A Scoping Review of Alternative Anticoagulation Strategies for Hemodialysis Patients with a Mechanical Heart Valve
Bibliographic record
Abstract
INTRODUCTION: Patients with end-stage renal disease (ESRD) have high rates of cardiac valvulopathy but can develop contraindications for vitamin K antagonist (VKA) therapy. We explored the evidence for alternative anticoagulation strategies in patients with ESRD with a contraindication for VKA therapy. METHODS: A scoping review was completed, searching MEDLINE, Embase, Cochrane Central Register of Controlled Trials, Web of Science, and Conference abstracts from inception to March 30, 2021. The study population was patients with ESRD who were on VKA therapy and developed a contraindication to VKA therapy use. All data regarding studies, patient characteristics, anticoagulation strategy, and clinical outcomes were summarized. RESULTS: Twenty-three articles met inclusion criteria. These articles included 57 patients. Contraindications to VKA therapy included calcific uremic arteriolopathy (CUA) (n = 55) and warfarin-induced skin necrosis (n = 2). All studies were either case reports or case series. There were 10 anticoagulation strategies identified. Continuation of VKA therapy was associated with increased death and decreased rates of CUA resolution (80.0% and 10.0%, respectively), compared to apixaban (24.0% and 70.8%), subcutaneous (SC) low-molecular-weight heparin (LMWH) (14.3%, 85.7%), and SC unfractionated heparin (0.0%, 100.0%). While only 5 patient cases were reported with mechanical heart valves, SC LMWH use has been reported in this context with good outcomes. CONCLUSIONS: In patients with ESRD who develop a contraindication to VKA therapy, several alternative anticoagulation strategies have been reported with superior outcomes to VKA continuation. While outcomes appear superior to continuation of VKA therapy, more data are required before definitive recommendations can be made for the patient with ESRD and a mechanical heart valve.
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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 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.014 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".