Use of Oral Fluid in a Rapid Syphilis Test Assay
Bibliographic record
Abstract
Abstract Background From 2014 to 2015, the syphilis rate in the United States increased by 19%, reaching its highest rate since 1994. Currently, point-of-care syphilis assays use fingerstick or venipuncture whole blood to identify Treponema pallidum (TP) antibodies by qualitative immunoassay. However, patients and providers prefer oral fluid testing to whole blood testing. In this study, we aimed to determine whether a rapid syphilis test intended for use on whole blood could be used to detect TP antibodies in oral fluid. Methods Oral fluid was collected from 72 participants using the Super•SAL™ Oral Fluid Collection Device (Oasis Diagnostics®, Vancouver, WA). The device uses an absorbent cylindrical pad to collect and filter ~1 mlml of oral fluid. Oral fluid filtrate was tested using the SD Bioline Syphilis 3.0 rapid test (Alere Diagnostics, MA) following manufacturer directions for whole blood. TP particle agglutination (TPPA) and rapid plasma reagin (RPR) results derived from participants’ medical records were used as reference values. We used three different definitions as comparators: 1: TPPA reactive; 2: TPPA and RPR reactive and 3: TPPA reactive and RPR titer >1:4. Those with non-reactive TPPA and RPR results were considered seronegative. We calculated the sensitivity and specificity for definition 1 and sensitivity for definitions 2 and 3. We used the exact binomial method to determine 95% confidence intervals (CI). Results With definitions 1, 2, and 3, respectively, sensitivity was 83.3% (CI: 67.2, 93.6), 86.4% (CI: 65.1, 97.1), and 100% (CI: 71.5, 100). Specificity was 47.2% (CI: 36.5, 75.5). Conclusion The high sensitivity of the SD Bioline Syphilis 3.0 test using oral fluid suggests a strong potential for the development of accurate rapid oral syphilis tests. Sensitivity increased with higher RPR titer. False positive results may be due to the presence of non-venereal treponemal antibodies in oral fluid. Further research and development are needed to optimize specificity. Disclosures All authors: No reported disclosures.
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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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".