Prognostic Factors Associated With Intracranial Hemorrhage and Ischemic Stroke During Venovenous Extracorporeal Membrane Oxygenation: A Systematic Review
Bibliographic record
Abstract
OBJECTIVES: Venovenous extracorporeal membrane oxygenation (ECMO) is a life-preserving intervention for patients with respiratory failure refractory to conventional mechanical ventilation. Intracranial hemorrhage (ICH) and ischemic stroke are life-threatening complications associated with venovenous ECMO. Despite this, little is known regarding the prognostic factors associated with these adverse neurologic events. We conducted a systematic review that characterizes these predictors of ICH and ischemic stroke during venovenous ECMO. DATA SOURCES: We conducted a comprehensive search of MEDLINE and Embase via the Ovid interface. STUDY SELECTION: We developed and performed a literature search to identify articles that evaluated ICH and ischemic stroke in adult patients undergoing venovenous ECMO. We excluded studies based on design, target population, and outcomes. DATA EXTRACTION: Data were extracted manually by one reviewer. Risk of bias assessment was completed using the Quality in Prognostic Studies approach for each included study. Prognostic factors associated with ICH and ischemic stroke that were identified in two or more included studies were evaluated through the Grading of Recommendations, Assessment, Development, and Evaluation approach. DATA SYNTHESIS: Three hundred thirty-three studies met criteria for screening. Seventeen studies met final inclusion criteria. Seventeen studies addressed predictors of ICH. Five studies demonstrated an increased risk of ICH with lower pH before venovenous ECMO (moderate certainty). Five studies demonstrated an increased risk of ICH with greater decreases in Pa co2 pre- to post-venovenous ECMO cannulation (moderate certainty). Four studies addressed predictors of ischemic stroke; however, there were no predictors of ischemic stroke identified in two or more of the included studies. CONCLUSIONS: This systematic review demonstrates that abnormalities and changes in blood gas parameters from pre- to post-venovenous ECMO cannulation are probably associated with increased risk of ICH. Additional high-quality studies dedicated to probable predictors of these adverse neurologic events are crucial to understanding the pathophysiology of ICH and ischemic stroke in this population and informing clinical practice to mitigate the risk of these life-threatening 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 | 0.009 | 0.050 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.009 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".