Yield of Stool Culture with Isolate Toxin Testing versus a Two-Step Algorithm Including Stool Toxin Testing for Detection of Toxigenic <i>Clostridium difficile</i>
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Bibliographic record
Abstract
We examined the incremental yield of stool culture (with toxin testing on isolates) versus our two-step algorithm for optimal detection of toxigenic Clostridium difficile. Per the two-step algorithm, stools were screened for C. difficile-associated glutamate dehydrogenase (GDH) antigen and, if positive, tested for toxin by a direct (stool) cell culture cytotoxicity neutralization assay (CCNA). In parallel, stools were cultured for C. difficile and tested for toxin by both indirect (isolate) CCNA and conventional PCR if the direct CCNA was negative. The "gold standard" for toxigenic C. difficile was detection of C. difficile by the GDH screen or by culture and toxin production by direct or indirect CCNA. We tested 439 specimens from 439 patients. GDH screening detected all culture-positive specimens. The sensitivity of the two-step algorithm was 77% (95% confidence interval [CI], 70 to 84%), and that of culture was 87% (95% CI, 80 to 92%). PCR results correlated completely with those of CCNA testing on isolates (29/29 positive and 32/32 negative, respectively). We conclude that GDH is an excellent screening test and that culture with isolate CCNA testing detects an additional 23% of toxigenic C. difficile missed by direct CCNA. Since culture is tedious and also detects nontoxigenic C. difficile, we conclude that culture is most useful (i) when the direct CCNA is negative but a high clinical suspicion of toxigenic C. difficile remains, (ii) in the evaluation of new diagnostic tests for toxigenic C. difficile (where the best reference standard is essential), and (iii) in epidemiologic studies (where the availability of an isolate allows for strain typing and antimicrobial susceptibility testing).
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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 it