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Record W4399500926 · doi:10.1111/dom.15703

Cost–utility analysis of a flash continuous glucose monitoring system in the management of people with type 2 diabetes mellitus on basal insulin therapy—An Italian healthcare system perspective

2024· article· en· W4399500926 on OpenAlexaff
Stefano Del Prato, Francesco Giorgino, Kirk Szafranski, Yeesha Poon

Bibliographic record

VenueDiabetes Obesity and Metabolism · 2024
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Research
Canadian institutionsEVERSANA (Canada)
Fundersnot available
KeywordsPerspective (graphical)Basal insulinFlash (photography)Continuous glucose monitoringMedicineType 2 Diabetes MellitusIntensive care medicineDiabetes mellitusBasal (medicine)InsulinCritically illType 1 diabetesType 2 diabetesComputer scienceInternal medicineEndocrinologyArtificial intelligenceArt

Abstract

fetched live from OpenAlex

AIMS: To assess the cost-utility of the FreeStyle Libre flash continuous glucose monitoring (CGM) system from an Italian healthcare system perspective, when compared with self-monitoring of blood glucose (SMBG) in people living with type 2 diabetes mellitus (T2DM) receiving basal insulin. MATERIALS AND METHODS: A patient-level microsimulation model was run using Microsoft Excel for 10 000 patients over a lifetime horizon, with 3.0% discounting for costs and utilities. Inputs were based on clinical trials and real-world evidence, with patient characteristics reflecting Italian population data. The effect of flash CGM was modelled as a persistent 0.8% reduction in glycated haemoglobin versus SMBG. Costs (€ 2023) and disutilities were applied to glucose monitoring, diabetes complications, severe hypoglycaemia, and diabetic ketoacidosis. The health outcome was measured as quality-adjusted life-years (QALYs). RESULTS: Direct costs were €5338 higher with flash CGM than with SMBG. Flash CGM was associated with 0.51 more QALYs than SMBG, giving an incremental cost-effectiveness ratio (ICER) of €10 556/QALY. Scenario analysis ICERs ranged from €3825/QALY to €26 737/QALY. In probabilistic analysis, flash CGM was 100% likely to be cost effective at willingness-to-pay thresholds > €20 000/QALY. CONCLUSIONS: From an Italian healthcare system perspective, flash CGM is cost effective compared with SMBG for people living with T2DM on basal insulin.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.097
Threshold uncertainty score0.675

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
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 head0.023
GPT teacher head0.295
Teacher spread0.272 · 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 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

Citations17
Published2024
Admission routes1
Has abstractyes

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