Evidence map›Paper›PMID 27711250›Full record

ArticlePloS one2016

Five-Year Antimicrobial Resistance Patterns of Urinary Escherichia coli at an Australian Tertiary Hospital: Time Series Analyses of Prevalence Data.

Oyebola Fasugba, Brett G Mitchell, George Mnatzaganian, Anindita Das, Peter Collignon, Anne Gardner

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 1 pooled it
5.0field-weighted citation impact, top 4% 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

35 citing papers in PubMed, 1 synthesis or guideline pooled it, 83 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Article
  4. Antibiotic Therapy for Pyelonephritis in the Emergency Department.Emergency medicine Australasia : EMA · 2025
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  9. Temporal Trends ofAntibiotics (Basel, Switzerland) · 2025
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  11. Unlocking Nitrofurantoin: Understanding Molecular Mechanisms of Action and Resistance in Enterobacterales.Medical principles and practice : international journal of the Kuwait University, Health Science Centre · 2025
    Review
  12. Article
  13. Investigating trends in antibiotic resistance ofMicrobiology (Reading, England) · 2024
    Article
  14. Article
  15. Article
  16. Article
  17. Review
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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

6 authors at 4 institutions in 1 country.

Oyebola FasugbaFaculty of Health Sciences, Australian Catholic University, Australian Capital Territory, Australia.
Brett G MitchellFaculty of Health Sciences, Australian Catholic University, Australian Capital Territory, Australia.
George MnatzaganianCollege of Science, Health and Engineering, La Trobe Rural Health School, La Trobe University, Victoria, Australia.
Anindita DasAustralian Capital Territory Pathology, Canberra Hospital and Health Services, Garran, Australian Capital Territory, Australia.
Peter CollignonAustralian Capital Territory Pathology, Canberra Hospital and Health Services, Garran, Australian Capital Territory, Australia.
Anne GardnerFaculty of Health Sciences, Australian Catholic University, Australian Capital Territory, Australia.
Australian Catholic University · AUCanberra Hospital · AUAvondale University · AULa Trobe University · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study describes the antimicrobial resistance temporal trends and seasonal variation of Escherichia coli (E. coli) urinary tract infections (UTIs) over five years, from 2009 to 2013, and compares prevalence of resistance in hospital- and community-acquired E. coli UTI. A cross sectional study of E. coli UTIs from patients attending a tertiary referral hospital in Canberra, Australia was undertaken. Time series analysis was performed to illustrate resistance trends. Only the first positive E. coli UTI per patient per year was included in the analysis. A total of 15,022 positive cultures from 8724 patients were identified. Results are based on 5333 first E. coli UTIs, from 4732 patients, of which 84.2% were community-acquired. Five-year hospital and community resistance rates were highest for ampicillin (41.9%) and trimethoprim (20.7%). Resistance was lowest for meropenem (0.0%), nitrofurantoin (2.7%), piperacillin-tazobactam (2.9%) and ciprofloxacin (6.5%). Resistance to amoxycillin-clavulanate, cefazolin, gentamicin and piperacillin-tazobactam were significantly higher in hospital- compared to community-acquired UTIs (9.3% versus 6.2%; 15.4% versus 9.7%; 5.2% versus 3.7% and 5.2% versus 2.5%, respectively). Trend analysis showed significant increases in resistance over five years for amoxycillin-clavulanate, trimethoprim, ciprofloxacin, nitrofurantoin, trimethoprim-sulphamethoxazole, cefazolin, ceftriaxone and gentamicin (P<0.05, for all) with seasonal pattern observed for trimethoprim resistance (augmented Dickey-Fuller statistic = 4.136; P = 0.006). An association between ciprofloxacin resistance, cefazolin resistance and ceftriaxone resistance with older age was noted. Given the relatively high resistance rates for ampicillin and trimethoprim, these antimicrobials should be reconsidered for empirical treatment of UTIs in this patient population. Our findings have important implications for UTI treatment based on setting of acquisition.

Indexed as

AgedAmpicillinAnti-Bacterial AgentsAustraliabeta-LactamasesCross-Sectional StudiesDrug Resistance, BacterialEscherichia coliEscherichia coli InfectionsFemaleHumansMaleMicrobial Sensitivity TestsMiddle AgedPrevalenceSeasonsAmpicillinAnti-Bacterial Agentsbeta-LactamasesTrimethoprim

Identifiers

PMID27711250
PMCPMC5053592
OpenAlexW2529518419

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.