Development and Validation of an Internationally-Standardized, High-Resolution Capillary Gel-Based Electrophoresis PCR-Ribotyping Protocol for Clostridium difficile
Bibliographic record
Abstract
PCR-ribotyping has been adopted in many laboratories as the method of choice for C. difficile typing and surveillance. However, issues with the conventional agarose gel-based technique, including inter-laboratory variation and interpretation of banding patterns have impeded progress. The method has recently been adapted to incorporate high-resolution capillary gel-based electrophoresis (CE-ribotyping), so improving discrimination, accuracy and reproducibility. However, reports to date have all represented single-centre studies and inter-laboratory variability has not been formally measured or assessed. Here, we achieved in a multi-centre setting a high level of reproducibility, accuracy and portability associated with a consensus CE-ribotyping protocol. Local databases were built at four participating laboratories using a distributed set of 70 known PCR-ribotypes. A panel of 50 isolates and 60 electronic profiles (blinded and randomized) were distributed to each testing centre for PCR-ribotype identification based on local databases generated using the standard set of 70 PCR-ribotypes, and the performance of the consensus protocol assessed. A maximum standard deviation of only ±3.8bp was recorded in individual fragment sizes, and PCR-ribotypes from 98.2% of anonymised strains were successfully discriminated across four ribotyping centres spanning Europe and North America (98.8% after analysing discrepancies). Consensus CE-ribotyping increases comparability of typing data between centres and thereby facilitates the rapid and accurate transfer of standardized typing data to support future national and international C. difficile surveillance programs.
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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 | 0.030 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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".