N-Acetylcysteine Interference with a Glucose Dehydrogenase Linked Glucose Meter
Bibliographic record
Abstract
BACKGROUND: Our objective was to determine the effect of therapeutic concentrations of N-acetylcysteine, following intravenous infusion, on the measurement of blood glucose using a Roche Diagnostics glucose dehydrogenase-linked glucose meter compared to hospital laboratory methods. METHODS: N-acetylcysteine was added to aliquots of blood, with glucose promptly measured by the glucose meter, blood gas analyzer (glucose oxidase comparative method) and following centrifugation, plasma glucose measured with a hexokinase spectrophotometric comparative method. Glucose results were evaluated with linear regression and Bland Altman plots. RESULTS: In the presence of NAC, at concentrations greater than 5 mg/dL (0.31 mmol/L), positively biased glucose meter results were compared to the clinical laboratory results. Multivariate linear regression revealed that NAC-mediated meter results are influenced by NAC and glucose concentrations. CONCLUSIONS: The addition of therapeutic concentrations of NAC to blood produces statistically significant positive biases when measured with the glucose dehydrogenase linked glucose meter device.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".