Risk factors for diabetic kidney disease in adults with longstanding type 1 diabetes: results from the Canadian Study of Longevity in Diabetes
Bibliographic record
Abstract
Objectives: Diabetic kidney disease (DKD) is an independent predictor of cardiovascular morbidity and mortality in type 1 diabetes (T1D). We aimed to explore clinical and biochemical factors, including the achievement of American Diabetes Association (ADA) recommended targets associated with DKD in people living with T1D for ≥50 years.Methods: This was a post hoc analysis of a cross-sectional study of 75 participants enrolled in the Canadian Study of Longevity in T1D. We explored diabetes-related complications, including neuropathy, retinopathy, cardiovascular disease, and DKD. Study participants were dichotomized based on the achievement of ADA recommended targets as the low-target group (achieving ≤4 targets, n = 31) and high-target group (achieving >4 targets, n = 44). The outcome of interest was DKD defined by estimated glomerular filtration rate (eGFR) values <60/mL/min/1.73 m2 and/or 24-h albumin excretion >30 mg. Multivariable logistic regression models were employed to estimate odds ratios (ORs) for DKD with 95% confidence intervals (CIs).Results: Of the 75 participants with prolonged T1D duration (45% male, mean age 66 years), 25 participants had DKD and 50 did not. There was no statistical difference between the high- and low-target groups in terms of age and body mass index. eGFR was significantly higher and the prevalence of diabetic retinopathy was significantly lower in the high-target group. Older age at diagnosis of T1D and lower frequency component to high-frequency component ratio increased the odds of having DKD.Conclusions: In adults with prolonged T1D duration, older age at diagnosis and lower heart rate variability may be associated with DKD.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.002 | 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".