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Record W2016678877 · doi:10.12968/bjon.2012.21.10.588

In pursuit of excellence in diabetes care: trends in insulin delivery

2012· article· en· W2016678877 on OpenAlexaff
Danny Meetoo, Gillian McAllister, Adele West, Mandy Turnbull

Bibliographic record

VenueBritish Journal of Nursing · 2012
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Research
Canadian institutionsRoyal Ottawa Mental Health Centre
Fundersnot available
KeywordsMedicineDiabetes mellitusInsulinExcellenceInsulin penIntensive care medicineInsulin deliveryType 2 Diabetes MellitusType 1 diabetesInternal medicineEndocrinology

Abstract

fetched live from OpenAlex

Diabetes mellitus has been estimated to affect 2.9 million people in the UK. Large-scale clinical trials conclusively demonstrate that elevated blood glucose levels are associated with an increased risk of micro- and macrovascular complications. The high rates of morbidity and mortality associated with this condition demonstrate how important effective glycaemic control is. Subcutaneous insulin injection continues to be the mainstay of therapy for all people with type 1 diabetes mellitus and the majority of individuals with type 2 diabetes mellitus. However, there are a number of barriers to insulin therapy. For example, conventional insulin delivery is arguably time consuming. Furthermore, it has been associated with common errors, such as inaccurate dosing and administration (National Patient Safety Agency, 2010). Insulin pen devices have various advantages over conventional delivery. Their ease of use and incorporation into busy lifestyles may improve diabetes control with much less effort, while maintaining adherence and quality of life. Research in insulin delivery shows there is a prospect of needle-free delivery in the near future. Despite such progress, the role of the healthcare professionals in involving, assessing, supporting and educating people having insulin therapy, including the attainment of the agreed blood glucose levels, cannot be overestimated.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.677
Threshold uncertainty score0.310

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.029
GPT teacher head0.323
Teacher spread0.294 · 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

Citations2
Published2012
Admission routes1
Has abstractyes

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