Evidence map›Paper›PMID 25911052›Full record

ArticleBMJ quality & safety2015

The association of hospital prevention processes and patient risk factors with the risk of Clostridium difficile infection: a population-based cohort study.

N Daneman, A Guttmann, X Wang, X Ma, D Gibson, T A Stukel

Open access · hybridAbstract read
In one paragraph

Article in BMJ quality & safety, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.7field-weighted citation impact, top 16% 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

7 citing papers in PubMed, 21 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Correlation of prevention practices with rates of health care-associatedInfection control and hospital epidemiology · 2020
    Article
  5. Article
  6. Article
  7. Hospital acquired diarrhea in a burn center of Tehran.Iranian journal of microbiology · 2015
    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

6 authors at 3 institutions in 1 country.

N DanemanInstitute for Clinical Evaluative Sciences, Toronto, Ontario, Canada Division of Infectious Diseases, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada.
A GuttmannInstitute for Clinical Evaluative Sciences, Toronto, Ontario, Canada Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada Division of Paediatric Medicine, Hospital for Sick Children, Toronto, Ontario, Canada Department of Paediatrics, University of Toronto, Toronto, Ontario, Canada.
X WangInstitute for Clinical Evaluative Sciences, Toronto, Ontario, Canada.
X MaInstitute for Clinical Evaluative Sciences, Toronto, Ontario, Canada.
D GibsonHealth Analytics Branch, Ontario Ministry of Health and Long-Term Care, Toronto, Ontario, Canada.
T A StukelInstitute for Clinical Evaluative Sciences, Toronto, Ontario, Canada Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada.
Institute for Clinical Evaluative Sciences · CAHealth Sciences Centre · CAMinistry of Health and Long Term Care · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundClostridium difficile is the most common cause of healthcare-acquired infection; the real-world impacts of some proposed C. difficile prevention processes are unknown.

methodsWe conducted a population-based retrospective cohort study of all patients admitted to acute care hospitals between April 2011 and March 2012 in Ontario, Canada. Hospital prevention practices were determined by survey of infection control programmes; responses were linked to patient-level risk factors and C. difficile outcomes in Ontario administrative databases. Multivariable generalised estimating equation (GEE) regression models were used to assess the impact of selected understudied hospital prevention processes on the patient-level risk of C. difficile infection, accounting for patient risk factors, baseline C. difficile rates and structural hospital characteristics.

resultsC. difficile infections complicated 2341 of 653 896 admissions (3.6 per 1000 admissions). Implementation of the selected C. difficile prevention practices was variable across the 159 hospitals with isolation of all patients at onset of diarrhoea reported by 43 (27%), auditing of antibiotic stewardship compliance by 26 (16%), auditing of cleaning practices by 115 (72%), on-site diagnostic testing by 74 (47%), vancomycin as first-line treatment by 24 (15%) and reporting rates to senior leadership by 52 (33%). None of these processes were associated with a significantly reduced risk of C. difficile after adjustment for baseline C. difficile rates, structural hospital characteristics and patient-level factors. Patient-level factors were strongly associated with C. difficile risk, including age, comorbidities, non-elective and medical admissions.

conclusionsIn the largest study to date, selected hospital prevention strategies were not associated with a statistically significant reduction in patients' risk of C. difficile infection. These prevention strategies have either limited effectiveness or were ineffectively implemented during the study period.

Indexed as

Clostridioides difficileHospitalsAdolescentAdultAgedAged, 80 and overAge FactorsChildChild, PreschoolClostridium InfectionsCross InfectionFemaleHumansInfantInfection ControlMaleHealthcare quality improvementHealth services researchInfection controlNosocomial infections

Identifiers

PMID25911052
PMCPMC4484271
OpenAlexW2152559248

What OpenQuestion holds

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LicenceCC BY-NC
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.