Association Between Plasma Triglycerides and High-Density Lipoprotein Cholesterol and Microvascular Kidney Disease and Retinopathy in Type 2 Diabetes Mellitus
Bibliographic record
Abstract
BACKGROUND: Microvascular renal and retinal diseases are common major complications of type 2 diabetes mellitus. The relation between plasma lipids and microvascular disease is not well established. METHODS AND RESULTS: The case subjects were 2535 patients with type 2 diabetes mellitus with an average duration of 14 years, 1891 of whom had kidney disease and 1218 with retinopathy. The case subjects were matched for diabetes mellitus duration, age, sex, and low-density lipoprotein cholesterol to 3683 control subjects with type 2 diabetes mellitus who did not have kidney disease or retinopathy. The study was conducted in 24 sites in 13 countries. The primary analysis included kidney disease and retinopathy cases. Matched analysis was performed by use of site-specific conditional logistic regression in multivariable models that adjusted for hemoglobin A1c, hypertension, and statin treatment. Mean low-density lipoprotein cholesterol concentration was 2.3 mmol/L. The microvascular disease odds ratio increased by a factor of 1.16 (95% confidence interval, 1.11-1.22) for every 0.5 mmol/L (≈1 quintile) increase in triglycerides or decreased by a factor of 0.92 (0.88-0.96) for every 0.2 mmol/L (≈1 quintile) increase in high-density lipoprotein cholesterol. For kidney disease, the odds ratio increased by 1.23 (1.16-1.31) with triglycerides and decreased by 0.86 (0.82-0.91) with high-density lipoprotein cholesterol. Retinopathy was associated with triglycerides and high-density lipoprotein cholesterol in matched analysis but not significantly after additional adjustment. CONCLUSIONS: Diabetic kidney disease is associated worldwide with higher levels of plasma triglycerides and lower levels of high-density lipoprotein cholesterol among patients with good control of low-density lipoprotein cholesterol. Retinopathy was less robustly associated with these lipids. These results strengthen the rationale for studying dyslipidemia treatment to prevent diabetic microvascular disease.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".