and referral patterns will yield insights on improving early sepsis recognition and escalation strategies within healthcare systems.