B-262 Validation of a point-of-care lateral flow immunoassay for urine drug testing prior to application in an outpatient rapid access addiction medicine clinic
Bibliographic record
Abstract
Abstract Background Point-of-care (POC) urine drug testing is a useful adjunct to self-reporting in rapid access addiction medicine settings to immediately guide patient management. However, available POC immunoassays have limitations including cross-reactivity with unrelated compounds or low sensitivity that may cause false results. Here, we assessed the performance of a multi-drug test panel by comparing against gold-standard liquid chromatography tandem mass spectrometry (LC-MS/MS) testing. Methods 102 residual urine specimens were assayed using a competitive lateral flow immunoassay (LFA) for 10 drugs: 2-ethylene-1,5-dimethyl-3,3-diphenylpyrrolidine (EDDP, methadone metabolite), buprenorphine, morphine, hydromorphone, oxycodone, fentanyl, cocaine, methamphetamine, amphetamine, and benzodiazepines (BTNX Rapid ResponseTM Multi-Drug Panel). Results were compared to those obtained by LC-MS/MS (n=67, 66%) or kinetic interaction of microparticles in solution automated immunoassay (KIMS) (Roche Diagnostics, n=35, 33%). Broad spectrum LC-MS/MS results were reviewed in entirety for discordant cases, particularly in false positives to identify the presence of any known cross-reacting compounds. Results Of 10 drugs evaluated, four demonstrated ≥95% agreement with LC-MS/MS or KIMS immunoassay (EDDP, buprenorphine, oxycodone, methamphetamine). Fentanyl demonstrated the highest false negative rate of 44% (LFA cut-off: 10 ng/mL) followed by amphetamines (22%, cut-off: 1000 ng/mL). Morphine and hydromorphone demonstrated false positive rates of 14% and 18%, respectively, with most cases likely due to cross-reacting opiate or opioid metabolites. Benzodiazepines (target: Oxazepam) demonstrated false positive and negative rates of 13% and 24%, respectively. Conclusions To our knowledge, this is the first study to evaluate the performance of the BTNX multi-drug test panel against definitive testing in urine samples. While good concordance was observed for most drugs, high rates of discordant results for fentanyl and others emphasize the need for confirmatory testing by methods with higher sensitivity and specificity. Careful consideration prior to implementation would be essential, including physician education, interpretative comments, and training resources.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".