Comparison of Assays for the Diagnosis of Mycoplasma genitalium and Macrolide Resistance Mutations in Self-Collected Vaginal Swabs and Urine
Bibliographic record
Abstract
BACKGROUND: The objective was to compare commercial assays on clinical specimens for Mycoplasma genitalium (MG) detection and macrolide resistance mutation (MRM) frequency. METHODS: Three self-collected vaginal swabs (VS) and a first-void urine (FVU) from 300 consented women were tested by Aptima MG (AMG), ResistancePlus MG (RPMG) and Seeplex STD6 ACE (STD6) for detection of MG. Aptima MG and STD6 MG positives were tested for MRM using MG 23S rRNA polymerase chain reaction with Sanger sequencing (23SMGSS) compared with MRM determination in the RPMG assay. Unique AMG positives were tested with confirmatory Aptima assays. RESULTS: M. genitalium prevalence ranged from 7.1% to 19.7%, influenced by the assay used and the specimen tested. Overall agreements for MG detection were 96.3% (κ = 0.91) for VS and 93.3% (κ = 0.72) for FVU between AMG and RPMG with lower agreements with STD6. Using a rotating reference standard, sensitivities on VS and FVU were 100% and 100% for AMG, 100% and 83.3% for RPMG, and 54.2% and 48.4% for STD6. Specificities were high for RPMG and STD6 and AMG detected extra positives, most of which were confirmed. Macrolide resistance mutation frequency rates testing VS and FVU were 50% (24/48) and 58.1% (18/31) by RPMG compared with 52.5% (31/59) and 23.5% (12/51) by 23SMGSS. MRM overall agreements between RPMG and 23SMGSS were 73.2% (κ = 0.41) for VS and 76.0% (κ = 0.52) for FVU. CONCLUSIONS: Aptima MG detected more cases of MG infections. ResistancePlus MG detection was more effective on VS than on FVU. Seeplex STD6 ACE performance was inferior. The MRM detection component of RPMG agreed with results from 23SMGSS most of the time.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".