Evaluation of the Bio-Rad BioPlex 2200 Syphilis Multiplex Flow Immunoassay for the Detection of IgM- and IgG-Class Antitreponemal Antibodies
Bibliographic record
Abstract
The laboratory diagnosis of syphilis is based primarily upon serologic findings. Historically, serologic testing for syphilis has relied on assays such as rapid plasma reagin, fluorescent treponemal antibody absorption, Treponema pallidum particle agglutination (TP-PA), and more recently, enzyme immunoassay (EIA). In this study, we evaluated the performance of a novel multiplex flow immunoassay (BioPlex 2200 Syphilis; Bio-Rad Laboratories, Hercules, CA) for the detection of antitreponemal IgG- and IgM-class antibodies. Serum specimens (n = 1,008) submitted for routine treponema-specific antibody testing by syphilis IgM and IgG EIA (Trep-Chek; Phoenix-Biotech, Mississauga, Ontario, Canada) were also analyzed by the BioPlex Syphilis multiplex assay. Specimens showing discordant results were repeat tested, with further discrepancies being arbitrated by TP-PA. Compared directly to the results of EIA, the BioPlex IgG assay demonstrated 98.7% (77/78) sensitivity and 99.4% (916/930) specificity. Compared to the Trep-Chek IgM EIA, the BioPlex IgM assay showed 80% (4/5) sensitivity and 97.9% (652/666) specificity. These results indicate that the BioPlex Syphilis multiplex assay shows similar serological agreement with EIA while allowing for a fully automated random-access platform that provides faster (1.7 h for 100 samples versus 4.5 h by EIA) and higher-throughput (800 samples per 9 h versus 200 samples by EIA) analysis of the syphilis serologic response.
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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 | 0.003 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".