Prevalence of Clostridium difficile and Salmonella, and validation of an immunoassay for Clostridium difficile toxin detection in horses
Bibliographic record
Abstract
Typhlocolitis in the horse is an important cause of morbidity and mortality. Specific etiologic agents that cause typhlocolitis have been described. Two pathogenic bacteria, which are common causes of equine enteritis, are 'Clostridium difficile' and 'Salmonella enterica '. Clinical presentations of 'C. difficile' infection and salmonellosis are indistinguishable from one another and from other infectious and non-infectious causes of typhlocolitis. This study determined the prevalence of these two bacteria, demonstrated the Techlab® ' C. DIFFICILE' TOX A/B II ELISA as the most frequently used diagnostic test throughout North America and validated its use in horses. Fecal samples were collected to assess the apparent prevalence of ' Clostridium difficile' and 'Salmonella' spp. shedding in racehorses at 4 racetracks and 2 breeding farms, and among horses admitted to a referral clinic in Ontario. PCR-ribotyping and toxin gene profiling were performed on the isolated strains of 'C. difficile'. A ' C. difficile' prevalence of 7.6% and a 'Salmonella' spp, prevalence of 0.2% was estimated on racetrack horses. A 'C. difficile ' prevalence of 5.8% was established for breeding farm horses and of 4.9% for horses admitted to the referral clinic; these were all negative for 'Salmonella' spp. An overall prevalence of 7.0% for ' C. difficile' and 0.14% for 'Salmonella' spp. was found in 742 fecal samples. Seventeen different PCR-ribotypes of 'C. difficile ' were identified. A survey conducted to establish winch of the diagnostic tests available for 'C. difficile' infection in horses is most commonly used throughout North America identified the Techlab® ' C. DIFFICILE' TOX A/B II ELISA. The test was validated against the Gold Standard for 'C. difficile' toxin detection, a cell cytotoxicity inhibition assay. No significant difference between tests was observed and a high level of agreement was obtained. The diagnostic performance of the ELISA test was adequate (84% sensitivity and 96% specificity) and the use of this test may now be recommended.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".