MiECC should not be restricted to selected patients and experienced teams. A MiECTiS rebuttal to 2024 EACTS/EACTAIC/EBCP guidelines on patient blood management
Bibliographic record
Abstract
Dear Editor, We read with great interest the recently published 2024 EACTS/EACTAIC guidelines on patient blood management in adult cardiac surgery produced in collaboration with EBCP [1]. Whilst we are supportive of most of the recommendations in the updated guideline, we, the undersigned as Board members of the ‘Minimal Invasive Extracorporeal Technologies International Society’ (MiECTiS), raise concerns regarding section 4.2.3, ‘Minimally invasive extracorporeal circulation circuit’ (MiECC). We strongly feel that the evidence used is outdated, incomplete and of low scientific merit, leading to erroneous recommendations. Please find our objections listed below: Based on these facts, we strongly consider that the concluding statement ‘MiECC applies to selected patients and experienced teams’ is misleading for the readers; we would highly recommend a review of the whole section for scientific integrity and a guideline recommendation supported by best evidence. Conflict of interest: none declared. The data underlying this article will be shared on reasonable request to the corresponding author.
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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 | 0.002 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.038 | 0.033 |
| Insufficient payload (model declined to judge) | 0.020 | 0.012 |
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".