Multicenter Evaluation of the BD Max Enteric Bacterial Panel PCR Assay for Rapid Detection of Salmonella spp., Shigella spp., Campylobacter spp. (C. jejuni and C. coli), and Shiga Toxin 1 and 2 Genes
Bibliographic record
Abstract
Diarrhea due to enteric bacterial pathogens causes significant morbidity and mortality in the United States and worldwide. However, bacterial pathogens may be infrequently identified. Currently, culture and enzyme immunoassays (EIAs) are the primary methods used by clinical laboratories to detect enteric bacterial pathogens. We conducted a multicenter evaluation of the BD Max enteric bacterial panel (EBP) PCR assay in comparison to culture for the detection of Salmonella spp., Shigella spp., Campylobacter jejuni, and Campylobacter coli and an EIA for Shiga toxins 1 and 2. A total of 4,242 preserved or unpreserved stool specimens, including 3,457 specimens collected prospectively and 785 frozen, retrospective samples, were evaluated. Compared to culture or EIA, the positive percent agreement (PPA) and negative percent agreement (NPA) values for the BD Max EBP assay for all specimens combined were as follows: 97.1% and 99.2% for Salmonella spp., 99.1% and 99.7% for Shigella spp., 97.2% and 98.4% for C. jejuni and C. coli, and 97.4% and 99.3% for Shiga toxins, respectively. Discrepant results for prospective samples were resolved with alternate PCR assays and bidirectional sequencing of amplicons. Following discrepant analysis, PPA and NPA values were as follows: 97.3% and 99.8% for Salmonella spp., 99.2% and 100% for Shigella spp., 97.5% and 99.0% for C. jejuni and C. coli, and 100% and 99.7% for Shiga toxins, respectively. No differences in detection were observed for samples preserved in Cary-Blair medium and unpreserved samples. In this large, multicenter study, the BD Max EBP assay showed superior sensitivity compared to conventional methods and excellent specificity for the detection of enteric bacterial pathogens in stool specimens.
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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 | 0.013 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".