Evidence map›Paper›PMID 42720074›Full record

Observational studyCritical care explorations2026

Diagnostic Uncertainty and Antibiotic Timing in Sepsis: Observational Validation of a Dual-Axis Decision Model.

Danielle Currey, Jonathan Siff, Satya Sahoo, Yasir Tarabichi

Abstract readObservational Study
In one paragraph

Observational study in Critical care explorations, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Danielle CurreySchool of Medicine, Case Western Reserve University, Cleveland, OH.
Jonathan SiffCenter for Clinical Informatics Research and Education, MetroHealth, Cleveland, OH.
Satya SahooDepartment of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH.
Yasir TarabichiSchool of Medicine, Case Western Reserve University, Cleveland, OH.ORCID 0000-0001-8577-5654

Funding

Clinical and Translational Science Collaborative of ClevelandUL1TR002548 · NCATS · CASE WESTERN RESERVE UNIVERSITY · PI MCCOMSEY, GRACE A · 2018 to 2022
$35.5M
Clinical and Translational Science Collaborative of Northern Ohio, Catalyzing Linkages to Equity in Health (CLE Health)UM1TR004528 · NCATS · CASE WESTERN RESERVE UNIVERSITY · PI GRACE A MCCOMSEY · 2023 to 2026
$32.1M
NCATS NIH HHS UL1 TR002548NCATS NIH HHS UM1 TR004528
6 · The paper itself

Abstract

importanceSepsis treatment requires balancing the benefits of timely antibiotic administration against the risks of over-treatment under diagnostic uncertainty. Although treatment urgency likely reflects both the probability of infection and physiologic severity, this joint structure has not previously been quantified using real-world clinical data.

objectivesTo determine whether real-world antibiotic timing in the emergency department reflects a dual-axis pattern integrating probability of infection and physiologic severity. DESIGN, SETTING, AND

participantsRetrospective observational cohort study using structured electronic health record data from adult emergency department encounters at a large urban safety-net health system from January 2019 through June 2025. A random forest model estimated the probability of sustained antibiotic treatment, P(treated infection), for suspected infection from early demographic, physiologic, and laboratory data, and physiologic severity was measured using the Modified Early Warning Score at 3 hours. MAIN OUTCOMES AND MEASURES: The primary outcome was time-to-antibiotics within 24 hours of presentation. The secondary outcome was a composite of ICU stay or in-hospital death among patients treated after 3 hours.

resultsThe study included 199,062 emergency department visits over 6.5 years. Of these, 83,910 visits were used for model development, and the remaining 115,152 emergency department encounters comprised a temporally held-out cohort used for model evaluation and downstream observational analyses. The P(treated infection) model demonstrated good discrimination (C-statistic, 0.86). Antibiotic timing followed a continuous gradient across jointly increasing P(treated infection) and physiologic severity, and restricted cubic spline regression confirmed significant contributions from both axes and their interaction (interaction, p = 0.0013). Among patients treated after 3 hours, antibiotic timing later-than-expected based on a patient's dual-axis position was associated with a higher rate of 3-day ICU stay or in-hospital death after adjustment for P(treated infection), physiologic severity, and their interaction (p < 0.001).

conclusionsReal-world antibiotic timing in suspected sepsis appears to reflect a dual-axis pattern consistent with clinicians integrating P(treated infection) and physiologic severity. Making this structure explicit may help identify unwarranted practice variation and inform future decision support strategies for timely treatment.

Indexed as

Anti-Bacterial AgentsDecision Support TechniquesSepsisTime-to-TreatmentAgedEmergency Service, HospitalFemaleHumansMaleMiddle AgedRetrospective StudiesTreatment DelayUncertaintyAnti-Bacterial Agentsclinical decision supportdiagnostic uncertaintyemergency departmentrisk stratificationsepsistime-to-antibiotics

Identifiers

PMID42720074
PMCPMC13561231

What OpenQuestion holds

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Registered trials

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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.