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Record W3172962300 · doi:10.2337/db19-98-lb

98-LB: Efficacy and Clinical Considerations of Flash Glucose Monitoring among Canadian Adults with Diabetes

2019· article· en· W3172962300 on OpenAlexaboutno aff
Aria Jazdarehee, Jordanna Kapeluto, Monika Pawłowska, MONIKA PAWLOWSKA, JESSICA MACKENZIE-FEDER, BENJAMIN SCHROEDER, ADAM WHITE

Bibliographic record

VenueDiabetes · 2019
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Research
Canadian institutionsnot available
Fundersnot available
KeywordsGlycemicMedicineDiabetes mellitusBlood Glucose Self-MonitoringEmergency medicineContinuous glucose monitoringEndocrinology

Abstract

fetched live from OpenAlex

The FreeStyle Libre flash glucose monitoring (FGM) system was introduced in Canada in 2017. FGM incorporates aspects of conventional blood glucose testing and continuous glucose monitoring (CGM). The FreeStyle Libre utilizes a sensor placed on the upper arm to test interstitial glucose levels every fifteen minutes and may be used to obtain a ‘flash’ (real-time) reading. The FreeStyle Libre system is less costly than CGM and may help overcome common barriers to conventional glucose testing, including pain, needle aversion, and inconvenience, but at present there is no public coverage for the product available in Canada. In this study, we investigated the continuation rate of FGM use in patients provided complimentary FreeStyle Libre starter packs, consisting of one reader and two 14-day sensors, and the impact of continued use on glycemic control. More than half (21/40) continued to use the system beyond the trial period. The mean A1C of patients who continued using FGM decreased by 1.14% at three months, compared to an increase of 0.17% in those who did not (p=0.038). Despite small sample size, there was also a trend of decreased basal and bolus insulin requirements in patients continuing use. These results show benefit and support the implementation of public coverage because greater adherence of self-monitoring of blood glucose results in improved glycemic control which ultimately reduces the risk of long-term diabetes associated complications and healthcare costs. Disclosure A. Jazdarehee: None. J.E. Kapeluto: None. M. Pawlowska: None. J. MacKenzie-Feder: None. B. Schroeder: Advisory Panel; Self; Abbott, Boehringer Ingelheim Pharmaceuticals, Inc., Janssen Pharmaceuticals, Inc., LifeScan Canada, Natesto, Sanofi-Aventis. Speaker’s Bureau; Self; AstraZeneca, Eli Lilly and Company, Merck & Co., Inc., Novo Nordisk Inc. A. White: Advisory Panel; Self; Abbott, AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Janssen Pharmaceuticals, Inc., Lilly Diabetes, Novo Nordisk Inc., Sanofi. Speaker’s Bureau; Self; Merck & Co., Inc. Other Relationship; Self; Diabetes Canada.

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)0.002
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.089
Threshold uncertainty score0.179

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.288
Teacher spread0.271 · 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 designObservational
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

Citations0
Published2019
Admission routes1
Has abstractyes

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