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Record W3127002597 · doi:10.16966/2380-5544.155

Continuous Glucose Monitors are Cost Neutral Compared to SMBG

2020· article· en· W3127002597 on OpenAlexaff
Thomas G. Elliott, A Weissinger

Bibliographic record

VenueJournal of Diabetes Research and Therapy · 2020
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Research
Canadian institutionsDiabetes CanadaUniversity of British Columbia
Fundersnot available
KeywordsContinuous glucose monitoringBlood Glucose Self-MonitoringMedicineIntensive care medicineDiabetes managementDiabetes mellitusType 1 diabetesType 2 diabetesEndocrinology

Abstract

fetched live from OpenAlex

Continuous Glucose Monitors (CGM) has revolutionized the management of diabetes and has become the standard of care for the management of Type 1 diabetes. The primary factor preventing widespread uptake of CGM is cost. Currently there is little provincial coverage for CGM, and many patients still must pay for the technology. The cost of CGM is here evaluated in comparison to standard care (self monitoring of blood glucose), including analysis of cost-savings and improvements in quality of life that could be achieved with the use of CGM. When costs of comorbidities and absenteeism that could be reduced by the use of CGM are included in the analysis, it is determined that CGM is cost-neutral relative to standard care.

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)0.004
metaresearch head score (Gemma)0.015
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.001

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 head0.113
GPT teacher head0.382
Teacher spread0.269 · 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
Published2020
Admission routes1
Has abstractyes

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