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Estimating the burden of antimicrobial resistance: a systematic literature review

Overview of attention for article published in Antimicrobial Resistance and Infection Control, April 2018
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#45 of 1,210)
  • High Attention Score compared to outputs of the same age (95th percentile)

Mentioned by

news
1 news outlet
blogs
1 blog
policy
2 policy sources
twitter
57 tweeters

Citations

dimensions_citation
229 Dimensions

Readers on

mendeley
647 Mendeley
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Title
Estimating the burden of antimicrobial resistance: a systematic literature review
Published in
Antimicrobial Resistance and Infection Control, April 2018
DOI 10.1186/s13756-018-0336-y
Pubmed ID
Authors

Nichola R. Naylor, Rifat Atun, Nina Zhu, Kavian Kulasabanathan, Sachin Silva, Anuja Chatterjee, Gwenan M. Knight, Julie V. Robotham

Abstract

Accurate estimates of the burden of antimicrobial resistance (AMR) are needed to establish the magnitude of this global threat in terms of both health and cost, and to paramaterise cost-effectiveness evaluations of interventions aiming to tackle the problem. This review aimed to establish the alternative methodologies used in estimating AMR burden in order to appraise the current evidence base. MEDLINE, EMBASE, Scopus, EconLit, PubMed and grey literature were searched. English language studies evaluating the impact of AMR (from any microbe) on patient, payer/provider and economic burden published between January 2013 and December 2015 were included. Independent screening of title/abstracts followed by full texts was performed using pre-specified criteria. A study quality score (from zero to one) was derived using Newcastle-Ottawa and Philips checklists. Extracted study data were used to compare study method and resulting burden estimate, according to perspective. Monetary costs were converted into 2013 USD. Out of 5187 unique retrievals, 214 studies were included. One hundred eighty-seven studies estimated patient health, 75 studies estimated payer/provider and 11 studies estimated economic burden. 64% of included studies were single centre. The majority of studies estimating patient or provider/payer burden used regression techniques. 48% of studies estimating mortality burden found a significant impact from resistance, excess healthcare system costs ranged from non-significance to $1 billion per year, whilst economic burden ranged from $21,832 per case to over $3 trillion in GDP loss. Median quality scores (interquartile range) for patient, payer/provider and economic burden studies were 0.67 (0.56-0.67), 0.56 (0.46-0.67) and 0.53 (0.44-0.60) respectively. This study highlights what methodological assumptions and biases can occur dependent on chosen outcome and perspective. Currently, there is considerable variability in burden estimates, which can lead in-turn to inaccurate intervention evaluations and poor policy/investment decisions. Future research should utilise the recommendations presented in this review. This systematic review is registered with PROSPERO (PROSPERO CRD42016037510).

Twitter Demographics

The data shown below were collected from the profiles of 57 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 647 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 647 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 106 16%
Student > Master 104 16%
Researcher 81 13%
Student > Bachelor 78 12%
Other 31 5%
Other 104 16%
Unknown 143 22%
Readers by discipline Count As %
Medicine and Dentistry 102 16%
Biochemistry, Genetics and Molecular Biology 63 10%
Immunology and Microbiology 58 9%
Agricultural and Biological Sciences 49 8%
Pharmacology, Toxicology and Pharmaceutical Science 39 6%
Other 162 25%
Unknown 174 27%

Attention Score in Context

This research output has an Altmetric Attention Score of 62. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 29 January 2022.
All research outputs
#525,826
of 21,435,803 outputs
Outputs from Antimicrobial Resistance and Infection Control
#45
of 1,210 outputs
Outputs of similar age
#13,522
of 296,845 outputs
Outputs of similar age from Antimicrobial Resistance and Infection Control
#1
of 1 outputs
Altmetric has tracked 21,435,803 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,210 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 16.1. This one has done particularly well, scoring higher than 96% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 296,845 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them