Safety and Efficacy of Low Molecular Weight Heparins for Hemodialysis in Patients with End-Stage Renal Disease: A Meta-Analysis of Randomized Trials.
Bibliographic record
Abstract
Abstract Background: The anticoagulant management of patients with thromboembolic disease who also have end-stage renal disease is a frequently encountered and unresolved clinical problem. Low molecular weight heparins (LWMHs) are the preferred initial treatment for these disorders but are renally excreted, and generally avoided in patients with renal failure due to concerns of bioaccumulation and increased bleeding risks. Unfractionated heparin (UFH) remains the primary anticoagulant used in this patient population despite the efficacy and convenience of LMWHs. Although LMWHs are typically not used to treat thrombosis in patients with end-stage renal disease, they are frequently used during hemodialysis to prevent thrombosis of the extracorporeal dialysis circuit. While there are no randomized data evaluating the safety and efficacy of LMWHs in these patients, randomized trials have been performed using LMWHs in the setting of hemodialysis. We performed a systematic review and meta-analysis of these randomized trials summarizing this data. Purpose: To evaluate the safety and efficacy of LMWHs compared to UFH for preventing thrombosis of the extracorporeal dialysis circuit. Data sources: We identified studies using MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials and FirstSearch, reviewed reference lists and contacted pharmaceutical companies. Study selection: We included randomized, controlled trials that compared a LMWH with another anticoagulant during hemodialysis in patients with end-stage renal disease, and reported at least one of the following outcomes: bleeding, extracorporeal circuit thrombosis, or anti-Xa levels. Data extraction: Two reviewers independently extracted data on methodologic quality, study design, clinical outcomes, and anti-Xa levels. Data synthesis: We included 17 trials in this systematic review, 11 of which were included in the meta-analysis. We found that LMWH did not significantly affect the number of bleeding events (relative risk [RR] 0.96, 95% CI, 0.27 to 3.43), bleeding assessed by vascular access compression time (weighted mean difference −0.87, 95% CI, −2.75 to 1.02) or extracorporeal circuit thrombosis (RR 1.15, 95% CI, 0.70 to 1.91) as compared with UFH. Conclusions: LMWHs appear to be as safe as UFH in terms of bleeding complications, and as effective as UFH in preventing extracorporeal circuit thrombosis. However, inferences from these trials assessing anticoagulation for patients undergoing hemodialysis will continue to be weak until larger, more rigorous randomized trials are conducted.
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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 | 0.018 | 0.038 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.045 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".