Non-pharmacological strategies for blood conservation in cardiac surgery.
Bibliographic record
Abstract
PURPOSE: Of all surgical specialties, cardiac operations are most often associated with coagulopathy, blood loss, and the need for transfusions. This not only represents a major burden on blood procurement and banking organizations at all levels, but also constitutes a risk for each patient receiving allogeneic blood products. This paper reviews current non-pharmacological strategies aimed at decreasing blood use in patients undergoing cardiac surgery. SOURCE: The literature pertaining to each blood conservation strategy was searched, reviewed, and appraised. Meta- analyses were also consulted and their results complemented with subsequent reports when available. PRINCIPAL FINDINGS: Preoperative autologous donation programs are effective in decreasing allogeneic transfusions, but are costly and applicable to elective patients only. Off-pump revascularization strategies also appear to decrease transfusion requirements in suitable patients. The effectiveness of acute normovolemic hemodilution, retrograde autologous priming, small volume cardiopulmonary bypass circuits, platelet-rich plasmapheresis, alternative heparin strategies, and postoperative cell salvage are more difficult to appraise as a high proportion of available studies suffer from lack of transfusion guidelines or the absence of blinding. Biological glues, surgical adhesives, and postoperative increases in positive end-expiratory pressure (PEEP) have no demonstrated efficacy. CONCLUSION: The applicability or effectiveness of many of these modalities remains controversial and more studies are needed before they may be employed routinely in cardiac surgical patients. The judicious use of rational transfusion guidelines may still be the simplest and most cost-effective means of blood conservation today.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".