ArticleJournal of parasitology research2014
Evaluation of an immunoassay-based algorithm for screening and identification of giardia and cryptosporidium antigens in human faecal specimens from saudi arabia.
Article in Journal of parasitology research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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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.
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Who cites it
12 citing papers in PubMed, 19 citations in OpenAlex.
- Cryptosporidiosis: A global threat to human and animal health.Open veterinary journal · 2025Review
- Review
- Establishment and preliminary application of nanoparticle-assisted PCR assay for detection of Cryptosporidium spp.Parasitology research · 2021Article
- Review
- Prevalence of Parasitic Infections in Surgically Removed Appendices: Parasitological and Histopathological Studies.Helminthologia · 2018Article
- High Frequency of Enteric Protozoan, Viral, and Bacterial Potential Pathogens in Community-Acquired Acute Diarrheal Episodes: Evidence Based on Results of Luminex Gastrointestinal Pathogen Panel Assay.The Korean journal of parasitology · 2017Article
- Seroprevalence of five parasitic pathogens in pregnant women in ten Caribbean countries.Parasitology research · 2017Article
- Evaluation of a Rapid Lateral Flow Point-of-Care Test for Detection of Cryptosporidium.The American journal of tropical medicine and hygiene · 2016Article
- An Improved PCR-RFLP Assay for Detection and Genotyping of Asymptomatic Giardia lamblia Infection in a Resource-Poor Setting.The Korean journal of parasitology · 2016Article
- Evaluation of ImmunoCard STAT test and ELISA versus light microscopy in diagnosis of giardiasis and cryptosporidiosis.Parasitology research · 2015Article
- Prevalence of Cryptosporidium-associated diarrhea in a high altitude-community of Saudi Arabia detected by conventional and molecular methods.The Korean journal of parasitology · 2014Article
- Antigen-Based Diagnosis of Human Giardiasis: A Systematic Review and Meta-Analysis.Iranian journal of parasitologyReview
Corrections and comments
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Authors and funding
1 author at 1 institution in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
An immunoassay-based algorithm, involving three commercial kits, was introduced and evaluated for screening and identification of Giardia/Cryptosporidium antigens in human stool specimens. Initially, Giardia/Cryptosporidium Chek kit (TechLab), an enzyme-linked immunosorbent assay (ELISA), was adopted for screening. The ELISA-positive reactions were subsequently characterised by RIDA Quick Giardia and RIDA Quick Cryptosporidium immunochromatographic kits (R-Biopharm). A gold standard test comprising PCR and microscopy was used for preparing control samples. Performance of individual kits was tested against these samples which included 50 Giardia-positive, 40 Cryptosporidium-positive, and 70 Cryptosporidium/Giardia-negative. For Cryptosporidium, specificities of the ELISA and RIDA Quick Cryptosporidium kits were 95.71% and 100%, respectively. Both kits demonstrated sensitivity of 95%. For Giardia, the ELISA and RIDA Quick Giardia kits showed sensitivities of 100% and 97.5%, respectively. Specificities obtained by the ELISA and RIDA Quick Giardia were 95.7% and 100%, respectively. Based on the results of two reference PCRs, on 250 random samples, the algorithm exhibited sensitivity, specificity, positive predictive value, and negative predictive value of 97.06%, 100.00%, 100.00%, and 98.91%, respectively. In conclusion, this immunoassay-based algorithm can be used as routine test in diagnostic laboratories for screening and identification of a large number of samples.
Identifiers
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Registered trials
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.