Evidence map›Paper›PMID 33408740›Full record

SynthesisFrontiers in genetics2020

Methods for Detecting Mycobacterial Mixed Strain Infections-A Systematic Review.

Alexander Stephen Byrne, Alex Goudreau, Nathalie Bissonnette, Isdore Chola Shamputa, Kapil Tahlan

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis in Frontiers in genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.6field-weighted citation impact, top 15% 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

13 citing papers in PubMed, 18 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Culture-independent detection ofFrontiers in veterinary science · 2025
    Article
  5. Article
  6. Article
  7. Article
  8. InvestigatingMicrobiology spectrum · 2023
    Article
  9. Article
  10. Article
  11. Article
  12. Whole Genome Sequencing LinksFrontiers in veterinary science · 2021
    Article
  13. 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 3 institutions in 1 country.

Alexander Stephen ByrneDepartment of Biology, Memorial University of Newfoundland, St. John's, NL, Canada.
Alex GoudreauScience & Health Sciences Librarian, University of New Brunswick, Saint John, NB, Canada.
Nathalie BissonnetteSherbrooke Research and Development Center, Agriculture and Agri-Food Canada, Sherbrooke, QC, Canada.
Isdore Chola ShamputaDepartment of Nursing & Health Sciences, University of New Brunswick, Saint John, NB, Canada.
Kapil TahlanDepartment of Biology, Memorial University of Newfoundland, St. John's, NL, Canada.
Memorial University of Newfoundland · CAUniversity of New Brunswick · CAAgriculture and Agri-Food Canada · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mixed strain infection (MSI) refers to the concurrent infection of a susceptible host with multiple strains of a single pathogenic species. Known to occur in humans and animals, MSIs deserve special consideration when studying transmission dynamics, evolution, and treatment of mycobacterial diseases, notably tuberculosis in humans and paratuberculosis (or Johne's disease) in ruminants. Therefore, a systematic review was conducted to examine how MSIs are defined in the literature, how widespread the phenomenon is across the host species spectrum, and to document common methods used to detect such infections. Our search strategy identified 121 articles reporting MSIs in both humans and animals, the majority (78.5%) of which involved members of the

Indexed as

complexdetectioninfectionsmethodsmixed strainMycobacteriumnon-tuberculoustuberculosis

Identifiers

PMID33408740
PMCPMC7779811
OpenAlexW3116360520

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.