ERAS Cardiac Society turnkey order set for patient blood management: Proceedings from the AATS ERAS Conclave 2023
Bibliographic record
Abstract
OBJECTIVES: There are multiple published guidelines on comprehensive patient blood management (PBM), centered on the 3 pillars of PBM: managing preoperative anemia, minimizing blood loss, and tolerating intraoperative/postoperative anemia. We sought to create an order set to facilitate widespread implementation of evidence-based PBM for cardiac surgery patients. METHODS: Subject matter experts were consulted to translate existing guidelines and literature into a sample turnkey order set (TKO) for PBM. Orders derived from consistent class I, class IIA, or equivalent recommendations across referenced guidelines and consensus manuscripts appear in the TKO in bold type. Selected orders that were inconsistently class I or IIA, class IIB, or supported by published evidence are presented in italic type. RESULTS: Preoperatively, there are strong recommendations to screen and treat preoperative anemia with iron replacement and erythropoietin and to discontinue dual antiplatelet therapy if the patient can safely wait for surgery. Intraoperative orders outline the routine use of an antifibrinolytic agent, cell saver, point of care viscoelastic testing, and use of a standard transfusion algorithm. The order set also reflects strong recommendations intraoperatively and postoperatively for agreed-upon hemoglobin thresholds to consider transfusion of packed red blood cells. A hemoglobin threshold should be adopted according to local team consensus and should trigger a discussion regarding transfusion. CONCLUSIONS: The benefit of a multidisciplinary PBM care pathway in cardiac surgery has been well established, yet implementation remains variable. Using recommendations from existing guidelines, we have created a TKO to facilitate the implementation of PBM.
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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 | 0.019 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.011 |
| Insufficient payload (model declined to judge) | 0.016 | 0.005 |
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".