Warfarin Use in Hemodialysis Patients With Atrial Fibrillation: A Systematic Review of Stroke and Bleeding Outcomes
Bibliographic record
Abstract
BACKGROUND: Given the lack of clear indications for the use of warfarin in the treatment of atrial fibrillation (AF) in patients on hemodialysis and the potential risks that accompany warfarin use in these patients, we systematically reviewed stroke and bleeding outcomes in hemodialysis patients treated with warfarin for AF. OBJECTIVE: To systematically review the stroke and bleeding outcomes associated with warfarin use in the hemodialysis population to treat AF. DESIGN: Systematic review. SETTING: All adult hemodialysis patients. PATIENTS: Patients on hemodialysis receiving warfarin for the management of AF. MEASUREMENTS: Any type of stroke and/or bleeding outcomes. METHODS: MEDLINE(R) In-Process & Other Non-Indexed Citations and MEDLINE(R) via OVID (1946 to January 11, 2017), and EMBASE via OVID (1974 to January 11, 2017) were searched for relevant literature. Inclusion criteria were randomized controlled trials, observational studies, and case series in English that examined stroke and bleeding outcomes in adult population of patients (over 18 years old) who are on hemodialysis and taking warfarin for AF. Studies with less than 10 subjects, case reports, review articles, and editorials were excluded. Quality of selected articles was assessed using Newcastle-Ottawa Scale (NOS). RESULTS: Of the 2340 titles and abstracts screened, 7 met the inclusion criteria. Two studies showed an association between warfarin use and an increased risk of stroke (Hazard Ratio: 1.93-3.36) but no association with an increased risk of bleed (HR: 0.85-1.04), while 4 studies showed no association between warfarin and stroke outcomes (HR: 0.12-1.17) but identified an association between warfarin and increased bleeding outcome (HR: 1.41-3.96). And 1 study reported neither beneficial nor harmful effects associated with warfarin use. LIMITATIONS: The major limitation to this review is that the 7 included studies were observational cohort studies, and thus the outcome measures were not specified and predetermined in a research protocol. CONCLUSION: Our systematic review demonstrated that for patients with AF who are on hemodialysis, warfarin was not associated with reduced outcomes of stroke but was rather associated with increased bleeding events.
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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 | 0.007 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".