Anticoagulation Practices during Venovenous Extracorporeal Membrane Oxygenation for Respiratory Failure. A Systematic Review
Bibliographic record
Abstract
BACKGROUND: The optimal anticoagulation strategy for venovenous extracorporeal membrane oxygenation (VV-ECMO) is not known. OBJECTIVES: To evaluate the safety of anticoagulation strategies and monitoring during VV-ECMO for respiratory failure. DATA SOURCES: We conducted a systematic review to evaluate the association between anticoagulation strategies during VV-ECMO and prespecified outcomes, including major bleeding episodes, thrombotic events, and in-hospital mortality. We included articles published between 1977 and January 30, 2015. Study quality was assessed using the Newcastle-Ottawa scoring system. A separate meta-analysis was not planned. DATA EXTRACTION: Data were independently extracted by two authors and collected on a standardized report form. SYNTHESIS: A total of 18 studies (n = 646) were included; 17 studies enrolled patients with acute respiratory distress syndrome. Across all studies, the duration of VV-ECMO support ranged from 4 to 20 days. Patients received an average of 2.3 (±3.9) units of transfused red blood cells per day. The bleeding rate across all studies was 16%, and the rate of thrombosis was 53%. Among seven studies (199 patients) targeting a specified activated partial thromboplastin time (aPTT), there were 37 (19%) major bleeding episodes and 53 (27%) major thromboses. Among five studies (43 patients) with aPTT targets of 60 seconds or greater, there were 24 (56%) bleeding episodes and 3 (7%) clotting events. Three studies (156 patients) with an aPTT target under 60 seconds reported 13 (8%) and 50 (32%) significant bleeding and thrombotic events, respectively. The most commonly reported thrombotic events were circuit-related clotting and deep-vein thrombosis. Mortality during VV-ECMO varied across the studies, ranging from 0 to at least 50% at heterogeneous time points. The total number of deaths for all studies combined was 186 (29%). CONCLUSIONS: The role and optimal therapeutic targets for anticoagulation during VV-ECMO are unclear. Previously published studies are limited by retrospective, observational design, small cohorts, and patient heterogeneity. The clinical significance of reported thrombotic complications is largely unknown. This systematic review underscores the need for randomized controlled trials of anticoagulation strategies for patients undergoing VV-ECMO for respiratory failure.
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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 | 0.009 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".