Brain Structure among Middle-aged and Older Adults with Longstanding Type 1 Diabetes in the DCCT/EDIC Study
Bibliographic record
Abstract
Objective: Individuals with type 1 diabetes (T1DM) are living to ages when neuropathological changes are increasingly evident. We hypothesized that middle-aged and older adults with long-standing T1DM will show abnormal brain structure in comparison to non-diabetic controls. Research Design and Methods: Magnetic resonance imaging (MRI) was used to compare brain structure among 416 T1DM participants in the Epidemiology of Diabetes Interventions and Complications (EDIC) study with 99 demographically similar non-diabetic controls at 26 U.S. and Canadian sites. Assessments included total brain (TBV, primary outcome), gray matter (GMV), white matter (WMV), ventricle and white matter hyperintensity (WMH) volumes and white matter fractional anisotropy (FA). Biomedical assessments included HbA1c and lipid levels, blood pressure, and cognitive assessments of memory and psychomotor and mental efficiency (PME). Among EDIC participants, HbA1c, severe hypoglycemia history, and vascular complications were measured longitudinally. Results: Mean age of EDIC participants and controls was 60 years. T1DM participants showed significantly smaller TBV (1206 ± 1.7 vs. 1229 ± 3.5 cm3, p<0.0001), GMV and WMV, larger ventricle and WMH volumes, but no differences in mean white matter FA versus controls. Structural MRI measures in T1DM were equivalent to controls who are 4 to 9 years older. Lower PME scores were associated with altered brain structure on all MRI measures in T1DM participants. Conclusions: Middle-aged and older adults with T1DM showed brain volume loss and increased vascular injury in comparison to non-diabetic controls, equivalent to 4 to 9 years of brain aging.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".