B-288 Turning False Positive Screening into True Positive Results
Bibliographic record
Abstract
Abstract Background After conducting a retrospective analysis of our laboratory data, we identified a notable disparity between immunoassay screen and mass spectrometry confirmation results for benzodiazepines. This prompted an investigation into whether the prevalence of false negative benzodiazepine results stemmed from the inadequacy of the immunoassay or the absence of new psychoactive substances (NPS) in our mass spectrometry confirmation assay. To determine the latter, we added four NPS benzodiazepines and their metabolites to our confirmation panel. Monitoring drug seizure records as well as reports detailing emerging substances were helpful in guiding which NPS to add. The objective of this study was to determine whether the addition of NPS benzodiazepines to our confirmation panel would increase the agreement between screen and confirmation benzodiazepine results in an opioid dependent population. Methods Urine samples that screened positive for benzodiazepines with immunoassay and confirmed negative by mass spectrometry over a 6-month timeframe were selected for analysis. Four NPS were added to our confirmation panel which included bromazolam, flubromazepam, flubromazolam, flualprazolam as well as their metabolites alpha-OH bromazolam, 3-OH flubromazepam, alpha-OH flubromazolam and alpha-OH flualprazolam. Immunoassay data was obtained using an Olympus AU480 instrument, while mass spectrometry results were acquired through an internally developed dynamic multiple reaction monitoring method on an Agilent 6470 triple quadrupole instrument. Results In the analysis of 476 urine samples using a cut-off value of 50 ng/mL, 55.3% of the samples tested positive for bromazolam, 83.0% for alpha-OH bromazolam, 0% for flubromazepam, 41.8% for 3-OH flubromazepam, 0% for flubromazolam, 0.2% for alpha-OH flubromazolam, 1.3% for flualprazolam and 6.7% for alpha-OH flualprazolam. Using a cut-off value of 10 ng/mL which represents the limit of quantitation, 75.4% tested positive for bromazolam, 89.9% for alpha-OH bromazolam, 2.1% for flubromazepam, 60.5% for 3-OH flubromazepam, 0% for flubromazolam, 0.2% for alpha-OH flubromazolam, 3.4% for flualprazolam and 9.7% for alpha-OH flualprazolam. In total, among the 476 samples that initially screened positive but confirmed negative, 95.8% confirmed positive for benzodiazepines with the inclusion of the four NPS benzodiazepines and their metabolites into our confirmation panel. Of the samples that tested positive for NPS benzodiazepines, 77.1% were also positive for fentanyl, and 95.2% were positive for norfentanyl. Conclusions The incorporation of NPS benzodiazepines into our confirmation panel significantly enhanced the concordance between immunoassay screen and mass spectrometry confirmation results. The discrepancies we observed with benzodiazepines were not predominantly linked to immunoassay challenges. Rather, they were due to the presence of NPS benzodiazepines commonly found in benzo-dope preparations, not accounted for in our mass spectrometry confirmation panel. The inclusion of NPS benzodiazepines into our confirmation panel has improved the reporting of useful diagnostic information which can be used to support harm reduction efforts.
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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 | 0.011 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".