Extracorporeal life support as bridge to lung transplantation: a systematic review
Bibliographic record
Abstract
INTRODUCTION: Patients with acute respiratory failure requiring respiratory support with invasive mechanical ventilation while awaiting lung transplantation are at a high risk of death. Extracorporeal membrane oxygenation (ECMO) has been proposed as an alternative bridging strategy to mechanical ventilation. The aim of this study was to assess the current evidence regarding how the ECMO bridge influences patients' survival and length of hospital stay. METHODS: We performed a systematic review by searching PubMed, EMBASE and the bibliographies of retrieved articles. Three reviewers independently screened citation titles and abstracts and agreement was reached by consensus. We selected studies enrolling patients who received ECMO with the intention to bridge lung transplant. We included randomized controlled trials (RCTs), case-control studies and case series with ten or more patients. Outcomes of interest included survival and length of hospital stay. Quantitative data summaries were made when feasible. RESULTS: We identified 82 studies, of which 14 were included in the final analysis. All 14 were retrospective studies which enrolled 441 patients in total. Because of the broad heterogeneity among the studies we did not perform a meta-analysis. The mortality rate of patients on ECMO before lung transplant and the one-year survival ranged from 10% to 50% and 50% to 90%, respectively. The intensive care and hospital length of stay ranged between a median of 15 to 47 days and 22 to 47 days, respectively. There was a general paucity of high-quality data and significant heterogeneity among studies in the enrolled patients and technology used, which confounded analysis. CONCLUSIONS: In most of the studies, patients on ECMO while awaiting lung transplantation also received invasive mechanical ventilation. Therefore, whether ECMO as an alternative, rather than an adjunction, to invasive mechanical ventilation is a better bridging strategy to lung transplantation still remains an unresolved issue. ECMO support as a bridge for these patients could provide acceptable one-year survival. Future studies are needed to investigate ECMO as part of an algorithm of care for patients with end-stage lung disease.
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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 | 0.007 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".