Intensive lifestyle intervention in type 2 diabetes and risk of incident coronary artery disease for the common haptoglobin phenotypes: the Look AHEAD study
Bibliographic record
Abstract
BACKGROUND: Intensive glycemic control reduced coronary artery disease (CAD) events among the Action to Control Cardiovascular Disease Risk in Diabetes (ACCORD) participants with the haptoglobin (Hp) 2-2 phenotype only. It remains unknown whether Hp phenotype modifies the effect of an intensive lifestyle intervention (ILI) on CAD in type 2 diabetes. METHODS: Haptoglobin phenotype was measured in 4542 samples from the Action for Health in Diabetes (Look AHEAD) study. Cox regression models assessed the effect of ILI (focused on weight loss from caloric restriction and physical activity) versus diabetes support and education (DSE) on CAD events in each phenotype group, and within pre-specified subgroups including race/ethnicity, sex, history of cardiovascular disease, diabetes medication use, and diabetes duration. RESULTS: 1590 (35%) participants had the Hp2-2 phenotype. The ILI did not lower glycated hemoglobin (%HbA1c) to < 6.5% in either phenotype, with a peak significant difference between treatment arms of 0.5% [non-Hp2-2] and 0.6% [Hp2-2]. The cumulative CAD incidence was 13.4% and 13.8% in the DSE arm and 12.2% and 13.6% in the ILI arm for non-Hp2-2 and Hp2-2 groups, respectively. Compared to DSE, the ILI was not associated with CAD among participants without (HR = 0.95, 95% CI 0.78-1.17) or with (0.89, 0.68-1.19) the Hp2-2 phenotype (p-interaction between Hp phenotype and ILI = 0.58). After Bonferroni correction, there were no significant results among any subgroups. CONCLUSIONS: Hp phenotype did not modify the effect of the weight loss ILI on risk of CAD in Look AHEAD, potentially because it did not substantially impact glycemic control among participants with or without the Hp2-2 phenotype. Further research is needed to determine if these results are conclusive.
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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 | 0.001 |
| 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) | 0.002 | 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".