Specimen Processing and Concentration of <i>Chlamydia trachomatis</i> Added Can Influence False-Negative Rates in the LCx Assay but Not in the APTIMA Combo 2 Assay When Testing for Inhibitors
Bibliographic record
Abstract
Inhibitors in clinical specimens can be detected by adding the target of nucleic acid amplification to the sample. Introduction of a Chlamydia trachomatis L2 434 preparation containing 12 elementary bodies (EBs) into first-void urine (FVU) from 225 nonpregnant women and 190 pregnant women before specimen processing by the assays produced false-negative rates of 0.48% (2 of 415 specimens) and 13% (44 of 338 specimens) by the APTIMA Combo 2 and the Chlamydia LCx tests, respectively. Reducing the amount of C. trachomatis added to one EB, a concentration closer to the APTIMA Combo 2 test cutoff, for a subset of 244 FVU specimens increased the number of specimens with false-negative results by the APTIMA Combo 2 assay to 7 (2.9%), suggesting that the strength of the input C. trachomatis per specimen has an influence on the number of specimens with false-negative results. Repeat testing after overnight storage and dilution decreased the APTIMA Combo 2 test false-negative rates to 0% (0 of 415 specimens) with the stronger inoculum and 0.8% (2 of 244 specimens) with the weaker inoculum; the false-negative rate of the LCx assay was reduced to 5.4% (18 of 334 specimens). When an additional 70 FVU specimens from women to which 12 EBs were added before specimen processing were tested by the LCx assay, 34 specimens had false-negative results, whereas 21 specimens had false-negative results when the C. trachomatis EBs were introduced after processing. Nine of the 21 specimens to which EBs were added after processing and all of the 34 urine specimens to which the target was added before processing remained falsely negative on repeat testing at a 1:2 dilution, suggesting that input C. trachomatis DNA was lost during processing by the LCx assay. In contrast, the APTIMA Combo 2 assay appears to have a higher sensitivity and either lost little nucleic acid during processing or demonstrated few problems with inhibitors of transcription-mediated amplification.
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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 | 0.013 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".