Direct LC-MS/MS and indirect GC–MS/MS methods for measuring urinary bisphenol A concentrations are comparable
Bibliographic record
Abstract
BACKGROUND: Bisphenol A (BPA) is typically measured in urine using an indirect method that involves enzymatic deconjugation and extraction. In contrast, the direct method measures free and conjugated BPA concurrently and sums them to estimate urinary BPA concentrations. Statistical comparison of total BPA results using the direct and indirect methods is necessary to accurately interpret biomonitoring data for risk assessments. OBJECTIVES: To compare urinary BPA concentrations estimated from the indirect and direct methods in duplicate first trimester urine samples collected from 1879 pregnant women from the MIREC Study. METHODS: For the indirect method, we measured urinary BPA concentrations using GC-MS/MS. For the direct method, we summed free and conjugated BPA concentrations measured using LC-MS/MS. We evaluated deviation between the two methods using the Bland-Altman analysis in the total sample and stratified (1) by specific gravity and (2) at the limit of quantification (LOQ). RESULTS: Median urinary BPA concentrations for the direct and indirect methods were 0.89 µg BPA equivalents/L and 0.81 µg/L respectively. Concentrations from the direct method were, on average, 8.6% (95% CI: 6.7%, 10.5%) higher than the indirect method in a Bland-Altman analysis. The percent differences between the two methods was 4.0% in urines with specific gravities < 1.02 (n = 1348, 72%) and 20.3% in urine with specific gravity ≥ 1.02. In values below the LOQ (n = 663, 35%), we observed smaller average percent deviation (4.8%) between the two methods but wider limits of agreement. DISCUSSION: Results from this study, based on the largest statistically rigorous comparison of the direct and indirect methods of BPA measurement, contrast previous findings reporting that the indirect method underestimates total BPA exposure. The difference in urinary BPA concentrations we observed with the indirect and direct methods is unlikely to alter the interpretation of health outcome data.
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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) | 0.003 | 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 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".