Abstract 11651: Effect of Combination Lipid Therapy on Incident Atrial Fibrillation or its Electrocardiographic Surrogate in the Action to Control Cardiovascular Risk in Diabetes Lipid (ACCORD Lipid) Trial
Bibliographic record
Abstract
Introduction: Atrial fibrillation (AF) is associated with increased cardiovascular disease (CVD) risk in patients with type 2 diabetes (DM). Observational studies have suggested that higher HDL and lower triglycerides are associated with lower AF risk. Hypothesis: We hypothesized that raising HDL and lowering triglycerides will reduce AF incidence in patients with DM. As such, we compared combination lipid therapy with simvastatin and fenofibrate vs. simvastatin alone in relation to incidence of AF or its established ECG surrogate, P-wave indices (PWI), in patients with DM. Methods: We analyzed data from the Action to Control Cardiovascular Risk in Diabetes Lipid (ACCORD Lipid) trial (Jan 2001-June 2009), a randomized controlled blinded trial of patients with DM and who were aged 40–79 years with CVD or aged 55–79 years with subclinical CVD or >2 CVD risk factors. Patients were randomized to receive simvastatin plus placebo vs. simvastatin plus fenofibrate. Dosing of simvastatin and fenofibrate was based on trial protocol. The primary outcome was a composite of incident AF (ascertained from study ECGs) or PWI (P wave duration in lead II ≥120 ms, P’ (negative) amplitude in V1 ≥100 μV, or P-terminal force in V1 >-4000 μV.ms). Results: Data from 5518 participants (mean age, 62.3 years; women, 30.7%; non-white, 34.5%) were analyzed. The Table shows the results after a mean follow-up of 4.7 years. Conclusions: Compared with simvastatin alone, combination lipid therapy with simvastatin and fenofibrate did not reduce the incidence of AF or its ECG surrogate in patients with DM at high CVD risk. Further research is needed to elucidate the role of dyslipidemia in the etiology of AF and to discover effective prevention strategies for AF in patients with DM.
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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) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".