Screening for <i>Giardia</i> / <i>Cryptosporidium</i> Infections Using an Enzyme Immunoassay in a Centralized Regional Microbiology Laboratory
Bibliographic record
Abstract
CONTEXT: Stool parasitologic testing for Giardia and Cryptosporidium (G/C) previously relied on staining (ie, modified iron hematoxylin-kinyoun), ethyl acetate concentration procedures, and microscopy (the stool ova and parasite method). In April 1999, a microplate enzyme immunoassay (EIA) (ProSpecT G/C, Remel, Inc, Lenexa, Kan) for routine screening of all stool specimens was implemented. OBJECTIVE: To determine the clinical and laboratory impact of this service change. DESIGN: Changes were made to the regional microbiology requisition so that physicians could order either a G/ C EIA screen or stool ova and parasite examination. During a 3-year period (May 1999 through April 2002), changes in physician ordering practice, the rate of detection of G/ C infections, and test turnaround times were monitored. The economic outcomes have also been studied and compared annually since implementation and up to the current fiscal year (2004). RESULTS: The following effects have been noted since G/ C EIA screening was implemented: (1) 70% of all stool parasite tests ordered were converted to G/C EIA screens versus stool ova and parasite tests, (2) stool parasitologic volumes decreased by up to 30% because of physicians ordering a single test per patient, (3) most stool parasite results (70%-80%) were reported within 24 hours of specimen receipt, and (4) the screening assay has improved detection of cryptosporidiosis cases. Although the G/C EIA tests cost more than stool ova and parasite examination, the equivalent of 1.8 full-time employees have been freed up to perform other duties. CONCLUSIONS: Routine stool G/C EIA screening in our region is not only clinically relevant but also improves the timeliness and efficiency of detection of these important enteric parasite infections.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".