Impact of Strain Type on Detection of Toxigenic <i>Clostridium difficile:</i> Comparison of Molecular Diagnostic and Enzyme Immunoassay Approaches
Bibliographic record
Abstract
A multicenter clinical trial assessed the performance of the Cepheid Xpert C. difficile assay on stool specimens collected from patients suspected of having Clostridium difficile infection (CDI). A total of 2,296 unformed stool specimens, collected from seven study sites, were tested by Xpert C. difficile enrichment culture followed by cell culture cytotoxicity testing of the isolates (i.e., toxigenic culture with enrichment) and the study sites' standard C. difficile test methods. The methods included enzyme immunoassay (EIA), direct cytotoxin testing, and two- and three-step algorithms using glutamate dehydrogenase (GDH) screening followed by either EIA or EIA and an in-house PCR assay. All C. difficile strains were typed by PCR-ribotyping. Compared to results for toxigenic culture with enrichment, the sensitivity, specificity, and positive and negative predictive values of the Xpert assay were 93.5, 94.0, 73.0, and 98.8%, respectively. The overall sensitivity of the EIAs compared to that of enrichment culture was 60.0%, and the sensitivity of combined GDH algorithms was 72.9%; both were significantly lower than that of Xpert C. difficile (P < 0.001 and P = 0.03, respectively). The sensitivity of the EIA was significantly lower than that of the Xpert C. difficile assay for detection of ribotypes 002, 027, and 106 (P < 0.0001, P < 0.0001, and P = 0.004, respectively, Fisher's exact test), and the sensitivity of GDH algorithms for ribotypes other than 027 was lower than that for Xpert C. difficile (P < 0.001). The Xpert C. difficile assay is a simple, rapid, and accurate method for detection of toxigenic C. difficile in unformed stool specimens and is minimally affected by strain type compared to EIA and GDH-based methods.
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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 | 0.018 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".