The Association of Atrial Fibrillation and Ischemic Stroke in Patients on Hemodialysis: A Competing Risk Analysis
Bibliographic record
Abstract
BACKGROUND: Stroke is common in patients with end-stage renal disease (ESRD) treated with hemodialysis (HD) and associated with high mortality rate. In the general population, atrial fibrillation (AF) is a major risk factor for stroke and therapeutic anticoagulation is associated with risk reduction, whereas in ESRD the relationship is less clear. OBJECTIVE: The purpose of this study is to demonstrate the influence of AF on stroke rates and probability in those on HD following competing risk analyses. DESIGN: A national record linkage cohort study. SETTING: All renal and stroke units in Scotland, UK. PATIENTS: All patients with ESRD receiving HD within Scotland from 2005 to 2013 (follow-up to 2015). MEASUREMENTS: Demographic, clinical, and laboratory data were linked between the Scottish Renal Registry, Scottish Stroke Care Audit, and hospital discharge data. Stroke was defined as a fatal or nonfatal event and mortality derived from national records. METHODS: Associations for stroke were determined using competing risk models: the cause-specific hazards model and the Fine and Gray subdistribution hazards model accounting for the competing risk of death in models of all stroke, ischemic stroke, and first-ever stroke. RESULTS: Of 5502 patients treated with HD with 12 348.6-year follow-up, 363 (6.6%) experienced stroke. The stroke incidence rate was 26.7 per 1000 patient-years. Multivariable regression on the cause-specific hazard for stroke demonstrated age, hazard ratio (HR) (95% confidence interval [CI]) = 1.04 (1.03-1.05); AF, HR (95% CI) = 1.88 (1.25-2.83); prior stroke, HR (95% CI) = 2.29 (1.48-3.54), and diabetes, HR (95% CI) = 1.92 (1.45-2.53); serum phosphate, HR (95% CI) = 2.15 (1.56-2.99); lower body weight, HR (95% CI) = 0.99 (0.98-1.00); lower hemoglobin, HR (95% CI) = 0.88 (0.77-0.99); and systolic blood pressure (BP), HR (95% CI) = 1.01 (1.00-1.02), to be associated with an increased stroke rate. In contrast, the subdistribution HRs obtained following Fine and Gray regression demonstrated that AF, weight, and hemoglobin were not associated with stroke risk. In both models, AF was significantly associated with nonstroke death. LIMITATIONS: Our analyses derive from retrospective data sets and thus can only describe association not causation. Data on anticoagulant use are not available. CONCLUSIONS: The incidence of stroke in HD patients is high. The competing risk of "prestroke" mortality affects the relationship between AF and risk of future stroke. Trial designs for interventions to reduce stroke risk in HD patients, such as anticoagulation for AF, should take account of competing risks affecting associations between risk factors and outcomes.
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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 | 0.015 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".