Canadian Public Health Laboratory Network guidelines for the use of point-of-care tests for <i>Treponema pallidum</i> in Canada
Bibliographic record
Abstract
Over the past few years, the increase in infectious syphilis outbreaks in major urban centres and remote or rural locations in Canada, often affecting hard-to-reach patient populations, has renewed an interest and urgency in studying the use of point-of-care tests (POCTs) that can provide test results at the time and place of primary health care delivery, obviating the repeat visit necessary with traditional syphilis serology or molecular diagnostic tests. In 2015, the Canadian Public Health Laboratory Network released its first laboratory guideline for the use of POCTs in the diagnosis of syphilis in Canada. Although Canada has no licensed POCT, two POCTs (Syphilis Health Check and the DPP® HIV Syphilis System) have received US Food and Drug Administration (FDA) approval under premarket approval applications. Most syphilis POCTs detect antibodies to treponemal antigens, so their results cannot be used to differentiate between active and past infection. The only POCT that detects antibodies to both treponemal and non-treponemal antigens does not yet have Health Canada or FDA approval. In this updated guideline, the current landscape of POCTs for syphilis, with an emphasis on data from low-prevalence countries, is described. Individual operators should consider the questions of where, when, how, and why a POCT is used before its actual implementation. Training in the operation and interpretation, quality control, proficiency program, safety, and careful documentation of the process and results are especially important for the successful implementation of POCTs.
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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 | 0.014 | 0.050 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.008 | 0.002 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.019 | 0.009 |
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".