Evidence map›Paper›PMID 40426534›Full record

ReviewAntibiotics (Basel, Switzerland)2025

Antibiotic De-Escalation in the Intensive Care Unit: Rationale and Potential Strategies.

Sarah Singer Matuszak, Lauren Kolodziej, Scott Micek, Marin Kollef

Abstract readReview
In one paragraph

Review in Antibiotics (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Review
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  7. Longitudinal biomarker trajectories and their prognostic utility for 21-day mortality in burn patients with sepsis: a retrospective cohort study.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2026
    Article
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  9. Review
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  12. Therapeutic approach in the critically ill patient with suspected multidrug resistance.Revista espanola de quimioterapia : publicacion oficial de la Sociedad Espanola de Quimioterapia · 2025
    Review
  13. Review
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.

Sarah Singer MatuszakDepartment of Pharmacy, Barnes-Jewish Hospital, St. Louis, MO 63110, USA.ORCID 0009-0008-4410-0720
Lauren KolodziejDepartment of Pharmacy, Barnes-Jewish Hospital, St. Louis, MO 63110, USA.ORCID 0009-0007-0949-0666
Scott MicekDepartment of Pharmacy Practice, University of Health Sciences and Pharmacy, St. Louis, MO 63110, USA.
Marin KollefDivision of Pulmonary and Critical Care Medicine, Washington University School of Medicine, St. Louis, MO 63110, USA.ORCID 0000-0003-0671-0751

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Antibiotic de-escalation (ADE) is important to help optimize antibiotic use and balance the positive and negative effects of antimicrobial therapy. ADE should be performed promptly, and infections should be treated with the shortest course of antimicrobials as clinically feasible to avoid unnecessary use of broad-spectrum antimicrobials. Several tools have been developed to increase efficient ADE, including rapid diagnostic tests (ex. multiplex PCR), MRSA nasal PCR/culture, and biomarkers. Multiplex PCR and MRSA nasal PCR/culture have been associated with reductions in inappropriate antibiotic use. Procalcitonin, a biomarker, has been associated with shorter antimicrobial durations in some studies; however, widespread use may be limited by lack of specificity for bacterial infections, cost, and lack of set cut-off points. Additional biomarkers such as IL-6, HMGB1, presepsin, sTREM-1, CD64, PSP, proadrenomedullin, and pentraxin-3 are currently being studied. As technology improves, additional tools may be leveraged to better optimize ADE even better, such as antimicrobial spectrum scoring tools and artificial intelligence (AI). Spectrum scores, which quantify antibiotic activity using specific numeric values, could be incorporated into electronic health records to identify patients on unnecessarily broad antibiotics. AI modeling has the potential to predict personal antibiograms or provide the probability that an empiric regimen may cover a particular infection, among other potential applications. This review will discuss the literature associated with ADE in the ICU, selected tools to help guide ADE, and perspectives on how to implement ADE into clinical practice.

Indexed as

antibioticsantimicrobial resistanceantimicrobial stewardshipde-escalationdurationintensive care unitrapid diagnosticssepsisspectrum

Identifiers

PMID40426534
PMCPMC12108321

What OpenQuestion holds

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Registered trials

None linked

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.