Alternative kidney filtration markers and the risk of major macrovascular and microvascular events, and <scp>all‐cause</scp> mortality in individuals with type 2 diabetes in the <scp>ADVANCE</scp> trial
Bibliographic record
Abstract
Abstract Background Creatinine‐based estimated glomerular filtration rate (eGFR) is biased in the setting of obesity and other conditions. Alternative kidney filtration markers may be useful in adults with diabetes, but few studies examined the associations with risk of clinical outcomes. Methods In the Action in Diabetes and Vascular Disease: Preterax and Diamicron Modified Release Controlled Evaluation (ADVANCE) trial, we evaluated whether baseline levels and change in eGFR based on creatinine (Cr), cystatin c (Cys), β2‐microglobulin (B2M), eGFRCr‐Cys, and the average of three estimates (eGFRCr‐Cys‐B2M) assessed in 7217 participants at baseline and a random sample of 640 participants at the 1‐year visit are associated with clinical outcomes. We examined associations with major macrovascular and microvascular events together and separately and all‐cause mortality using Cox regression models, adjusting for established risk factors. Results Over a median follow‐up of 5 years, 1313 major macrovascular (n = 748) and microvascular events (n = 637), and 743 deaths occurred. Lower levels of eGFR based on all filtration markers individually and combined were associated with 1.4 to 3.0 times higher risk of major macrovascular and microvascular events (combined and separately) and all‐cause mortality. Per 30% decline in eGFRCys, eGFR Cr‐Cys, and eGFRCr‐Cys‐B2M were associated with a >2‐fold higher risk of all clinical outcomes. Conclusions In adults with type 2 diabetes, baseline levels of eGFR based on alternative filtration markers and per 30% decline in eGFRCys, eGFR Cr‐Cys, and eGFRCr‐Cys‐B2M were associated with clinical outcomes. Measurement of alternative filtration markers, particularly B2M in adults with type 2 diabetes may be warranted.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| 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".