Evidence map›Paper›PMID 36267251›Full record

ArticleOpen forum infectious diseases2022

Polymicrobial Foot Infection Patterns Are Common and Associated With Treatment Failure.

Neal R Barshes, Nicholas J Clark, Deeksha Bidare, J H Dudenhoeffer, Cezarina Mindru, Maria C Rodriguez-Barradas

Abstract read
In one paragraph

Article in Open forum infectious diseases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
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

5 citing papers in PubMed.

  1. Microenvironment shapesiScience · 2026
    Article
  2. Article
  3. Article
  4. Article
  5. Review
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.

Neal R BarshesDivision of Vascular Surgery and Endovascular Therapy, Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas, USA.ORCID https://orcid.org/0000-0003-1019-8930
Nicholas J ClarkSchool of Veterinary Science, School of Veterinary Science, The University of Queensland, Gatton, Queensland, Australia.
Deeksha BidareBaylor College of Medicine, One Baylor Plaza, Houston, Texas, USA.
J H DudenhoefferDepartment of Biology and Biochemistry, University of Houston, Houston, Texas, USA.
Cezarina MindruMichael E. DeBakey Veterans Affairs Medical Center, Houston, Texas, USA.
Maria C Rodriguez-BarradasMichael E. DeBakey Veterans Affairs Medical Center, Houston, Texas, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: That foot infections are predominately polymicrobial has long been recognized, but it is not clear if the various species co-occur randomly or in patterns. We sought nonrandom species co-occurrence patterns that might help better predict prognosis or guide antimicrobial selection. Methods: We analyzed tissue (bone, skin, and other soft tissue), fluid, and swab specimens collected from initial foot infection episodes during a 10-year period using a hospital registry. Nonrandom co-occurrence of microbial species was identified using simple pairwise co-occurrence rates adjusted for multiple comparisons, Markov and conditional random fields, and factor analysis. A historical cohort was used to validate pattern occurrence and identify clinical significance. Results: In total, 156 unique species were identified among the 727 specimens obtained from initial foot infection episodes in 694 patients. Multiple analyses suggested that Conclusions: Several nonrandom microbial co-occurrence patterns are frequently seen in foot infection specimens. One particular pattern with many

Indexed as

diabetic foot ulcerecologicalfoot infectionosteomyelitispolymicrobialspecies co-occurrence

Identifiers

PMID36267251
PMCPMC9578153

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.