Adiponectin, Free Fatty Acids, and Cardiovascular Outcomes in Patients With Type 2 Diabetes and Acute Coronary Syndrome
Bibliographic record
Abstract
OBJECTIVE In observational cohorts, adiponectin is inversely associated and free fatty acids (FFAs) are directly associated with incident coronary heart disease (CHD). Adiponectin tends to be reduced and FFAs elevated in type 2 diabetes. We investigated relationships of adiponectin and FFA and major adverse cardiovascular events (MACEs) and death in patients with acute coronary syndrome (ACS) and type 2 diabetes using data from the AleCardio (Effect of Aleglitazar on Cardiovascular Outcomes After Acute Coronary Syndrome in Patients With Type 2 Diabetes Mellitus) trial, which compared the PPAR-α/γ agonist aleglitazar with placebo. RESEARCH DESIGN AND METHODS Using Cox regression adjusted for demographic, laboratory, and treatment variables, we determined associations of baseline adiponectin and FFAs, or the change in adiponectin and FFAs from baseline, with MACEs (cardiovascular death, myocardial infarction, or stroke) and death. RESULTS A twofold higher baseline adiponectin (n = 6,998) was directly associated with risk of MACEs (hazard ratio [HR] 1.17 [95% CI 1.08–1.27]) and death (HR 1.53 [95% CI 1.35–1.73]). A doubling of adiponectin from baseline to month 3 (n = 6,325) was also associated with risk of death (HR 1.20 [95% CI 1.03–1.41]). Baseline FFAs (n = 7,038), but not change in FFAs from baseline (n = 6,365), were directly associated with greater risk of MACEs and death. There were no interactions with study treatment. CONCLUSIONS In contrast to prior observational data for incident CHD, adiponectin is prospectively associated with MACEs and death in patients with type 2 diabetes and ACS, and an increase in adiponectin from baseline is directly related to death. These findings raise the possibility that adiponectin has different effects in patients with type 2 diabetes and ACS than in populations without prevalent cardiovascular disease. Consistent with prior data, FFAs are directly associated with adverse outcomes.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".