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Record W2164667631 · doi:10.1177/193229680900300407

Increases in Whole Blood Glucose Measurements Using Optically Based Self-Monitoring of Blood Glucose Analyzers Due to Extreme Canadian Winters

2009· article· en· W2164667631 on OpenAlexaffabout
George Cembrowski, Barbara K. Smith, Ellen M. O’Malley

Bibliographic record

VenueJournal of Diabetes Science and Technology · 2009
Typearticle
Languageen
FieldMedicine
TopicHyperglycemia and glycemic control in critically ill and hospitalized patients
Canadian institutionsUniversity of Alberta HospitalAlberta Hospital Edmonton
Fundersnot available
KeywordsBlood Glucose Self-MonitoringBlood glucose monitoringMedicineWhole bloodDiabetes mellitusChromatographyEmergency medicineEnvironmental scienceContinuous glucose monitoringInternal medicineChemistryEndocrinologyType 1 diabetes

Abstract

fetched live from OpenAlex

BACKGROUND: Temperature and humidity have been reported to influence the results of whole blood glucose (WBG) measurements. METHODS: To determine whether patient WBG values were affected by seasonal variation, we conducted a retrospective analysis of 3 years' worth of weekly averages of patient WBG in five Edmonton hospitals. RESULTS: In all five hospitals, the winter WBG averages were consistently higher than the summer WBG averages, with the differences varying between 5% and 9%. Whole blood glucose averages were negatively correlated with the outside temperature. This seasonal variation was not observed in weekly patient averages of specimens run in a central hospital laboratory. INTERPRETATION: It is probable that the seasonal variation of WBG arises from the very low indoor humidities that are associated with external subzero temperatures. These increases in WBG in cold weather may be due to limitations in the WBG measuring systems when operated in decreased humidities and/or increased evaporation of the blood sample during the blood glucose measurement process. The implications of this seasonal variation are significant in that it (1) introduces increased variability in patient WBG, (2) may result in increased glucose-lowering therapy during periods of external cold and low indoor humidity, and (3) confounds evaluations of WBG meter technology in geographic regions of subzero temperature and low indoor humidity. To mitigate the risk of diagnosing and treating factitious hyperglycemia, the humidity of patient care areas must be strictly controlled.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.168
Threshold uncertainty score0.522

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.022
GPT teacher head0.270
Teacher spread0.248 · 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 teacher head, 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

Citations5
Published2009
Admission routes2
Has abstractyes

Explore more

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