Abstract P248: Glycemic Markers and Risk of Peripheral Artery Disease: The Atherosclerosis Risk in Communities (ARIC) Study
Bibliographic record
Abstract
Introduction: Hemoglobin A1c (HbA1c) is a risk marker for incident peripheral artery disease (PAD). However, its relationship to critical limb ischemia (CLI), the most severe form of PAD, has not been fully characterized. Also, the prognostic value of non-traditional glycemic markers, glycated albumin, fructosamine, and 1,5-anhydroglucitol (1,5-AG) for PAD/CLI risk is unknown. Hypotheses: These glycemic markers will be particularly strongly associated with incident CLI, and non-traditional markers may provide additional information on PAD risk beyond HbA1c. Methods: We quantified the associations of four glycemic markers with PAD (hospitalizations with PAD diagnosis [ICD-9: 440.2-440.4] or leg revascularization [eg, 38.18]) in 11,797 ARIC participants free of a history of PAD at baseline (1990-92) using Cox models. Within these PAD cases, CLI was defined with an ICD code of ulcer, gangrene, or leg amputation. All markers were categorized into five groups according to diagnosed diabetes status and percentiles for clinical cut-points of HbA1c as in Table. Results: Over a median follow-up of 20.7 years, there were 397 cases of PAD (137 were CLI). Compared with the non-diabetic reference group, elevated glycemic marker levels (or reduced levels for 1-5AG) significantly contributed to increased risk of PAD (Table). The glycemic contribution was particularly strong for CLI events, with hazard ratios ranging 14-18 (vs. 6-8 for PAD, p for difference <0.001 in all glycemic markers) in diagnosed diabetes with their elevated levels (reduced for 1-5AG). The associations of non-traditional glycemic markers with PAD/CLI risk were strongly attenuated with further adjustment for HbA1c. Conclusions: Glycemic markers were significantly associated with PAD, particularly with its severe form, CLI, supporting the importance of glucose metabolism in the progression of PAD. Non-traditional glycemic markers provide similar (but not much additional) predictive value as HbA1c for classifying PAD risk.
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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) | 0.000 | 0.000 |
| 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".