Restrictive Versus Liberal Transfusion Strategy in Extracorporeal Membrane Oxygenation
Bibliographic record
Abstract
Abstract Background: To compare the clinical outcomes of patients requiring extracorporeal membrane oxygenation (ECMO) support who had a restrictive red cell transfusion strategy with those who had a liberal transfusion strategy. Methods: We retrospectively reviewed all adult ECMO cases in Hong Kong from 2010 to 2019. Patients who received a minimum of one packed red blood cell (pRBC) during ECMO were included. Haemoglobin values before each episode of transfusion was retrieved. Restrictive transfusion strategy was defined as a transfusion threshold ≤ 8.5 g/dL in all transfusion episodes for a single patient, while liberal transfusion strategy was defined as a transfusion threshold > 8.5 g/dL in any transfusion episode. Mortality outcomes and other complications were compared.Results: The analysis included 763 patients, with 138 (18.1%) patients in the restrictive and 625 (81.9%) in the liberal transfusion strategy group, and median haemoglobin of 8.3 and 9.9 g/dL, respectively. The average units of pRBC received per day were 0.7 (0.3-1.8) and 1.2 (0.6-2.3) in the two groups. There were no significant differences in ICU mortality (adjusted odds ratio (OR), 0.86; 95% CI 0.56-1.30; P=0.47), hospital mortality (adjusted OR, 0.79; 95% CI 0.52 to 1.21; P=0.28), and 90-day mortality (adjusted OR, 0.84; 95% CI 0.55 to 1.28; P=0.42) between the two groups. Among patients receiving veno-venous ECMO, the ICU mortality was significantly lower with the restrictive transfusion strategy (adjusted OR, 0.36; 95% CI 0.17 - 0.73; P=0.005). Conclusions: Compared with a liberal transfusion strategy, a restrictive red blood cell transfusion threshold of 8.5 g/dL was not associated with worse outcomes in patients on ECMO, with better survival outcomes for patients on veno-venous ECMO.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".