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Record W2948226705 · doi:10.2337/db19-1440-p

1440-P: Does HbA1c Impact Survival in the Newly Diagnosed Elderly Aged 75 Years and Over?

2019· article· en· W2948226705 on OpenAlexaboutno aff
Margaret McGill, Lynda Molyneaux, Maria Constantino, Stephen M. Twigg, Timothy Middleton, Ted Wu, Jencia Wong

Bibliographic record

VenueDiabetes · 2019
Typearticle
Languageen
FieldMedicine
TopicDiabetes, Cardiovascular Risks, and Lipoproteins
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDiabetes mellitusProportional hazards modelDemographySurvival analysisInternal medicinePopulationNational Death IndexGerontologyPediatricsHazard ratioConfidence interval

Abstract

fetched live from OpenAlex

Clinical practice guidelines recommend screening for diabetes after the age of 45 years, but without an upper age limit. An ageing population has resulted in increasing numbers of older people being diagnosed. Previous reports indicate a J-shaped relationship between HbA1c and mortality in older populations with largely longstanding diabetes. However, whether these mortality relationships hold true in the newly diagnosed elderly remains uncertain, as do appropriate glycaemic targets. We aimed to study the relationship between HbA1c and mortality in newly diagnosed elderly aged ≥ 75 years. Records from the RPA Diabetes Clinical Database from 1988 to 2015, linked with the Australian National Death Index to establish all cause, IHD and cancer mortality outcomes were examined. 376 subjects were studied; median diabetes duration at first visit was 0.8 years (IQR 0.2-2.4), with mean age at diagnosis 78.7±3.1 years, 48% male and 53% Angloceltic. Data were stratified by updated HbA1c% NGSP Units categories (< 6; 6.1-7.0; 7.1-8.0; 8.1-9.0 and >9) with a median of 1.8±1.5 measures. Over a median observation period of 6.0 (IQR 2.8-10.4) years there were 237 deaths (17% from cancer, 38.9% from IHD). Using Kaplan-Meier survival analysis for all-cause mortality, no differences in survival between the HbA1c categories were seen (logrank p=0.8). Cox regression was used to examine the relationship between all-cause mortality and updated HbA1c categories after accounting for age or duration at first visit, gender and ethnicity. No significant differences nor observable trends in RR were seen using the HbA1c 6.1-7% group as reference. Prior albuminuria, stroke history and lipid status also had no impact on this relationship. Examination of IHD and cancer-related deaths similarly showed no relationship with HbA1c in this population. Whilst current guidelines recommend a general HbA1c target of 7% to 8% in the elderly we did not demonstrate a survival benefit for any HbA1c level in these newly diagnosed over 75 years of age. Disclosure M. McGill: None. L.M. Molyneaux: None. M.I. Constantino: None. S.M. Twigg: Advisory Panel; Self; Abbott, Boehringer Ingelheim Pharmaceuticals, Inc., Novo Nordisk Inc., Sanofi-Aventis. Board Member; Self; AstraZeneca. Research Support; Self; Abbott. Speaker's Bureau; Self; Abbott, AstraZeneca, Merck Sharp & Dohme Corp., Novo Nordisk Inc., Sanofi-Aventis. T. Middleton: Other Relationship; Self; AstraZeneca. T. Wu: Advisory Panel; Self; Boehringer Ingelheim International GmbH, Eli Lilly and Company, Novo Nordisk A/S, Sanofi. Speaker's Bureau; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Merck Sharp & Dohme Corp., Novo Nordisk A/S, Sanofi. J. Wong: Advisory Panel; Self; Sanofi. Speaker's Bureau; Self; AstraZeneca, Lilly 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.

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)0.003
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.008
GPT teacher head0.244
Teacher spread0.236 · 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 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

Citations0
Published2019
Admission routes1
Has abstractyes

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