Evidence map›Paper›PMID 26450660›Full record

ArticleVaccine2015

Identification of population at risk for future Clostridium difficile infection following hospital discharge to be targeted for vaccine trials.

James Baggs, Kimberly Yousey-Hindes, Elizabeth Dodds Ashley, James Meek, Ghinwa Dumyati, Jessica Cohen, Matthew E Wise, L Clifford McDonald, Fernanda C Lessa

Abstract read
In one paragraph

Article in Vaccine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.0field-weighted citation impact, top 26% 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

8 citing papers in PubMed, 17 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. A Risk Score to PredictOpen forum infectious diseases · 2021
    Article
  5. Reductions in inpatient fluoroquinolone use and postdischargeAntimicrobial stewardship & healthcare epidemiology : ASHE · 2021
    Article
  6. Evaluation of a risk score to predict futureHuman vaccines & immunotherapeutics · 2019
    Observational
  7. Increasing Age Has Limited Impact on Risk ofOpen forum infectious diseases · 2018
    Article
  8. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors at 2 institutions in 2 countries.

James BaggsDivision of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, GA, United States. Electronic address: jbaggs@cdc.gov.
Kimberly Yousey-HindesConnecticut Emerging Infections Program, Yale School of Public Health, New Haven, CT, United States.
Elizabeth Dodds AshleyUniversity of Rochester Medical Center, Rochester, NY, United States.
James MeekConnecticut Emerging Infections Program, Yale School of Public Health, New Haven, CT, United States.
Ghinwa DumyatiUniversity of Rochester Medical Center, Rochester, NY, United States.
Jessica CohenDivision of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, GA, United States; Atlanta Research and Education Foundation, Atlanta, GA, United States.
Matthew E WiseDivision of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, GA, United States.
L Clifford McDonaldDivision of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, GA, United States.
Fernanda C LessaDivision of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, GA, United States.
Centers for Disease Control and Prevention · USUniversity of Rochester Medical Center · US

Funding

Intramural CDC HHS CC999999
6 · The paper itself

Abstract

backgroundEfforts to develop a Clostridium difficile vaccine are underway; identification of patients at risk for C. difficile infection (CDI) is critical to inform vaccine trials. We identified groups at high risk of CDI ≥ 2 8 days after hospital discharge.

methodsHospital discharge data and pharmacy data from two large academic centers, in New York and Connecticut, were linked to active population-based CDI surveillance data from the Emerging Infections Program (EIP). Adult residents of the EIP surveillance area were included if they had an inpatient stay at a study hospital without prior history of CDI. The primary outcome was CDI by either toxin or molecular assay ≥ 28 days after an index hospitalization. Important predictors of CDI ≥ 28 days post discharge were initially identified through a Cox proportional hazards model (stepwise backward selection) using a derivation cohort; final model parameters were used to develop a risk score evaluated in the validation cohort.

resultsOf the 35,186 index hospitalizations, 288 (0.82%) had CDI ≥ 28 days post discharge. After parameter selection, age, number of hospitalizations in the prior 90 days, admission diagnosis, and the use of 3rd/4th generation cephalosporin, clindamycin or fluoroquinolone antibiotic classes remained in the model. Using the validation cohort, the risk score was predictive (p<0.001) with a c-score of 0.75. Based on the distribution of scores in the derivation cohort, we divided the patients into low and high risk groups. In the high risk group, 1.6% experienced CDI ≥ 28 days post discharge compared to 0.3% among our low risk group.

conclusionsOur study identified specific parameters for a risk score that can be applied at discharge to identify a patient population whose risk of CDI ≥ 28 days following an acute care hospitalization was 5 times greater than other patients.

Indexed as

Clinical Trials as TopicDecision Support TechniquesAdolescentAdultAgedAged, 80 and overBacterial VaccinesClostridioides difficileClostridium InfectionsConnecticutFemaleHospitalsHumansMaleMiddle AgedNew YorkBacterial VaccinesAdministrative dataAnti-bacterial agentsClostridium difficile infectionHealth care-associated infectionsVaccines

Identifiers

PMID26450660
PMCPMC4702247
OpenAlexW1894187162

What OpenQuestion holds

Textmetadata
LicenceTDM
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.