Intracranial hemorrhage on extracorporeal membrane oxygenation: an international survey
Bibliographic record
Abstract
Introduction: Intracranial hemorrhage is one of the most dreaded complications associated with extracorporeal membrane oxygenation. However, robust data to guide clinical practice are lacking. We aimed to describe the current perceptions and practices surrounding the risk, prevention, diagnosis, management, and prognosis of intracranial hemorrhage in patients on extracorporeal membrane oxygenation. Methods: We conducted an international, cross-sectional survey of adult extracorporeal membrane oxygenation centers using a self-administered electronic questionnaire sent to medical directors and program coordinators of all 290 adult centers member of the Extracorporeal Life Support Organization. Results: There were 143 respondents (49%). The median proportion of patients having neuroimaging performed was only 1-25% in venovenous-extracorporeal membrane oxygenation patients and 26-50% in venoarterial-extracorporeal membrane oxygenation and extracorporeal cardiopulmonary resuscitation. The majority of participants (58%) tolerated a PaO 2 < 60 mm Hg on venovenous-extracorporeal membrane oxygenation. Lower PaO 2 targets were inversely correlated with the reported incidence of intracranial hemorrhage (r =−0.247; p = 0.024). In patients with intracranial hemorrhage, most participants reported stopping anticoagulation, and median targets for blood product administration were 70,000-99,000 platelets/µL, 1.5-1.9 of international normalized ratio, and 1.6-2.0 g/L of fibrinogen. Conclusion: We found significant heterogeneity in the perceptions and practices. This underlines the need for more research to appropriately guide patient management. Importantly, neuroimaging was performed only in a minority of patients. Considering the important management implications reported by most centers when intracranial hemorrhage is diagnosed, perhaps clinicians should consider widening their indications for early neuroimaging.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".