Abstract

Intravenous fluids are an essential part of treatment in sepsis, but there remains clinical equipoise on which type of crystalloid fluids to use in sepsis. A previously reported sepsis subphenotype (ie, group D) has demonstrated a substantial mortality benefit from balanced crystalloids compared with normal saline. To test the hypothesis that targeting balanced crystalloids to patients with group D sepsis through an electronic health record (EHR) alert will reduce 30-day inpatient mortality. The Precision Resuscitation With Crystalloids in Sepsis (PRECISE) trial is a parallel-group, multihospital, single-blind, pragmatic randomized clinical trial to be conducted at 6 hospitals in the Emory Healthcare system. Patients with suspicion of group D infection in whom a clinician initiates an order for normal saline in the emergency department (ED) or intensive care unit (ICU) will be randomized to usual care and intervention arms. An EHR alert that appears in the ED and ICUs to nudge clinicians to use balanced crystalloids instead of normal saline. The primary outcome is 30-day inpatient mortality. Secondary outcomes are ICU admission, in-hospital mortality, receipt of vasoactive drugs, receipt of new kidney replacement therapy, and receipt of mechanical ventilation (vasoactive drugs, kidney replacement therapy, and mechanical ventilation are counted if they occur after randomization and within the 30-day study period). Intention-to-treat analysis will be conducted. The PRECISE trial may be one of the first precision medicine trials of crystalloid fluids in sepsis. Using routine vital signs (temperature, heart rate, respiratory rate, and blood pressure), available even in low-resource settings, a validated machine learning algorithm will prospectively identify and enroll patients with group D sepsis who may have a substantial mortality reduction from used of balanced crystalloids compared with normal saline. On finalizing participant enrollment and analyzing the data, the study's findings will be shared with the public through publication in a peer-reviewed journal. With use of a validated machine learning algorithm, precision resuscitation in sepsis could fundamentally redefine international standards for intravenous fluid resuscitation. ClinicalTrials.gov Identifier: NCT06253585.

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