185: THE ECMO HOUR: A NOVEL MULTIDISCIPLINARY EDUCATIONAL CURRICULUM
Bibliographic record
Abstract
Introduction: Successful extracorporeal membrane oxygenation (ECMO) therapy requires ongoing education for the multidisciplinary team. Ensuring all team members receive consistent, evidence-based education is challenging. To address this, Boston Children’s Hospital ECMO program implemented a monthly curriculum called “The ECMO Hour,” featuring 13 unique, 1-hour presentations on pediatric ECMO care. The sessions included case-based scenarios, literature reviews, and expert discussions, using multiple-choice questions and spaced-repetition to enhance long-term understanding. This study evaluates the curriculum’s impact on participants’ knowledge and perceived comfort levels. Methods: An anonymized pre- and post-assessment survey was conducted via Survey Monkey. QR codes were provided during presentations, with reminder emails sent to attendees. Descriptive statistics compared pre/post self-efficacy and attitudinal data. Results: 23 participants completed the pre-assessment survey, and 31 completed the post-assessment (January 2023 and June 2024). Most respondents were physicians (51.8%) or ECMO specialists (20.3%), with the majority having less than six years of ICU and ECMO experience (53 and 58%). Participants reported increased knowledge in membrane gas exchange and physiology (41.9%), oxygen content, delivery, and consumption (33.3%), ECMO pharmacology (41.9%), and ECMO mode and physiology (35.5%). Favorite topics included anticoagulation (20%), gas exchange on ECMO (17%), and ECMO pharmacology (13.3%). Confidence increased in identifying ECMO candidates (70% to 94%), managing circuit problems (48% to 83%), assessing readiness for decannulation (61% to 90%), and understanding weaning and decannulation (60% to 93%). Conclusion: The ECMO Hour curriculum enhanced understanding and bolstered confidence in essential ECMO concepts, better preparing participants to care for ECMO patients.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".