Serum Creatinine Concentration and the Risk of Stroke, Myocardial Infarction, and Vascular Death in Patients with Symptomatic Carotid Stenosis.
Bibliographic record
Abstract
P144 Background: High serum creatinine (SCr) is a predictor of mortality in patients with hypertension, myocardial infarction (MI), and stroke. In men it is associated with stroke. Objective: Examine the relationship between SCr and the risk of stroke, MI, and vascular death (VD) in patients with symptomatic internal carotid artery (ICA) stenosis. Methods: Data from 1977 male NASCET patients with baseline SCr measurements were analyzed. Results: Increased levels of SCr were associated with older age and a higher prevalence of hypertension, history of MI or angina, and intermittent claudication. No association was found between the level of SCr and a history of diabetes or hyperlipidemia or with the type and location of prior cerebrovascular ischemic events. The Kaplan-Meier risk for the outcomes of stroke at 5 years, MI at 5 years, and the combined outcome of stroke, MI, or VD at 5 years increased with increasing levels of SCr (all at a p< 0.001, table). This increased risk was unconfounded and remained statistically significant after adjusting for all baseline characteristics using Cox proportional hazards regression model. The causes of stroke were similar in all SCr level groups (70% large artery, 22% lacunar, 8% cardioembolic). The risk of death from any cause at 5 years increased with increased SCr levels, cardiac disorders were the predominant cause of death. Conclusion: A mild to moderate elevation of serum creatinine level is an independent risk factor for stroke, MI, and VD in male patients with recent ischemic symptoms attributable to carotid artery stenosis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".