Clinical and Surgical Strategies for Avoiding or Reducing Allogeneic Blood Transfusions
Bibliographic record
Abstract
Blood transfusions have still been used as a standard therapy to treat severe anemia. Current evidences point to both excessive allogeneic blood consumption and decreased donations, which result in reduced stocks in blood banks. Several studies have increasingly suggested a more restrictive transfusion practice for blood products. Currently, a number of autologous blood conservation protocols in surgeries have been noted. We report a case of severe anemia with 2.9 g/dL hemoglobin, which was successfully handled without using the standard therapy to treat anemia with hemotransfusions. Such a case of severe anemia condition resulted after the patient was submitted to ascending aortic aneurism repair, valvar aortic replacement, reimplantation of right coronary ostium, followed by a coronary artery bypass grafting and several postoperative complications. The main clinical and surgical strategies used in this case to avoid blood transfusions were acute normovolemic hemodilution, intraoperative blood cell salvage, and meticulous hemostasis, beyond epsilon-aminocaproic acid, desmopressin, prothrombin complex concentrate, human fibrinogen concentrate, factor VIIa recombinant, erythropoietin and hyperoxic ventilation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".