Multiplexed rapid technologies for sexually transmitted infections: a systematic review
Bibliographic record
Abstract
Multiplexed technologies for sexually transmitted infections offer a convenient diagnostics option to screen, confirm, and treat multiple pathogens simultaneously. Due to scarce published real-world diagnostic performance data, we did a systematic review. Two reviewers searched major databases for data published between Jan 1, 2009, and April 20, 2020, and abstracted and analysed sensitivity and specificity data from 24 studies, which assessed 17 multiplex rapid nucleic acid amplification test platforms and seven multiplex immunochromatographic devices. Overall, these studies evaluated 19 sexually transmitted infections in 26 126 individuals. High sensitivity and specificity were shown for rapid nucleic acid amplification platform tests and immunochromatographic devices, with performance varying by pathogen, device, seropositivity, and subpopulation screened. As most devices yielded more than 95% sensitivity and specificity, immunochromatographic tests and rapid nucleic acid amplification test platforms can be advised for screening and confirmatory use. These highly accurate devices are appropriate for integrated, rapid screening initiatives for sexually transmitted infections to screen and treat many of these infections simultaneously, for antimicrobial stewardship, and for disease elimination programmes.
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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 | 0.006 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.012 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".