Relation Between Red Blood Cell Distribution Width and Cardiovascular Event Rate in People With Coronary Disease
Bibliographic record
Abstract
BACKGROUND: Higher levels of red blood cell distribution width (RDW) may be associated with adverse outcomes in patients with heart failure. We examined the association between RDW and the risk of all-cause mortality and adverse cardiovascular outcomes in a population of people with coronary disease who were free of heart failure at baseline. METHODS AND RESULTS: We performed a post hoc analysis of data from the Cholesterol and Recurrent Events study. Baseline RDW was measured in 4111 participants who were randomized to receive pravastatin 40 mg daily or placebo and followed for a median of 59.7 months. We used Cox proportional hazards models to examine the association between RDW and adverse clinical outcomes. During nearly 60 months of follow-up, 376 participants died. A significant association was noted between baseline RDW level and the adjusted risk of all-cause mortality (hazard ratio per percent increase in RDW, 1.14; 95% confidence interval, 1.05 to 1.24). After categorization based on quartile of baseline RDW and further adjustment for hematocrit and other cardiovascular risk factors, a graded independent relation between RDW and death was observed (P for trend=0.001). For instance, participants with RDW in the highest quartile had an adjusted hazard ratio for death of 1.78 (95% confidence interval, 1.28 to 2.47) compared with those in the lowest quartile. Higher levels of RDW were also associated with increased risk of coronary death/nonfatal myocardial infarction, new symptomatic heart failure, and stroke. CONCLUSIONS: We found a graded independent relation between higher levels of RDW and the risk of death and cardiovascular events in people with prior myocardial infarction but no symptomatic heart failure at baseline.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".