Clostridioides difficile PCR Tcdb Cycle Threshold predicts toxin EIA positivity but not severity of infection
Bibliographic record
Abstract
Background Diagnosis of Clostridioides difficile Infection (CDI) entails compatible clinical presentation and laboratory findings. We evaluated real-time polymerase chain reaction (qPCR) cycle threshold (C T ) as a predictor for disease severity and TcdB enzyme immunoassay (EIA) results. Methods Inpatients or emergency department patients who tested positive for tcdB gene by PCR were evaluated. Patients’ stools underwent testing for GDH and TcdA/B by EIA. Medical health records were reviewed for demographic, clinical presentation, laboratory, treatment and outcome data. Severity of CDI was calculated using various severity score indexes. Results The median C T of cases was 32.05 ± 5.45. The optimal cut-off for predicting toxin EIA positivity and severe CDI based on chart review was 32.6 and 29.8, respectively, with the area under the receiver operator characteristics curve (AUC) of 0.74 and 0.60 respectively. Conclusion C T value was an acceptable predictor for EIA toxin but less so for clinical severity. Our study potentially supports a diagnostic algorithm including C T value to reduce the number of EIA toxin assays performed.
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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 | 0.001 | 0.005 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".