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Improving glucose management: Ten steps to get more patients with type 2 diabetes to glycaemic goal

2005· article· en· W2124701241 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Clinical Practice · 2005
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineType 2 diabetesIntensive care medicineMultidisciplinary approachDiabetes mellitusGeneral partnershipDiabetes managementHealth careQuality of life (healthcare)Risk analysis (engineering)Nursing

Abstract

fetched live from OpenAlex

Despite increasingly stringent clinical practice guidelines for glycaemic control, the implementation of recommendations has been disappointing, with over 60% of patients not reaching recommended glycaemic goals. As a result, current management of glycaemia falls significantly short of accepted treatment goals. The Global Partnership for Effective Diabetes Management has identified a number of major barriers that can prevent individuals from achieving their glycaemic targets. This article proposes 10 key practical recommendations to aid healthcare providers in overcoming these barriers and to enable a greater proportion of patients to achieve glycaemic goals. These include advice on targeting the underlying pathophysiology of type 2 diabetes, treating early and effectively with combination therapies, adopting a holistic, multidisciplinary approach and improving patient understanding of type 2 diabetes. Implementation of these recommendations should reduce the risk of diabetes-related complications, improve patient quality of life and impact more effectively on the increasing healthcare cost related to diabetes.

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.

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)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.799
Threshold uncertainty score0.619

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.025
GPT teacher head0.414
Teacher spread0.389 · 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