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Record W3136585435 · doi:10.1177/1932296821999416

N-Acetylcysteine Interference with a Glucose Dehydrogenase Linked Glucose Meter

2021· article· en· W3136585435 on OpenAlexaff
Martha E. Lyon, Andrew W. Lyon

Bibliographic record

VenueJournal of Diabetes Science and Technology · 2021
Typearticle
Languageen
FieldMedicine
TopicHyperglycemia and glycemic control in critically ill and hospitalized patients
Canadian institutionsSaskatchewan HealthSaskatchewan Health Authority
Fundersnot available
KeywordsGlucose meterGlucose oxidaseChemistryChromatographyBlood Glucose Self-MonitoringMedicineDiabetes mellitusInternal medicineEndocrinologyBiochemistryGlycemicEnzymeContinuous glucose monitoring

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.009
GPT teacher head0.252
Teacher spread0.242 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Diabetes Science and TechnologySame topicHyperglycemia and glycemic control in critically ill and hospitalized patientsFrench-language works237,207