Minimizing bleeding and transfusion in single-stage bilateral hip and knee arthroplasty: A systematic review of current interventions
Bibliographic record
Abstract
OBJECTIVES: To evaluate perioperative strategies for minimizing bleeding and transfusion needs in single-stage bilateral hip and knee arthroplasty. This systematic review identifies effective interventions and provides evidence-based recommendations and highlight areas for future research in optimizing bleeding management. METHODS: A systematic review of literature from January 2010 to October 2024 was conducted, focusing on randomized controlled trials (RCTs), meta-analyses, and guidelines. Databases searched included PubMed/MEDLINE, Embase, Cochrane Library, and Web of Science. Interventions assessed included tranexamic acid (TXA), surgical techniques, regional anesthesia, controlled hypotension, preoperative anemia correction, tourniquet use, bone wax, and restrictive transfusion strategies. Study selection, data extraction, and quality assessment followed PRISMA and Newcastle-Ottawa Scale guidelines. RESULTS: From 325 included studies, TXA consistently demonstrated the most significant impact, reducing transfusion rates by 40-60%. Anterior THA was associated with reduced blood loss. Regional anesthesia and controlled hypotension further minimized intraoperative bleeding. Preoperative anemia correction and restrictive transfusion thresholds also showed benefits. Tourniquet evidence was inconclusive. Limited evidence supported bone wax. GRADE assessment suggested high evidence quality for TXA and regional anesthesia, moderate for minimally invasive surgery, anemia correction, and restrictive transfusion, and low for bone wax. CONCLUSIONS: Multimodal approach integrating TXA, regional anesthesia, minimally invasive surgery, anemia correction, and restrictive transfusion protocols effectively reduces bleeding and transfusion needs in bilateral arthroplasty. Incorporation into Enhance recovery after surgery (ERAS) protocols is recommended. Future research should refine TXA dosing, clarify tourniquet use, and assess cost-effectiveness.
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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 | 0.008 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.011 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".