Evidence map›Paper›PMID 24968123›Full record

SynthesisPLoS pathogens2014

Cycling empirical antibiotic therapy in hospitals: meta-analysis and models.

Pia Abel zur Wiesch, Roger Kouyos, Sören Abel, Wolfgang Viechtbauer, Sebastian Bonhoeffer

Open access · goldAbstract readMeta-Analysis
In one paragraph

Synthesis in PLoS pathogens, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
53citing papers in PubMed, 2 pooled it
5.9field-weighted citation impact, top 3% 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

53 citing papers in PubMed, 2 syntheses or guidelines pooled it, 104 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Article
  5. Article
  6. Ceftobiprole in cystic fibrosis: a case series.JAC-antimicrobial resistance · 2025
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Tumour Growth Mechanisms Determine Effectiveness of Adaptive Therapy in Glandular Tumours.Interdisciplinary sciences, computational life sciences · 2024
    Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Association between Antibiotic Use and Hospital-OnsetAntibiotics (Basel, Switzerland) · 2022
    Article
  17. Article
  18. Article
  19. Article
  20. Article
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

5 authors at 4 institutions in 3 countries.

Pia Abel zur WieschInstitute of Integrative Biology, ETH Zurich, Zurich, Switzerland; Division of Global Health Equity, Brigham and Women's Hospital/Harvard Medical School, Boston, Massachusetts, United States of America.
Roger KouyosInstitute of Integrative Biology, ETH Zurich, Zurich, Switzerland; Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.
Sören AbelDivision of Infectious Diseases, Brigham and Women's Hospital/Harvard Medical School, Boston, Massachusetts, United States of America.
Wolfgang ViechtbauerDepartment of Psychiatry and Psychology, School for Mental Health and Neuroscience, Faculty of Health, Medicine, and Life Sciences, Maastricht University, Maastricht, The Netherlands.
Sebastian BonhoefferInstitute of Integrative Biology, ETH Zurich, Zurich, Switzerland.
ETH Zurich · CHBrigham and Women's Hospital · USHarvard University · USMaastricht University · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The rise of resistance together with the shortage of new broad-spectrum antibiotics underlines the urgency of optimizing the use of available drugs to minimize disease burden. Theoretical studies suggest that coordinating empirical usage of antibiotics in a hospital ward can contain the spread of resistance. However, theoretical and clinical studies came to different conclusions regarding the usefulness of rotating first-line therapy (cycling). Here, we performed a quantitative pathogen-specific meta-analysis of clinical studies comparing cycling to standard practice. We searched PubMed and Google Scholar and identified 46 clinical studies addressing the effect of cycling on nosocomial infections, of which 11 met our selection criteria. We employed a method for multivariate meta-analysis using incidence rates as endpoints and find that cycling reduced the incidence rate/1000 patient days of both total infections by 4.95 [9.43-0.48] and resistant infections by 7.2 [14.00-0.44]. This positive effect was observed in most pathogens despite a large variance between individual species. Our findings remain robust in uni- and multivariate metaregressions. We used theoretical models that reflect various infections and hospital settings to compare cycling to random assignment to different drugs (mixing). We make the realistic assumption that therapy is changed when first line treatment is ineffective, which we call "adjustable cycling/mixing". In concordance with earlier theoretical studies, we find that in strict regimens, cycling is detrimental. However, in adjustable regimens single resistance is suppressed and cycling is successful in most settings. Both a meta-regression and our theoretical model indicate that "adjustable cycling" is especially useful to suppress emergence of multiple resistance. While our model predicts that cycling periods of one month perform well, we expect that too long cycling periods are detrimental. Our results suggest that "adjustable cycling" suppresses multiple resistance and warrants further investigations that allow comparing various diseases and hospital settings.

Indexed as

Drug Resistance, BacterialModels, BiologicalAnti-Bacterial AgentsBacterial InfectionsDrug MonitoringDrug Resistance, Multiple, BacterialEmpirical ResearchGram-Negative BacteriaGram-Positive BacteriaHospital UnitsHumansIncidenceTime FactorsAnti-Bacterial Agents

Identifiers

PMID24968123
PMCPMC4072793
OpenAlexW2103863773

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.