Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 638

The DOI matches its Crossref record.

Antimicrobial Resistance

Marston, Hilary D., Dixon, Dennis M., Knisely, Jane M., Palmore, Tara N., Fauci, Anthony S.·2016·JAMA

Abstract

IMPORTANCE: The development of antibiotics is considered among the most important advances of modern science. Antibiotics have saved millions of lives. However, antimicrobial resistance (AMR) threatens this progress and presents significant risks to human health. OBJECTIVE: To identify factors associated with AMR, the current epidemiology of important resistant organisms, and possible solutions to the AMR problem. DATA SOURCES, STUDY SELECTION, AND DATA SYNTHESIS: PubMed (2000-2016), NIH REPORTER, and ClinicalTrials.gov databases were searched for articles and entries related to AMR, focusing on epidemiology, clinical effects of AMR, discovery of novel agents to treat AMR bacterial infections, and nonpharmacological strategies to eliminate or modify AMR bacteria. In addition to articles and entries found in these databases, selected health policy reports and public health guidance documents were reviewed. Of 217 articles, databases, and reports identified, 103 were selected for review. RESULTS: The increase in AMR has been driven by a diverse set of factors, including inappropriate antibiotic prescribing and sales, use of antibiotics outside of the health care sector, and genetic factors intrinsic to bacteria. The problem has been exacerbated by inadequate economic incentives for pharmaceutical development of new antimicrobial agents. A range of specific AMR concerns, including carbapenem- and colistin-resistant gram-negative organisms, pose a clinical challenge. Alternative approaches to address the AMR threat include new methods of antibacterial drug identification and strategies that neutralize virulence factors. CONCLUSIONS AND RELEVANCE: Antimicrobial resistance poses significant challenges for current clinical care. Modified use of antimicrobial agents and public health interventions, coupled with novel antimicrobial strategies, may help mitigate the effect of multidrug-resistant organisms in the future.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1001/jama.2016.11764

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cited by

See all 638

Metadata

Authors
Marston, H. D., Dixon, D. M., Knisely, J. M., Palmore, T. N., & Fauci, A. S.
Venue
JAMA
Published
2016-09-20
Volume
316
Issue
11
Pages
1193
ISSN
  • 0002-9955 (ISSN-L)
  • 0098-7484
OpenAlex
W4245505926
Cited by
638
References
0
FWCI
32.13
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Antimicrobial Resistance. https://app.cochat.ai/papers/10.1001/jama.2016.11764
The paper
Marston, H. D., Dixon, D. M., Knisely, J. M., Palmore, T. N., & Fauci, A. S. (2016). Antimicrobial Resistance. JAMA. https://doi.org/10.1001/jama.2016.11764

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.