Impact of Urine Collection Order on the Ability of Assays to Identify Chlamydia trachomatis Infections in Men
Bibliographic record
Abstract
In Brief Background Noninvasive urine samples have been used to diagnose Chlamydia trachomatis infections, with the assumption that the first-void urine (FVU), defined as the first 20 to 30 ml at any micturition, would be the optimal collection. We compared testing technologies on first, second, and third volumes for diagnosis. Goal The goal was to test in nonculture assays three sequential volumes of urine from men also undergoing urethral swabbing for C trachomatis culture specimens. Study Design A total of 237 men attending an STD clinic (C trachomatis prevalence, 11%) collected three containers of urine (each containing 20–30 mL) for testing in four nonculture assays. A urethral swab specimen was tested in cell culture. Results The numbers of men positive by testing of FVU with nucleic acid amplification (LCx chlamydia), nucleic acid hybridization (PACE 2), enzyme immunoassay (Chlamydiazyme), and a leukocyte esterase dipstick were 26, 7, 14, and 11, respectively; urethral culture identified 6 of the infected men. Comparative testing of all voids from the 26 men positive by the FVU assays demonstrated a reduction of LCx-positives. Non-amplified-test positivity declined precipitously in subsequent voids, approaching zero in the third void. The presence of symptoms and time of last void up to 8 hours had little effect on the number of positives detected by LCx of FVU. Conclusion Amplified testing of FVU was most effective for diagnosing infection in these men. LCx testing of three sequential voids of urine found that more than twice as many were positive for C trachomatis than when nonamplified testing was performed, and 23% of the first void LCx positives were negative in the subsequent voids. Symptom or time since last void had little impact when amplified testing was performed on FVUs.
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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 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".