Timing of Lung Transplant Referral in Patients with Severe COVID-19 Lung Injury Supported by ECMO
Bibliographic record
Abstract
Severe respiratory failure caused by COVID-19 often requires mechanical ventilation, including extracorporeal membrane oxygenation (ECMO). In rare cases, lung transplantation (LTx) may be considered as a last resort. However, uncertainties remain about patient selection and optimal timing for referral and listing. This retrospective study analyzed patients with severe COVID-19 who were supported by veno-venous ECMO and listed for LTx between July 2020 and June 2022. Out of the 20 patients in the study population, four who underwent LTx were excluded. The clinical characteristics of the remaining 16 patients were compared, including nine who recovered and seven who died while awaiting LTx. The median duration from hospitalization to listing was 85.5 days, and the median duration on the waitlist was 25.5 days. Younger age was significantly associated with a higher likelihood of recovery without LTx after a median of 59 days on ECMO, compared to those who died at a median of 99 days. In patients with severe COVID-19-induced lung damage supported by ECMO, referral to LTx should be delayed for 8-10 weeks after ECMO initiation, particularly for younger patients who have a higher probability of spontaneous recovery and may not require LTx.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".