Evaluation and Verification of the Seeplex Diarrhea-V ACE Assay for Simultaneous Detection of Adenovirus, Rotavirus, and Norovirus Genogroups I and II in Clinical Stool Specimens
Bibliographic record
Abstract
Acute viral gastroenteritis is an intestinal infection that can be caused by several different viruses. Here we describe the evaluation and verification of Seeplex Diarrhea-V ACE (Seeplex DV), a novel commercial multiplex reverse transcription-PCR (RT-PCR) assay that detects 5 diarrheal pathogens, including adenovirus, rotavirus, norovirus genogroup I (GI) and GII, and astrovirus. We describe a retrospective study of 200 clinical specimens of which 177 were stool specimens previously tested for the presence of gastrointestinal viruses by electron microscopy (EM) and/or real-time RT-PCR (rRT-PCR). The remaining 23 specimens comprised other human pathogens of viral or bacterial origin. Discordant norovirus GI and GII results were resolved using a commercial kit; discordant adenovirus and rotavirus results were resolved using a home brew multiplex rRT-PCR assay. Diagnostic sensitivities and specificities were calculated before and after discordant analysis. After discordant analysis, estimated diagnostic sensitivities were 100% for adenovirus, rotavirus, and norovirus GI and 97% for norovirus GII. Diagnostic specificities after discordant analysis were 100% for adenovirus, rotavirus, and norovirus GI and 99.4% for norovirus GII. The 95% limits of detection were 31, 10, 2, and 1 genome equivalent per reaction for adenovirus, rotavirus, and norovirus GI and GII, respectively. The results demonstrate that the Seeplex DV assay is sensitive, specific, convenient, and reliable for the simultaneous detection of several viral pathogens directly in specimens from patients with gastroenteritis. Importantly, this novel multiplex PCR assay enabled the identification of viral coinfections in 12 (6.8%) 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 | 0.002 | 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 | 0.000 | 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".