O10.5 Rapid diagnosis of<i>trichomonas vaginalis</i>by testing vaginal swabs in an isothermal helicase-dependent amplivue<sup>®</sup>assay
Bibliographic record
Abstract
Introduction Infections due to Trichomonas vaginalis are treatable. Diagnostic methods such as wet mount microscopy are rapid but insensitive. Culture or traditional molecular assays are more sensitive but lack rapid results. Biohelix (a Quidel company) has created an isothermal, cassette-based, point-of-care molecular amplified test for the diagnosis of T. vaginalis in vaginal samples which can provide a diagnosis in 5 min. The objective was to demonstrate the clinical performance of the AmpliVue® Trichomonas assay on vaginal swabs from women with or without symptoms living in 5 geographical areas of North America. Methods Women attending STD, family planning, colposcopy and OB/GYN clinics were invited to participate using an investigational research board approved consent form. A healthcare worker collected 4 swabs. The first and second swabs were randomised for wet mount and culture (In-Pouch system, Biomed Diagnostics). Cultures were inoculated and read at 2 and 3 days, and wet mount microscopy performed within 1 h of collection. The third was tested in AmpliVue® and the fourth in Aptima TV (ATV; Hologic, Inc), a transcription-mediated amplification assay. AmpliVue® and ATV testing was performed within 48 h. Positives by diagnostic method were compared to each other and agreements with kappa values were calculated between AmpliVue®and ATV. Results A total of 1132 women (373 symptomatic and 759 asymptomatic) were enrolled. Comparing AmpliVue® to culture and wet mount as a patient infected status demonstrated 100% sensitivity, 98.2% specificity and 87.9–100% positive and negative predictive values in patients with or without symptoms. AmpliVue® showed strong overall agreement with ATV (97.5% 0.89 kappa). Conclusion The AmpliVue Trichomonas Assay identified substantially more T. vaginalis infections and yielded accurate results in 45 min for the diagnosis and treatment of Trichomonas vaginalis in symptomatic and asymptomatic patients representing high and low-prevalence clinics. Clinicians can use this information for their clinics. Disclosure of interest statement Dr. Chernesky has received research funding from Quidel.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".