Evidence map›Paper›PMID 25734120›Full record

ArticleOpen forum infectious diseases2014

Determinants of Clostridium difficile Infection Incidence Across Diverse United States Geographic Locations.

Fernanda C Lessa, Yi Mu, Lisa G Winston, Ghinwa K Dumyati, Monica M Farley, Zintars G Beldavs, Kelly Kast, Stacy M Holzbauer, James I Meek, Jessica Cohen and 2 more

Open access · goldAbstract read
In one paragraph

Article in Open forum infectious diseases, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 3 pooled it
2.9field-weighted citation impact, top 9% 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

31 citing papers in PubMed, 3 syntheses or guidelines pooled it, 50 citations in OpenAlex.

  1. Epidemiologic profile of community-acquiredEpidemiology and infection · 2025
    Pooled it
  2. Pooled it
  3. Global burden ofJournal of global health · 2019
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  7. Trends and Disparities inGastroenterology research and practice · 2026
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  11. Antibiotics (Basel, Switzerland) · 2024
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  12. Potential underreporting of treated patients using aInfection control and hospital epidemiology · 2024
    Observational
  13. Article
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  16. Prevalence of diagnostically-discrepantFrontiers in medicine · 2023
    Article
  17. Comparison of the Risk of RecurrentOpen forum infectious diseases · 2022
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  18. Open forum infectious diseases · 2021
    Article
  19. Health care resource utilization and costs of recurrentJournal of managed care & specialty pharmacy · 2021
    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

12 authors at 10 institutions in 1 country.

Fernanda C LessaDivision of Healthcare Quality Promotion, National Center for Emerging and Zoonotic Infectious Diseases , Centers for Disease Control and Prevention , Atlanta, Georgia.
Yi MuDivision of Healthcare Quality Promotion, National Center for Emerging and Zoonotic Infectious Diseases , Centers for Disease Control and Prevention , Atlanta, Georgia.
Lisa G WinstonDivision of Infectious Diseases , University of California, San Francisco School of Medicine.
Ghinwa K DumyatiDivision of Infectious Diseases , University of Rochester Medical Center , New York.
Monica M FarleyDivision of Infectious Diseases , Emory University School of Medicine , Atlanta, Georgia ; Atlanta Veterans Affairs Medical Center , Georgia.
Zintars G BeldavsOregon Health Authority, Public Health Division , Portland.
Kelly KastColorado Department of Public Health and Environment, Denver.
Stacy M HolzbauerCenters for Disease Control and Prevention Epidemiology Field Officer Assigned to Minnesota Department of Health, St. Paul, Minnesota.
James I MeekEmerging Infections Program , Yale University School of Public Health , New Haven, Connecticut.
Jessica CohenDivision of Healthcare Quality Promotion, National Center for Emerging and Zoonotic Infectious Diseases , Centers for Disease Control and Prevention , Atlanta, Georgia ; Atlanta Research and Education Foundation , Georgia.
L Clifford McDonaldDivision of Healthcare Quality Promotion, National Center for Emerging and Zoonotic Infectious Diseases , Centers for Disease Control and Prevention , Atlanta, Georgia.
Scott K FridkinDivision of Healthcare Quality Promotion, National Center for Emerging and Zoonotic Infectious Diseases , Centers for Disease Control and Prevention , Atlanta, Georgia.
National Center for Emerging and Zoonotic Infectious Diseases · USAtlanta Research and Education Foundation · USCenters for Disease Control and Prevention · USColorado Department of Public Health and Environment · USMinnesota Department of Health · USOregon Health Authority · USUniversity of California, San Francisco · USUniversity of Rochester Medical Center · USVeterans Health Administration · USYale University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundClostridium difficile infection (CDI) is no longer restricted to hospital settings, and population-based incidence measures are needed. Understanding the determinants of CDI incidence will allow for more meaningful comparisons of rates and accurate national estimates.

methodsData from active population- and laboratory-based CDI surveillance in 7 US states were used to identify CDI cases (ie, residents with positive C difficile stool specimen without a positive test in the prior 8 weeks). Cases were classified as community-associated (CA) if stool was collected as outpatients or ≤3 days of admission and no overnight healthcare facility stay in the past 12 weeks; otherwise, cases were classified as healthcare-associated (HA). Two regression models, one for CA-CDI and another for HA-CDI, were built to evaluate predictors of high CDI incidence. Site-specific incidence was adjusted based on the regression models.

resultsOf 10 062 cases identified, 32% were CA. Crude incidence varied by geographic area; CA-CDI ranged from 28.2 to 79.1/100 000 and HA-CDI ranged from 45.7 to 155.9/100 000. Independent predictors of higher CA-CDI incidence were older age, white race, female gender, and nucleic acid amplification test (NAAT) use. For HA-CDI, older age and a greater number of inpatient-days were predictors. After adjusting for relevant predictors, the range of incidence narrowed greatly; CA-CDI rates ranged from 30.7 to 41.3/100 000 and HA-CDI rates ranged from 58.5 to 94.8/100 000.

conclusionsDifferences in CDI incidence across geographic areas can be partially explained by differences in NAAT use, age, race, sex, and inpatient-days. Variation in antimicrobial use may contribute to the remaining differences in incidence.

Identifiers

PMID25734120
PMCPMC4281776
OpenAlexW2139367531

What OpenQuestion holds

Textmetadata
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.