SynthesisViruses2022
Point-of-Care Tests for Rapid Detection of Porcine Epidemic Diarrhea Virus: A Systematic Review and Meta-Analysis.
Synthesis in Viruses, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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.
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.
Who cites it
5 citing papers in PubMed, 6 citations in OpenAlex.
- Development of a High-Resolution Melting (HRM)-Based Multiplex Real-Time PCR Assay of PEDV, TGEV, PoRV, PDCoV, PRV, and PRRSV.Transboundary and emerging diseases · 2026Article
- Advances and emerging technologies in the diagnosis of viral infections in pigs: Progress, challenges, and One Health perspectives.Veterinary world · 2025Review
- Advances in porcine epidemic diarrhea virus research: genome, epidemiology, vaccines, and detection methods.Discover nano · 2025Review
- Antiviral activity of chrysin and naringenin against porcine epidemic diarrhea virus infection.Frontiers in veterinary science · 2023Article
- Development of Duplex LAMP Technique for Detection of Porcine Epidemic Diarrhea Virus (PEDV) and Porcine Circovirus Type 2 (PCV 2).Current issues in molecular biology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The timely and accurate diagnosis of porcine epidemic diarrhea virus (PEDV) infection is crucial to reduce the risk of viral transmission. Therefore, the objective of this review was to evaluate the overall diagnostic accuracy of rapid point-of-care tests (POCTs) for PEDV. Studies published before 7 January 2022 were identified by searching PubMed, EMBASE, Springer Link, and Web of Science databases, using subject headings or keywords related to point of care and rapid test diagnostic for PEDV and PED. Two investigators independently extracted data, rated risk of bias, and assessed the quality using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. The bivariate model and the hierarchical summary receiver operating characteristic (HSROC) model were used for performing the meta-analysis. Threshold effect, subgroup analysis, and meta-regression were applied to explore heterogeneity. Of the 2908 records identified, 24 eligible studies involving 3264 specimens were enrolled in the meta-analysis, including 11 studies on evaluation of lateral flow immunochromatography assay (ICA)-based, and 13 on nucleic acid isothermal amplification (NAIA)-based POCTs. The overall pooled sensitivity, specificity and diagnostic odds ratio (DOR) were 0.95 (95% CI: 0.92-0.97), 0.96 (95% CI 0.88-0.99) and 480 (95% CI 111-2074), respectively; for ICA-based POCTs and the corresponding values for NAIA-based, POCTs were 0.97 (95% CI 0.94-0.99), 0.98 (95% CI 0.91-0.99) and 1517 (95% CI 290-7943), respectively. The two tests showed highly comparable and satisfactory diagnostic performance in clinical utility. These results support current recommendations for the use of rapid POC tests when PEDV is suspected.
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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.