Evidence map›Paper›PMID 37658908›Full record

ArticleClinical infectious diseases : an official publication of the Infectious Diseases Society of America2023

Diagnostic Accuracy of Hospital Antibiograms in Predicting the Risk of Antimicrobial Resistance in Enterobacteriaceae Isolates: A Nationwide Multicenter Evaluation at the Veterans Health Administration.

Shinya Hasegawa, Daniel J Livorsi, Eli N Perencevich, Jonas N Church, Michihiko Goto

Open access · bronzeAbstract readMulticenter Study
In one paragraph

Article in Clinical infectious diseases : an official publication of the Infectious Diseases Society of America, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
4.0field-weighted citation impact, top 5% of its field
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

10 citing papers in PubMed, 19 citations in OpenAlex.

  1. Article
  2. Article
  3. The institutional antibiogram: Time for a makeover?Journal of hospital medicine · 2026
    Article
  4. Article
  5. Article
  6. Variation in facility-level likelihood of drug-resistantAntimicrobial stewardship & healthcare epidemiology : ASHE · 2025
    Article
  7. Article
  8. Article
  9. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Shinya HasegawaCenter for Access and Delivery Research and Evaluation, Iowa City Veterans Affairs Health Care System, Iowa City, Iowa, USA.ORCID 0000-0001-7167-270X
Daniel J LivorsiCenter for Access and Delivery Research and Evaluation, Iowa City Veterans Affairs Health Care System, Iowa City, Iowa, USA.ORCID 0000-0001-8523-214X
Eli N PerencevichCenter for Access and Delivery Research and Evaluation, Iowa City Veterans Affairs Health Care System, Iowa City, Iowa, USA.ORCID 0000-0002-3721-3355
Jonas N ChurchDepartment of Internal Medicine, University of Iowa, Iowa City, Iowa, USA.
Michihiko GotoCenter for Access and Delivery Research and Evaluation, Iowa City Veterans Affairs Health Care System, Iowa City, Iowa, USA.ORCID 0000-0001-6612-5613
University of Iowa · US

Funding

Agency for Healthcare Research and Quality K08HS027472AHRQ HHS K08 HS027472
6 · The paper itself

Abstract

backgroundMany clinical guidelines recommend that clinicians use antibiograms to inform empiric antimicrobial therapy. However, hospital antibiograms are typically generated by crude aggregation of microbiologic data, and little is known about an antibiogram's reliability in predicting antimicrobial resistance (AMR) risk at the patient-level. We aimed to assess the diagnostic accuracy of antibiograms as a tool for selecting empiric therapy for Escherichia coli and Klebsiella spp. for individual patients.

methodsWe retrospectively generated hospital antibiograms for the nationwide Veterans Health Administration (VHA) facilities from 2000 to 2019 using all clinical culture specimens positive for E. coli and Klebsiella spp., then assessed the diagnostic accuracy of an antibiogram to predict resistance for isolates in the following calendar year using logistic regression models and predefined 5-step interpretation thresholds.

resultsAmong 127 VHA facilities, 1 484 038 isolates from 704 779 patients for E. coli and 671 035 isolates from 340 504 patients for Klebsiella spp. were available for analysis. For E. coli and Klebsiella spp., the discrimination abilities of hospital-level antibiograms in predicting individual patient AMR were mostly poor, with the areas under the receiver operating curve at 0.686 and 0.715 for ceftriaxone, 0.637 and 0.675 for fluoroquinolones, and 0.576 and 0.624 for trimethoprim-sulfamethoxazole, respectively. The sensitivity and specificity of the antibiogram varied widely by antimicrobial groups and interpretation thresholds with substantial trade-offs.

conclusionsConventional hospital antibiograms for E. coli and Klebsiella spp. have limited performance in predicting AMR for individual patients, and their utility in guiding empiric therapy may be low.

Indexed as

Anti-Bacterial AgentsEscherichia coliDrug Resistance, BacterialHospitalsHumansKlebsiellaMicrobial Sensitivity TestsReproducibility of ResultsRetrospective StudiesRisk FactorsVeterans HealthAnti-Bacterial Agentsantimicrobial resistancediagnostic accuracyempiric therapygram-negative rodshospital antibiogram

Identifiers

PMID37658908
PMCPMC11487110
OpenAlexW4385752432

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.