PRIME-Sepsis Trial: Presepsin and Immature Granulocytes for Multicenter Early Sepsis Detection in the Emergency Department: A Prospective Observational Study

Sepsis is characterized by a dysregulated host inflammatory response to infection, potentially leading to multiple organ dysfunction syndrome (MODS) and death. Globally, the estimated annual incidence of sepsis ranges from 18 to 31.5 million cases, with mortality rates as high as 30%. Approximately 70% of sepsis patients are initially managed in the emergency department (ED). Although delayed recognition and treatment are associated with poorer outcomes, and early evidence-based intervention significantly improves survival , early identification of sepsis in the ED remains a formidable clinical challenge . Despite the critical need for prompt intervention, research indicates that the detection of infection is often delayed by more than 4 hours after hospital admission and by over 8 hours in approximately 30% of ED cases.

Diverse biomarkers have been proposed to facilitate timely diagnosis, risk stratification, and the initiation of appropriate treatment. Complete blood count (CBC) parameters are particularly advantageous in the ED due to their rapid turnaround time, low cost, and repeatability. Traditionally, white blood cell (WBC) count and immature granulocyte (IG) count have served as first-line indicators. Advanced hematology technologies now provide detailed morphologic data (e.g., cell volume and structural changes), potentially enhancing the diagnostic value of these parameters. While IG has been recognized as a marker of systemic inflammation and sepsis, its clinical utility remains a subject of ongoing debate. Specifically, some studies suggest limited predictive value for long-term outcomes such as 28-day mortality, leading to inconsistent conclusions regarding its diagnostic reliability when used in isolation for the detection of sepsis.

Recent investigations into IG for ED sepsis diagnosis have reported areas under the receiver operating characteristic curve (AUC) ranging from 0.52 to 0.93. This pronounced variability is likely attributable to differences in study methodologies and patient populations. Concurrently, Presepsin (soluble CD14 subtype, sCD14-ST) has emerged as a promising alternative biomarker. Presepsin is generated via monocyte activation and pathogen phagocytosis, resulting in a rapid surge in circulating levels during the incipient immune response. Evidence suggests that Presepsin rises earlier than conventional biomarkers and correlates strongly with sepsis severity and clinical outcomes. Specifically, Presepsin has demonstrated superior or comparable diagnostic performance to C-reactive protein (CRP) and procalcitonin (PCT) in emergency settings.

Previous investigations have consistently demonstrated the superior diagnostic performance of Presepsin, with reported Area Under the Receiver Operating Characteristic curve (AUROC) values often exceeding 0.90 in both emergency sepsis presentations and complex postoperative infectious settings, supporting its role as a benchmark biomarker for early infection detection.

In the PRIME-Sepsis Trial (Presepsin and Immature Granulocytes for Multicenter Early Sepsis Detection), we aim to evaluate the synergistic diagnostic accuracy of integrating IG and Presepsin for identifying sepsis in adult patients with a high clinical suspicion of infection in the ED. While Presepsin offers superior diagnostic potential in the hyper-acute phase, IG provides a readily available, cost-effective reflection of the systemic hematopoietic response. By synergizing these complementary biomarkers, our primary objective is to assess the incremental diagnostic yield of a combined molecular-cellular model against multiple reference standards (Sepsis-2, Sepsis-3, and qSOFA). This approach will enable us to derive and evaluate a novel dual-parameter diagnostic algorithm, ultimately facilitating earlier clinical decision-making and improving prognostic accuracy in diverse emergency care settings. This prospective, multicenter design minimizes the biases inherent in previous retrospective analyses, providing a more robust foundation for clinical implementation.