Evidence map›Paper›PMID 32928850›Full record

ArticleBMJ open2020

Discordant

Lauriane Lenggenhager, Marie-Céline Zanella, Antoine Poncet, Laurent Kaiser, Jacques Schrenzel

Open access · goldAbstract read
In one paragraph

Article in BMJ open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
0.1field-weighted citation impact, top 53% 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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Potential underreporting of treated patients using aInfection control and hospital epidemiology · 2024
    Observational
  4. 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 1 institution in 1 country.

Lauriane Lenggenhager *Division of Infectious Diseases, Geneva University Hospitals, Geneve, Switzerland.ORCID 0000-0001-8669-643X
Marie-Céline Zanella *Division of Infectious Diseases, Geneva University Hospitals, Geneve, Switzerland marie-celine.zanella@hcuge.ch.ORCID 0000-0001-9544-1295
Antoine PoncetDivision of Clinical Epidemiology, Geneva University Hospitals, Geneve, Switzerland.ORCID 0000-0003-0998-853X
Laurent KaiserDivision of Infectious Diseases, Geneva University Hospitals, Geneve, Switzerland.ORCID 0000-0002-0857-2252
Jacques SchrenzelDivision of Infectious Diseases, Geneva University Hospitals, Geneve, Switzerland.ORCID 0000-0001-5464-7764
University of Geneva · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo determine the proportion of patients who received a treatment for

designCross-sectional study.

settingMonocentric study in a tertiary care hospital, Geneva, Switzerland.

participantsAmong 4562 adult patients tested for

main outcome measuresTreatment for CDI.

resultsCDI treatment was administered in 147 (71%) cases. In multivariate analysis, an abdominal CT scan with signs of colitis (OR 14.7; 95% CI 1.96 to 110.8) was the only factor associated with CDI treatment.

conclusionsThe proportion of NAAT+/EIA- patients who received treatment questions the contribution of the EIA for the detection of toxin A/B after NAAT to limit overtreatment. Additional studies are needed to investigate if other factors are associated with the decision to treat.

Indexed as

Bacterial ToxinsClostridioides difficileClostridium InfectionsAdultClostridioidesCross-Sectional StudiesHumansSwitzerlandTertiary Care CentersBacterial Toxinsdiagnostic microbiologygastrointestinal infectionsmicrobiology

Identifiers

PMID32928850
PMCPMC7488797
OpenAlexW3085719623

What OpenQuestion holds

Textmetadata
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.