Low‐dose aspirin for prevention of cardiovascular disease in patients on hemodialysis: A 5‐y prospective cohort study
Bibliographic record
Abstract
Abstract Introduction Aspirin is an effective antiplatelet drug for preventing cardiovascular events in high‐risk subjects. However, for patients with chronic kidney disease and undergoing hemodialysis (HD), its preventive efficacy remains controversial. The present study aimed to determine whether aspirin therapy reduces the risk of cardiovascular disease (CVD) and all‐cause mortality in patients on HD. Methods We conducted a 5‐y prospective cohort study involving patients on HD. Major exposure variables included prescription of aspirin (100 mg/d) and no aspirin (nonaspirin). The primary outcomes included all‐cause death, cardiovascular events, hemorrhage, and ischemic stroke. The secondary outcome included bleeding events defined by the requirement of hospitalization. Findings In this study, 406 patients on regular HD were involved during a 5‐y follow‐up. Among these, 152 and 254 propensity‐matched patients were enrolled in the aspirin and nonaspirin cohort, respectively. The cumulative survival rate was not significantly higher in the aspirin than in the nonaspirin users (log rank χ2 = 1.080, P = 0.299). Aspirin use was not significantly associated with reduced all‐cause mortality, fatal and nonfatal congestive heart failure, as well as acute myocardial infarction and ischemic stroke. The risk of fatal cerebral hemorrhage was not significantly increased in the aspirin users (HR = 1.795, 95% CI 0.666–4.841, P = 0.174). After adjustment for other confounders, aspirin use was also not associated with decreased risk of all‐cause mortality and CVD. Discussion The present prospective cohort study suggests that low‐dose aspirin use is not associated with a significant decrease in the risks of all‐cause mortality, CVD, and stroke in population undergoing HD ( ClinicalTrials.gov number, NCT02261025).
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".