MétaCan
Menu
Back to cohort
Record W3033741448 · doi:10.1097/xce.0000000000000210

Estimating life years lost to diabetes: outcomes from analysis of National Diabetes Audit and Office of National Statistics data

2020· article· en· W3033741448 on OpenAlex
Adrian Heald, Mike Stedman, Mark Davies, Mark Livingston, Ramadan Alshames, Mark Lunt, Gerry Rayman, Roger Gadsby

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

VenueCardiovascular Endocrinology & Metabolism · 2020
Typearticle
Languageen
FieldMedicine
TopicChronic Disease Management Strategies
Canadian institutionsHealth Sciences Centre
Fundersnot available
KeywordsLife expectancyDiabetes mellitusMedicineType 1 diabetesDemographyPopulationAuditGerontologyPediatricsEnvironmental healthEndocrinology

Abstract

fetched live from OpenAlex

With sustained growth of diabetes numbers, sustained patient engagement is essential. Using nationally available data, we have shown that the higher mortality associated with a diagnosis of T1DM/T2DM could produces loss of 6.4 million future life years in the current UK population. In the model, the 'average' person with T1DM (age 42.8 years) has a life expectancy from now of 32.6 years, compared to 40.2 years in the equivalent age non diabetes mellitus population, corresponding to lost life years (LLYs) of 7.6 years/average person. The 'average' person with T2DM (age 65.4 years) has a life expectancy from now of 18.6 years compared to the 20.3 years for the equivalent non diabetes mellitus population, corresponding to LLY of 1.7 years/average person. We estimate that for both T1DM and T2DM, one year with HbA1c >58 mmol/mol loses around 100 life days. Linking glycaemic control to mortality has the potential to focus minds on effective engagement with therapy and lifestyle recommendation adherence.

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)0.000
metaresearch head score (Gemma)0.003
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 score0.486
Threshold uncertainty score0.848

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.059
GPT teacher head0.311
Teacher spread0.253 · 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