Brazilian guidelines for the management of brain-dead potential organ donors. The task force of the Associação de Medicina Intensiva Brasileira, Associação Brasileira de Transplantes de Órgãos, Brazilian Research in Critical Care Network, and the General Coordination of the National Transplant System
Bibliographic record
Abstract
OBJECTIVE: To contribute to updating the recommendations for brain-dead potential organ donor management. METHODS: A group of 27 experts, including intensivists, transplant coordinators, transplant surgeons, and epidemiologists, answered questions related to the following topics were divided into mechanical ventilation, hemodynamics, endocrine-metabolic management, infection, body temperature, blood transfusion, and checklists use. The outcomes considered were cardiac arrests, number of organs removed or transplanted as well as function / survival of transplanted organs. The quality of evidence of the recommendations was assessed using the Grading of Recommendations Assessment, Development, and Evaluation system to classify the recommendations. RESULTS: A total of 19 recommendations were drawn from the expert panel. Of these, 7 were classified as strong, 11 as weak and 1 was considered a good clinical practice. CONCLUSION: Despite the agreement among panel members on most recommendations, the grade of recommendation was mostly weak.
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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 | 0.036 | 0.096 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.007 |
| Bibliometrics | 0.011 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.006 | 0.002 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".