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Record W4389118485 · doi:10.2337/dc23-0839

Diabetes Risk Factors and Bone Microarchitecture as Assessed by High-Resolution Peripheral Quantitative Computed Tomography in Adults With Long-standing Type 1 Diabetes

2023· article· en· W4389118485 on OpenAlexaff
Naina Sinha Gregory, Andrew J. Burghardt, Jye‐Yu C. Backlund, Mishaela R. Rubin, Ionut Bebu, Barbara H. Braffett, David J. Kenny, Thomas M. Link, Galateia J. Kazakia, Annette Barnie, John M. Lachin, Rose Gubitosi‐Klug, Ian H. de Boer, Ann V. Schwartz

Bibliographic record

VenueDiabetes Care · 2023
Typearticle
Languageen
FieldMedicine
TopicBone health and osteoporosis research
Canadian institutionsUniversity of TorontoMount Sinai Hospital
FundersDivision of Diabetes, Endocrinology, and Metabolic DiseasesNational Center for Advancing Translational SciencesNational Institute of Arthritis and Musculoskeletal and Skin DiseasesFeinberg School of MedicineCase Western Reserve UniversityNational Institute of Diabetes and Digestive and Kidney DiseasesUniversity of MinnesotaGeorge Washington UniversityNorthwestern University
KeywordsMedicineQuantitative computed tomographyDiabetes mellitusType 2 diabetesPeripheralComputed tomographyType 1 diabetesInternal medicineRadiologyBone densityEndocrinologyOsteoporosis

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine whether type 1 diabetes and its complications are associated with bone geometry and microarchitecture. RESEARCH DESIGN AND METHODS: This cross-sectional study was embedded in a long-term observational study. High-resolution peripheral quantitative computed tomography (HR-pQCT) scans of the distal radius and distal and diaphyseal tibia were performed in a subset of 183 participants with type 1 diabetes from the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) study and 94 control participants without diabetes. HbA1c, skin advanced glycation end products (AGEs), and diabetes-related complications were assessed in EDIC participants with >30 years of follow-up. RESULTS: Compared with control participants (aged 60 ± 8 years, 65% female), EDIC participants (aged 60 ± 7 years, diabetes duration 38 ± 5 years, 51% female) had lower total bone mineral density (BMD) at the distal radius (-7.9% [95% CI -15.2%, -0.6%]; P = 0.030) and distal tibia (-11.3% [95% CI -18.5%, -4.2%]; P = 0.001); larger total area at all sites (distal radius 4.7% [95% CI 0.5%, 8.8%; P = 0.030]; distal tibia 5.9% [95% CI 2.1%, 9.8%; P = 0.003]; diaphyseal tibia 3.4% [95% CI 0.8%, 6.1%; P = 0.011]); and poorer radius trabecular and cortical microarchitecture. Estimated failure load was similar between the two groups. Among EDIC participants, higher HbA1c, AGE levels, and macroalbuminuria were associated with lower total BMD. Macroalbuminuria was associated with larger total area and lower cortical thickness at the distal radius. Higher HbA1c and AGE levels and lower glomerular filtration rate, peripheral neuropathy, and retinopathy were associated with deficits in trabecular microarchitecture. CONCLUSIONS: Type 1 diabetes is associated with lower BMD, larger bone area, and poorer trabecular microarchitecture. Among participants with type 1 diabetes, suboptimal glycemic control, AGE accumulation, and microvascular complications are associated with deficits in bone microarchitecture and lower BMD.

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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.011
GPT teacher head0.277
Teacher spread0.266 · 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

Citations14
Published2023
Admission routes1
Has abstractyes

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