Validation of a Commercial Enzyme Immunoassay for Detection of <i>Clostridium difficile</i> Toxins in Feces of Horses with Acute Diarrhea
Bibliographic record
Abstract
BACKGROUND: Clostridium difficile infection (CDI) is a recognized cause of colitis in the horse. Identification of its toxins is important for management of individual cases and for prevention of transmission and zoonosis. In humans, CDI diagnosis is performed with enzyme immunoassays, none of which have been validated for horses. HYPOTHESIS/OBJECTIVES: (1) Establish which test for CDI diagnosis was more frequently used by diagnostic laboratories, (2) determine the identified test's performance, sensitivity, and specificity, and (3) validate its use in diarrheic horses. ANIMALS: Samples were obtained from 72 horses presented with acute diarrhea and hospitalized at the Ontario Veterinary College, University of Guelph. METHODS: A survey was conducted to establish which of the tests for CDI diagnosis in horses is most commonly used throughout North America. A questionnaire was sent to all laboratories registered in the Veterinary Infection Control Society and the American Association of Veterinary Laboratory Diagnosticians. The performance of the test was evaluated by comparison to a cell cytotoxicity assay (CTA), the accepted Gold Standard for C. difficile toxin detection. RESULTS: The Techlab C. difficile Tox A/B II ELISA was the most frequently used test. Compared with the CTA, no significant difference was observed, and a good level of agreement (93%) was obtained. The diagnostic performance of the ELISA test was adequate (84% sensitivity and 96% specificity). CONCLUSIONS AND CLINICAL IMPORTANCE: Results demonstrate that the Techlab C. difficile Tox A/B II ELISA is a reliable, adequate, and practical tool for identification of C. difficile toxins in horse feces.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".