Evidence map›Paper›PMID 25662435›Full record

ArticleExperimental parasitology

Comparison of diagnostic techniques for the detection of Cryptosporidium oocysts in animal samples.

Marzieh Ezzaty Mirhashemi, Annetta Zintl, Tim Grant, Frances E Lucy, Grace Mulcahy, Theo De Waal

Open access · greenAbstract readComparative Study
In one paragraph

Article in Experimental parasitology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
3.5field-weighted citation impact, top 8% 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

22 citing papers in PubMed, 50 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Prevalence and risk factors ofVeterinarni medicina · 2025
    Article
  5. Article
  6. Article
  7. Review
  8. Rapid detection ofHeliyon · 2023
    Article
  9. Diagnosis and control of cryptosporidiosis in farm animals.Journal of parasitic diseases : official organ of the Indian Society for Parasitology · 2022
    Review
  10. Article
  11. Apicomplexans in Goat: Prevalence ofAnimals : an open access journal from MDPI · 2022
    Article
  12. Article
  13. Article
  14. A comparison of assays for the detection ofJournal of veterinary diagnostic investigation : official publication of the American Association of Veterinary Laboratory Diagnosticians, Inc · 2022
    Article
  15. Article
  16. Review
  17. Cryptosporidium-associated diarrhoea in neonatal calves in Algeria.Veterinary parasitology, regional studies and reports · 2018
    Article
  18. Article
  19. 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

6 authors at 2 institutions in 1 country.

Marzieh Ezzaty MirhashemiSchool of Veterinary Medicine, University College Dublin, Belfield, Dublin 4, Ireland; School of Public Health and Population Science, University College Dublin, Belfield, Dublin 4, Ireland. Electronic address: marzieh.mirhashemi@tufts.edu.
Annetta ZintlSchool of Veterinary Medicine, University College Dublin, Belfield, Dublin 4, Ireland.
Tim GrantSchool of Public Health and Population Science, University College Dublin, Belfield, Dublin 4, Ireland.
Frances E LucyCentre for Environmental Research Innovation and Sustainability (CERIS), Institute of Technology, Sligo, Ireland.
Grace MulcahySchool of Veterinary Medicine, University College Dublin, Belfield, Dublin 4, Ireland.
Theo De WaalSchool of Veterinary Medicine, University College Dublin, Belfield, Dublin 4, Ireland.
University College Dublin · IEInstitute of Technology Sligo · IE

Funding

Tufts Clinical and Translational Research InstituteUL1TR001064 · NCATS · TUFTS UNIVERSITY BOSTON · PI SELKER, HARRY P. · 2013 to 2017
$26.4M
NCATS NIH HHS UL1 TR001064
6 · The paper itself

Abstract

While a large number of laboratory methods for the detection of Cryptosporidium oocysts in faecal samples are now available, their efficacy for identifying asymptomatic cases of cryptosporidiosis is poorly understood. This study was carried out to determine a reliable screening test for epidemiological studies in livestock. In addition, three molecular tests were compared to identify Cryptosporidium species responsible for the infection in cattle, sheep and horses. A variety of diagnostic tests including microscopic (Kinyoun's staining), immunological (Direct Fluorescence Antibody tests or DFAT), enzyme-linked immunosorbent assay (ELISA), and molecular methods (nested PCR) were compared to assess their ability to detect Cryptosporidium in cattle, horse and sheep faecal samples. The results indicate that the sensitivity and specificity of each test is highly dependent on the input samples; while Kinyoun's and DFAT proved to be reliable screening tools for cattle samples, DFAT and PCR analysis (targeted at the 18S rRNA gene fragment) were more sensitive for screening sheep and horse samples. Finally different PCR primer sets targetedat the same region resulted in the preferential amplification of certain Cryptosporidium species when multiple species were present in the sample. Therefore, for identification of Cryptosporidium spp. in the event of asymptomatic cryptosporidiosis, the combination of different 18S rRNA nested PCR primer sets is recommended for further epidemiological applications and also tracking the sources of infection.

Indexed as

AnimalsBase SequenceCattleCattle DiseasesCryptosporidiosisCryptosporidiumDNA, ProtozoanEnzyme-Linked Immunosorbent AssayFecesFluorescent Antibody Technique, DirectHorse DiseasesHorsesMass ScreeningOocystsPolymerase Chain ReactionRNA, Ribosomal, 18SDNA, ProtozoanRNA, Ribosomal, 18SCattleCryptosporidiumDiagnostic techniquesHorseLatent class analysisMolecular methodsSheep

Identifiers

PMID25662435
PMCPMC4406248
OpenAlexW2029501770

What OpenQuestion holds

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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.