Cited by 21Sepsis Diagnosis and TreatmentAcute Kidney Injury ResearchAntibiotics Pharmacokinetics and Efficacy

The Precision Resuscitation With Crystalloids in Sepsis (PRECISE) Trial: A Trial Protocol

Open access
Bhavani, Sivasubramanium V., Holder, Andre, Miltz, Danielle, Kamaleswaran, Rishikesan, Khan, Sharaf, Easley, Kirk, Murphy, David J., Franks, Nicole +6 more·2024·JAMA Network Open

Abstract

Importance: 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. Objective: 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. Design, Setting, and Participants: 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. Intervention: An EHR alert that appears in the ED and ICUs to nudge clinicians to use balanced crystalloids instead of normal saline. Main Outcomes and Measures: 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. Discussion: 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. Results: 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. Conclusions: With use of a validated machine learning algorithm, precision resuscitation in sepsis could fundamentally redefine international standards for intravenous fluid resuscitation. Trial Registration: ClinicalTrials.gov Identifier: NCT06253585.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1001/jamanetworkopen.2024.34197

Cites

21 of 21 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • AI could improve RCTs by allowing the enrolment of very subtle subgroups of patients with hundreds of specific inclusion criteria over dozens of centres, improving trial efficiency in enrolling enriched populations.

    “AI could thus improve RCTs by allowing the enrolment of very subtle subgroups of patients with hundreds of specific inclusion criteria over dozens of centres, a task impossible to perform by humans in real-time practice, improving trial efficiency in enrolling enriched populations [65–67].”

    From Implementing Artificial Intelligence in Critical Care Medicine: a consensus of 22. (2025) · cites this paper as [66]

    The Introduction and Methods (Study Design; Population) describe an algorithm that identifies a sepsis subphenotype for enrollment and randomization across six hospitals. The Discussion says the trial may demonstrate the feasibility of real-time precision enrollment. The paper does not describe hundreds of inclusion criteria, dozens of centres, a demonstrated improvement in enrollment efficiency, or a task impossible for humans in real time. (LLM, conf=0.89)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Bhavani, S. V., Holder, A., Miltz, D., Kamaleswaran, R., Khan, S., Easley, K., Murphy, D. J., Franks, N., Wright, D. W., Kraft, C., Semler, M. W., Churpek, M. M., Martin, G. S., & Coopersmith, C. M.
Affiliations
  • Emory University (US)
  • Duke University (US)
  • Vanderbilt University (US)
  • University of Wisconsin–Madison (US)
Corresponding author
Bhavani, Sivasubramanium V.
Venue
JAMA Network Open
Published
2024-09-18
Volume
7
Issue
9
Pages
e2434197
ISSN
2574-3805 (ISSN-L)
OpenAlex
W4402599603
Cited by
21
References
21
Citations by year
2026: 12 · 2025: 9
FWCI
6.41
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • JAMA Network Open (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • PubMed Central (publishedVersion, cc-by)
Funders
National Institute of General Medical Sciences (K23GM137182, R35GM148217, R35GM145330, K23GM144867)
Topics
  • Health Sciences › Medicine › Epidemiology › Sepsis Diagnosis and Treatment
  • Health Sciences › Medicine › Nephrology › Acute Kidney Injury Research
  • Health Sciences › Medicine › Pharmacology › Antibiotics Pharmacokinetics and Efficacy
Keywords
sepsis, crystalloid resuscitation, balanced crystalloids, normal saline, electronic health record alerts, precision medicine, 30-day mortality, intravenous fluid therapy, vasoactive drugs, renal replacement therapy, mechanical ventilation
MeSH terms
Crystalloid Solutions, Female, Fluid Therapy, Humans, Resuscitation, Randomized Controlled Trials as Topic, Single-Blind Method, Hospital Mortality, Sepsis, Electronic Health Records, Pragmatic Clinical Trials as Topic

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review