Evidence map›Paper›PMID 40298973›Full record

ArticleIntensive care medicine2025

Decision analysis model of rapid versus deferred antibiotic initiation in patients with suspected sepsis in the emergency department.

Terra M Hill, Lauren T Kerivan, Katherine A Vilain, Sam Windham, Nima Sarani, Steven Q Simpson, Christopher A Guidry

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Article in Intensive care medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Terra M HillDepartment of Surgery, University of Kansas Medical Center, Kansas City, USA.ORCID 0009-0006-9490-6912
Lauren T KerivanDepartment of Surgery, University of Kansas Medical Center, Kansas City, USA.
Katherine A VilainSaint Luke's Hospital Cardiovascular and Cardiothoracic Research, Kansas City, USA.ORCID 0000-0001-7615-1428
Sam WindhamDepartment of Internal Medicine, Medical Center, University of Kansas, Kansas City, USA.ORCID 0000-0002-3572-8291
Nima SaraniDepartment of Emergency Medicine, Medical Center, University of Kansas, Kansas City, USA.
Steven Q SimpsonDepartment of Internal Medicine, Medical Center, University of Kansas, Kansas City, USA.ORCID 0000-0002-9166-2717
Christopher A GuidryDepartment of Surgery, University of Kansas Medical Center, Kansas City, USA. cguidry2@kumc.edu.ORCID 0000-0003-0749-8625

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeSepsis remains a major health concern with high associated mortality. Adequate treatment involves the use of antibiotic therapy although the timing of antibiotics is controversial. A decision analysis model of antibiotic initiation was created to determine optimal management of patients with suspected sepsis.

methodsTwo decision trees were created using data from the published literature. A limited model used mortality as the primary outcome using the impact of antibiotic timing on rates of progression to shock and in-hospital mortality. The primary model included mortality and stewardship-related factors such as antibiotic avoidance and antibiotic-associated adverse events. Rapid initiation of antibiotics was defined as universal antibiotic administration within 3 h of presentation whereas deferred initiation included administration up to 6 h. Sensitivity analyses were performed to evaluate the effectiveness of each option.

resultsWhen considering only mortality, rapid initiation was the optimal strategy. When considering stewardship-related factors, rapid initiation of antibiotics maximized utility in only 40.6% of model iterations. One-way sensitivity analysis demonstrated rapid initiation of antibiotics was optimal when initiation times were above 1.33 h and the prevalence of infection was above 89.5%. Two-way sensitivity analysis demonstrated that as time to antibiotics increased, rate of true infection above which rapid antibiotics is optimal drops from just under 91% to approximately 88.5%.

conclusionWe constructed decision analysis models to characterize optimal conditions for antibiotic initiation in suspected sepsis. Our model suggests that the prevalence of infection needs to be approximately 90% for rapid initiation of antibiotics to be the optimal strategy.

Indexed as

Anti-Bacterial AgentsDecision Support TechniquesEmergency Service, HospitalSepsisAntimicrobial StewardshipDecision TreesHospital MortalityHumansTime FactorsTime-to-TreatmentAnti-Bacterial AgentsAntibiotic timingDecision analysisEmergency departmentSepsis

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.