Direct fluorescence antibody testing augments syphilis diagnosis, compared to serology alone
Bibliographic record
Abstract
In Ottawa, Canada, we initiated protocols to include non-serologic syphilis testing, as direct fluorescence antibody (DFA) for patients with syphilis symptoms. The purpose was to assess the ability of DFA to detect syphilis during acute infection and to determine if non-serologic testing could yield an increased number of syphilis diagnoses. We reviewed charts of patients of our local sexual health clinic for whom syphilis was suspected. A total of 69 clinical encounters were recorded for 67 unique patients, most of whom were male. The most common symptom was a painless genital lesion. Of the 67 patients, 29 were found to have a new syphilis diagnosis, among whom, 52% had positive syphilis serology and positive DFA, 34% had a positive syphilis serology and negative DFA, and 14% had negative syphilis serology and positive DFA. While DFA testing did not yield an abundance of new cases, it was useful to support findings from syphilis serology or confirm diagnosis where serology was negative. Where available, alternate non-serologic tests, such as nucleic acid amplification tests, should be considered above DFA due to its higher sensitivity for detecting syphilis in primary lesions; however, in clinical situations, when new syphilis infection is suspected, empiric treatment should not be delayed.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".