A Dual Point-of-Care Test Shows Good Performance in Simultaneously Detecting Nontreponemal and Treponemal Antibodies in Patients With Syphilis: A Multisite Evaluation Study in China
Bibliographic record
Abstract
BACKGROUND: Rapid point-of-care (POC) syphilis tests based on simultaneous detection of treponemal and nontreponemal antibodies (dual POC tests) offer the opportunity to increase coverage of syphilis screening and treatment. This study aimed to conduct a multisite performance evaluation of a dual POC syphilis test in China. METHODS: Participants were recruited from patients at sexually transmitted infection clinics and high-risk groups in outreach settings in 6 sites in China. Three kinds of specimens (whole blood [WB], fingerprick blood [FB], and blood plasma [BP]) were used for evaluating sensitivity and specificity of the Dual Path Platform (DPP) Syphilis Screen and Confirm test using its treponemal and nontreponemal lines to compare Treponema pallidum particle agglutination (TPPA) assay and toluidine red unheated serum test (TRUST) as reference standards. RESULTS: A total of 3134 specimens (WB 1323, FB 488, and BP 1323) from 1323 individuals were collected. The sensitivities as compared with TPPA were 96.7% for WB, 96.4% for FB, and 94.6% for BP, and the specificities were 99.3%, 99.1%, and 99.6%, respectively. The sensitivities as compared with TRUST were 87.2% for WB, 85.8% for FB, and 88.4% for BP, and the specificities were 94.4%, 96.1%, and 95.0%, respectively. For specimens with a TRUST titer of 1:4 or higher, the sensitivities were 100.0% for WB, 97.8% for FB, and 99.6% for BP. CONCLUSIONS: DPP test shows good sensitivity and specificity in detecting treponemal and nontreponemal antibodies in 3 kinds of specimens. It is hoped that this assay can be considered as an alternative in the diagnosis of syphilis, particularly in resource-limited areas.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".