Evidence map›Paper›PMID 30560781›Full record

ArticleeLife2018

The distribution of antibiotic use and its association with antibiotic resistance.

Scott W Olesen, Michael L Barnett, Derek R MacFadden, John S Brownstein, Sonia Hernández-Díaz, Marc Lipsitch, Yonatan H Grad

Abstract read
In one paragraph

Article in eLife, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 106 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
106citing papers in PubMed, 5 pooled it
–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

106 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Pooled it
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  4. β-Lactam-Resistant Streptococcus pneumoniae Dynamics Following Treatment: A Dose-Response Meta-analysis.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2022
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  16. Impact of antibiotic use onVeterinary world · 2025
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46 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Scott W OlesenDepartment of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, United States.ORCID http://orcid.org/0000-0001-5400-4945
Michael L BarnettDepartment of Health Policy and Management, Harvard T.H. Chan School of Public Health, Boston, United States.
Derek R MacFaddenDivision of Infectious Diseases, Department of Medicine, University of Toronto, Toronto, Canada.
John S BrownsteinBoston Children's Hospital, Boston, United States.
Sonia Hernández-DíazDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, United States.
Marc LipsitchDepartment of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, United States.ORCID http://orcid.org/0000-0003-1504-9213
Yonatan H GradDepartment of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, United States.ORCID http://orcid.org/0000-0001-5646-1314

Funding

Understanding and controlling antibiotic resistanceU54GM088558 · NIGMS · HARVARD SCHOOL OF PUBLIC HEALTH · PI LIPSITCH, MARC · 2009 to 2018
$26.4M
NIGMS NIH HHS U54 GM088558NIGMS NIH HHS U54GM088558
6 · The paper itself

Abstract

Antibiotic use is a primary driver of antibiotic resistance. However, antibiotic use can be distributed in different ways in a population, and the association between the distribution of use and antibiotic resistance has not been explored. Here, we tested the hypothesis that repeated use of antibiotics has a stronger association with population-wide antibiotic resistance than broadly-distributed, low-intensity use. First, we characterized the distribution of outpatient antibiotic use across US states, finding that antibiotic use is uneven and that repeated use of antibiotics makes up a minority of antibiotic use. Second, we compared antibiotic use with resistance for 72 pathogen-antibiotic combinations across states. Finally, having partitioned total use into extensive and intensive margins, we found that intense use had a weaker association with resistance than extensive use. If the use-resistance relationship is causal, these results suggest that reducing total use and selection intensity will require reducing broadly distributed, low-intensity use.

Indexed as

Drug Resistance, MicrobialAnti-Bacterial AgentsBacterial InfectionsDrug PrescriptionsHumansInsuranceRisk AssessmentRisk FactorsUnited StatesAnti-Bacterial Agentsantibiotic resistanceantimicrobialE. coliepidemiologyglobal healthinfectious diseasemicrobiologypublic healthS. pyogenes

Identifiers

PMID30560781
PMCPMC6307856

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.