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ABSTRACT
Three enzyme immunoassays (EIAs) were evaluated on two platforms each for detecting Cryptosporidium, Giardia, and Campylobacter in stool samples compared to gold standard methods. The Cryptosporidium EIAs run on stool specimens in three preservative media showed 100% agreement with direct fluorescent antibody (DFA) testing and high correlation with the microscopic method. The Giardia EIAs demonstrated 100% sensitivity but only moderate correlation with the microscopic method. The Campylobacter EIAs had 93.5% sensitivity (out of 65 positives) and 100% specificity compared to the culture method.
Automation on a DS2 system for these three EIAs, along with five others, yielded acceptable performance (92.5-100% accuracy) compared to manual methods. The automation saved labor time and improved operational efficiency but may not be cost-effective for low-volume runs due to the labor required for automation not scaling proportionally with sample numbers.
In conclusion, EIAs are preferred for detecting protozoan parasites in stool, with the Cryptosporidium EIA showing potential as a semi-quantitative assay and a reference method. Automation benefits high-throughput laboratories but may not be as advantageous for low-volume laboratories.
IMPORTANCE Enzyme immunoassay (EIA) is a widely used method in clinical laboratories to detect pathogens in stool samples related to diarrhea diseases. This study evaluated the performance of three EIAs for detecting Cryptosporidium, Giardia, and Campylobacter antigens compared to their gold standard methods. The Cryptosporidium EIAs matched the direct fluorescent antibody (DFA) testing and had a high correlation with microscopic findings (99.7%). The Giardia EIAs showed 100% sensitivity but lower specificity (58%) and moderate correlation with microscopic results (87.4%). The Campylobacter EIA had 93.5% sensitivity (n=65 positive samples) with few discrepancies. Automating these three and five other EIAs using a DS2 system (Dynex) yielded good accuracy (92.5-100%) and 100% precision compared to manual methods. While automation saved hands-on time for high-volume assays, it may not be cost-effective for low-volume laboratories.
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