Extracorporeal Membrane Oxygenation as “Bridge” to Lung Transplantation: What Remains in Order to Make It Standard of Care?
Bibliographic record
Abstract
Since its introduction into clinical practice, lung transplantation (LTx) is gradually becoming a worldwide standard treatment for patients with a broad spectrum of end-stage respiratory diseases (1–3). From 1995 to 2010, more than 30,000 LTx have been performed, and it is worth noting that in recent years the number of LTx has been progressively increasing to more than 3,000/year in 2010, with a post-transplant graft half-life that went from 4.7 in the 1990s to 5.9 in the new millennium (4). However, the crude mortality rate of patients awaiting LTx is higher than mortality for other solid organs. Mortality rate in 2009 for patients on the waiting list for LTx was about 14.1% in North America (www.srtr.org) and 14.7% in Italy (www.airt.it). What are the reasons for these unacceptable mortality rates? First, patients have to wait for the graft longer than patients waiting for other organs because of the small number of lungs suitable for transplantation (5). Second is the lack of supportive therapies that are able to replace respiratory function when the primary pulmonary diseases evolve from “respiratory insufficiency” to “respiratory failure,” characterized by refractory hypoxemia and hypercapnia.
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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 | 0.019 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.008 | 0.014 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.007 | 0.012 |
| Insufficient payload (model declined to judge) | 0.009 | 0.005 |
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".