Diagnostic Algorithm Using a Sensitive Broth Culture Method for Detection of <i>Clostridium difficile</i> Toxin from Stool Samples
Bibliographic record
Abstract
BACKGROUND: The two-step glutamate dehydrogenase antigencytotoxicity neutralization assay algorithm has been found to be reliable for the diagnosis of toxigenic Clostridium difficile. However, the high sensitivity of the screening method is compromised by the relative low sensitivity of the second step, the direct cytotoxin neutralization assay (DCNA) using a fecal filtrate. The objective of the present study was to compare the DCNA with an indirect cytotoxin neutralization assay (ICNA). METHODS: For ICNA, the cytotoxin B of C difficile was obtained from a broth culture of the stools and neutralized according to a standard cytotoxin assay using MRC-5 fibroblast cells. RESULTS: A total of 923 stool specimens from adults were tested during a three-month period from June to August 2008. The prevalence of toxigenic C difficile was 13.5%. The sensitivity of the two-step algorithm was 88%. With the ICNA, 12% toxigenic C difficile were detected that were missed by DCNA. CONCLUSIONS: The use of broth for the ICNA is convenient, and results in increased sensitivity of detection of toxigenic C difficile. It can be implemented in routine diagnosis.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".