Extracorporeal membrane oxygenation use in Trauma Quality Improvement Program centers: Temporal trends and future directions
Bibliographic record
Abstract
BACKGROUND: Increased clinical experience and the decreased need for systemic anticoagulation have renewed interest in the use of extracorporeal membrane oxygenation (ECMO) for posttraumatic respiratory and cardiopulmonary failure. The objectives of this study were to describe the incidence and temporal trends of ECMO use at trauma centers, the outcomes of trauma patients undergoing ECMO, and the characteristics of trauma centers providing ECMO. METHODS: Data were derived from the American College of Surgeons Trauma Quality Improvement Program data set. We included adults with at least one severe injury admitted to a level I or II trauma center between 2012 and 2016 who received at least 1 day of mechanical ventilation. Patients were categorized based on whether or not they received ECMO during their admission. The primary outcome was change in the incidence of ECMO across study years. We also evaluated patient outcomes and variation in ECMO volumes across centers. RESULTS: Of 194,314 severely injured patients undergoing mechanical ventilation across 450 centers, 269 (0.14%) received ECMO. Extracorporeal membrane oxygenation patients had significantly higher mortality than non-ECMO patients (32% vs. 19%). The standardized rate of ECMO from 2012 to 2016 increased significantly from 75.2 to 179.0 cases per 100,000 severely injured patients undergoing mechanical ventilation. The average annual growth rate was 24%. Of the 82 centers(18%) reporting at least 1 ECMO trauma case, 34 (41%) reported only a single case. CONCLUSION: The use of ECMO for trauma, although rare, is rapidly increasing. Two thirds of patients who receive ECMO following traumatic injury survive their hospitalization. These data suggest that ECMO represents a potential treatment strategy for trauma patients with respiratory or cardiopulmonary failure. However, given the rarity of the procedure, there exists an opportunity to develop practice guidelines regarding the indications for, and approach to, ECMO in the setting of trauma. LEVEL OF EVIDENCE: Therapeutic/care management, level IV.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".