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Record W3112122139 · doi:10.1038/s41598-020-79132-1

The effect of diabetes and the common diabetogenic TBC1D4 p.Arg684Ter variant on cardiovascular risk in Inuit in Greenland

2020· article· en· W3112122139 on OpenAlexaboutno aff
Maria Overvad, Lars Jorge Díaz, Peter Bjerregaard, Michael Lynge Pedersen, Christina Viskum Lytken Larsen, Ninna Senftleber, Niels Grarup, Torben Hansen, Marit E. Jørgensen

Bibliographic record

VenueScientific Reports · 2020
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Function and Risk Factors
Canadian institutionsnot available
FundersSyddansk UniversitetNovo Nordisk FondenSteno Diabetes Center CopenhagenHjerteforeningen
KeywordsDiabetes mellitusMedicineInternal medicineBioinformaticsCardiologyEndocrinologyBiology

Abstract

fetched live from OpenAlex

Cardiovascular disease (CVD) is a well-known complication of diabetes, but the association has not been studied among Inuit in Greenland. The aim was to examine the association between diabetes and incident CVD among Inuit in Greenland and determine if the common diabetogenic TBC1D4 variant confers increased risk of CVD. We followed an initial study population of 4127 adults in Greenland who had participated in at least one population-based health survey, in national registers. We used Poisson regression to calculate incidence rate ratios (IRR) of cardiovascular endpoints, comparing participants with and without diabetes and comparing homozygous TBC1D4 carriers with heterozygous carriers and non-carriers combined. Close to 10% had diabetes and age range was 18-96 years (45% male). Of the 3924 participants without prior CVD, 362 (~ 9%) had CVD events during a median follow-up of 10 years. Multivariate IRR for the effect of diabetes on CVD was 1.12 (95% CI: 0.80, 1.57) p = 0.50. Using a recessive genetic model, we compared homozygous TBC1D4 carriers with wildtype and heterozygous carriers combined, with a multivariate IRR of 1.20 (95% CI: 0.69, 2.11) p = 0.52. Neither diabetes nor the TBC1D4 variant significantly increased CVD risk among Inuit in Greenland in adjusted models.

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)0.007
metaresearch head score (Gemma)0.001
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 score0.020
Threshold uncertainty score0.293

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
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 head0.006
GPT teacher head0.208
Teacher spread0.202 · 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

Citations31
Published2020
Admission routes1
Has abstractyes

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