Determination of the performance of a novel diagnostic test for <i>Clostridioides difficile</i> toxins A and B using latent class analysis
Bibliographic record
Abstract
(CD) toxin B gene suffer from suboptimal specificity for CDI due to CD asymptomatic colonization. Enzyme immunoassays (EIAs) that detect the presence of CD toxins are more specific for CDI but suffer from low sensitivity. To address this challenge, assays detecting CD toxins were developed using single-molecule array (SIMOA) technology, which have much lower limits of toxin detection than conventional EIAs. In this study, stool specimens from 708 symptomatic patients were aliquoted for testing by cell cytotoxicity neutralization assay (CCNA), toxigenic culture, NAAT, conventional CD toxin EIA, and SIMOA CD toxin EIAs. Using latent class analysis, we calculated the sensitivity and specificity of each of these diagnostic tests for detecting, separately, the presence of CD bacterium, CD toxin gene, and CD toxin. We estimated that the prevalence of CDI in our cohort was 14% (95% credible interval [CI]: 0.11-0.17). While the specificity of NAAT for detecting the presence of CD toxin was 95% (95% CI: 0.94-0.97), its positive predictive value was poor due to the low prevalence of CDI. The specificity of the conventional CD toxin EIA for CDI was excellent, but the sensitivity was only 48% (95% CI: 0.41-0.55). In comparison, the sensitivities of the SIMOA toxins A and B EIAs were 76% (95% CI: 0.67-0.84) and 77% (95% CI: 0.67-0.84), respectively, while maintaining excellent specificity. We conclude that SIMOA CD toxin EIAs are significantly more sensitive than conventional CD toxin EIAs. IMPORTANCE: (CD) toxin B gene have suboptimal specificity due to the presence of CD asymptomatic colonization, while enzyme immunoassays (EIAs) that detect the toxin itself are much more specific but are limited by low sensitivity. New assays for detecting CD toxins were developed using single-molecule array (SIMOA) technology, which have much lower limits of toxin detection than conventional EIAs, potentially improving the sensitivity of these conventional EIAs while remaining highly specific. In this study, we use latent class analysis to evaluate the sensitivity and specificity of different diagnostic tests for CD, including the novel SIMOA toxin assays, in detecting the different CD targets: the presence of CD bacterium, the presence of CD toxin gene, and the presence of CD toxin.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".