North American Neonatal Extracorporeal Membrane Oxygenation (ECMO) Devices: 2002 Survey Results
Bibliographic record
Abstract
In mid 2002, surveys of active extracorporeal membrane oxygenation (ECMO) centers in the United States and Canada were conducted via E-mail regarding neonatal equipment and personnel. Seventy-four out of 99 (75%) North American ECMO centers listed in the Extracorporeal Life Support Organization (ELSO) directory responded to the survey. Of the responding centers, 95% use roller pumps, and the remaining 5% use centrifugal pumps. Silicone membrane oxygenators were used by 97% of the respondents, while 3% used hollow fiber oxygenators. Of the silicone membrane oxygenator users, 82% used the Medtronic ECMOtherm heat exchanger, 15% used a Gish heat exchanger, and 3% used the Dideco D720 heat exchanger. Sixty-one percent of the responding centers used some form of in-line blood gas monitoring. Five percent of the centers used a bubble trap in the arterial line, and 12% used an arterial line filter. A bladder was used by 92% of the centers, and 29% used a mechanical bladder box for servo regulation, the remaining 71% used pressure servo regulation. An air bubble detector was used by 65% of the responding centers, although 81% had the device available. Heparin coating was used by 5% of the centers on all their neonatal ECMO patients. The average low range ACT was 183 seconds, and the average high range ACT was 216 seconds. At 49% of the responding centers, perfusionists were involved with the ECMO program, registered nurses were involved at 84% of the centers, and respiratory therapists were involved at 61% of the centers, perfusion assistants were involved at one center (1%), and biomedical engineers were involved at one of the centers. When compared to a 1990 survey, a shift away from using bladder boxes and toward using air bubble detectors is apparent. But other than those two shifts, ECMO is done in much the same manner as it was done 12 years ago.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".