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Record W4416624781 · doi:10.1177/19322968251393740

Expert Opinion Statement on Continuous Glucose Monitoring in Type 2 Diabetes in the Arab Gulf Region

2025· article· en· W4416624781 on OpenAlexaff
Abdulrahman Alshaikh, Abdulmohsen Bakhsh, Afaf Alsagheir, Ahmed El-Laboudi, Dabia Al‐Mohanadi, Fatheya Alawadi, Hussein Elbadawi, Lamya Alzubaidi, Mohammed E. Al‐Sofiani, Muhammad H. Farooqi, Raed Aldahash, Reem Alamoudi, Saud Alsifri, Mohammed Almehthel

Bibliographic record

VenueJournal of Diabetes Science and Technology · 2025
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Research
Canadian institutionsUniversity of British Columbia
FundersDexcom
KeywordsReimbursementContinuous glucose monitoringExpert opinionType 2 diabetesHealth carePopulationMEDLINEDiabetes management

Abstract

fetched live from OpenAlex

The introduction of continuous glucose monitoring (CGM) has been considered a transformative monitoring tool in diabetes management. However, its adoption remains limited in the Gulf region, especially for patients with type 2 diabetes, due to cost, lack of reimbursement strategies, variability in healthcare infrastructure, and lack of trained health care providers (HCPs). The lack of regional guidelines tailored to the unique demographic, cultural, and health care needs of the Gulf population has resulted in low adoption and inconsistent use of CGM in clinical practice, leaving many patients without adequate advanced glucose monitoring options. This expert opinion statement evaluates the evidence for real-time CGM in the management of patients with type 2 diabetes and provides region-specific recommendations to guide HCPs in optimizing CGM use, improving patient outcomes, and addressing barriers to implementation in the Gulf region.

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)0.008
metaresearch head score (Gemma)0.061
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.014
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.061
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0120.006
Insufficient payload (model declined to judge)0.0140.007

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 head0.024
GPT teacher head0.332
Teacher spread0.308 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations3
Published2025
Admission routes1
Has abstractyes

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