MétaCan
Menu
Back to cohort
Record W4392960534 · doi:10.1016/j.lanepe.2024.100888

Non-coronary peripheral arterial complications in people with type 2 diabetes: a Swedish retrospective cohort study

2024· article· en· W4392960534 on OpenAlexaff
Araz Rawshani, Björn Eliasson, Jan Borén, Naveed Sattar, Deepak L. Bhatt, Linn El-Khalili, Joakim Nordanstig, Tarik Avdic, Joshua A. Beckman, Hertzel C. Gerstein, Darren K. McGuire, Elmir Ömerovic, Aidin Rawshani

Bibliographic record

VenueThe Lancet Regional Health - Europe · 2024
Typearticle
Languageen
FieldMedicine
TopicPeripheral Artery Disease Management
Canadian institutionsHamilton Health SciencesMcMaster UniversityPopulation Health Research Institute
FundersHjärt-Lungfonden
KeywordsMedicineInternal medicineDiabetes mellitusType 2 diabetesRisk factorCohortCardiologyCoronary artery diseaseType 2 Diabetes MellitusPopulationSurgeryEndocrinology

Abstract

fetched live from OpenAlex

Background: Few studies have explored long-term trends and risk factors for peripheral arterial complications in type 2 diabetes compared to the general population. Our research focuses on identifying optimal risk factors, their significance, risk associated with multifactorial risk factor control, and trends for these complications in diabetic patients versus general controls. Methods: This study included persons with type 2 diabetes mellitus entered into the Swedish National Diabetes Register 2001-2019 and controls matched for age-, sex- and county of residence. Outcomes comprised of extracranial large artery disease, aortic aneurysm, aortic dissection, lower extremity arterial disease and diabetes foot disease. Standardized incidence rates and Cox regression were used for analyses. Findings: The study comprises 655,250 persons with type 2 diabetes mellitus; average age 64.2; 43.8% women. Among persons with type 2 diabetes mellitus, the incidence rates per 100,000 person years for each non-coronary peripheral arterial complication event changed between 2001 and 2019 as follows: extracranial large artery disease 170.0-84.9; aortic aneurysm 40.6-69.2; aortic dissection 9.3 to 5.6; lower extremity artery disease from 338.8 to 190.8; and diabetic foot disease from 309.8 to 226.8. Baseline hemoglobin A1c (HbA1c), systolic blood pressure (SBP), smoking status and lipid levels were independently associated with all outcomes in the type 2 diabetes mellitus cohort. Within the cohort with type 2 diabetes mellitus, the risk for extracranial large artery disease and lower extremity artery disease increased in a stepwise fashion for each risk factor not within target. Excess risk for non-coronary peripheral arterial complications in the entire cohort for persons with type 2 diabetes mellitus, compared to matched controls, were as follows: extracranial large artery disease adjusted hazard ratio (HR) 1.69 (95% confidence interval (CI), 1.65-1.73), aortic aneurysm HR 0.89 (95% CI, 0.87-0.92), aortic dissection HR 0.51 (95% CI, 0.46-0.57) and lower extremity artery disease HR 2.59 (95% CI, 2.55-2.64). Interpretation: The incidence of non-coronary peripheral arterial complications has declined significantly among persons with type 2 diabetes mellitus, with the exception of aortic aneurysm. HbA1c, smoking and blood pressure demonstrated greatest relative contribution for outcomes and lower levels of cardiometabolic risk factors are associated with reduced relative risk of outcomes. Funding: Swedish Governmental and the County support of research and education of doctors, the Swedish Heart-Lung Foundation and Åke-Wibergs grant.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.038
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.032
GPT teacher head0.315
Teacher spread0.284 · 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

Citations8
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueThe Lancet Regional Health - EuropeSame topicPeripheral Artery Disease ManagementFrench-language works237,207