Safety and Efficacy of Anti-Fibrinolytics in Orthopedic Surgery: A Meta-Analysis of Randomized Trials.
Bibliographic record
Abstract
Abstract Background: Minimizing blood transfusions following elective orthopedic procedures is desirable given the risks associated with transfusion, including cost, infection, and allergic reactions. Anti-fibrinolytic agents may reduce perioperative blood loss but are used infrequently possibly due to a lack of data supporting their efficacy and concerns about increased risks for venous thromboembolism (VTE). We performed a meta-analysis to determine whether anti-fibrinolytic agents reduce perioperative blood loss in patients undergoing total hip replacement (THR) or total knee arthroplasty (TKA). Data sources: MEDLINE (1966 to May Week 3 2006), EMBASE (1980 to 2006 Week 21), Cochrane Database of Systematic Reviews, ACP Journal Club, Database of Abstracts of Reviews of Effects, and Cochrane Central Register of Controlled Trials (the latter four databases to May 29, 2006) were searched. Additional trials were identified by manual searches. Authors and/or pharmaceutical companies were contacted if required. Study selection was based on the following criteria: prospective randomized clinical trials in which tranexamic acid, epsilon-aminocaproic acid, or aprotinin were administered. Two independent reviewers abstracted transfusion requirements, total blood loss, and venous thromboembolism. Study quality was assessed using the Jadad Quality Assessment scale. Data was pooled using the Mantel-Haenszel method and a random effects model. Results: In 25 studies involving 1332 patients, the weighted mean difference (WMD) in total blood loss in patients treated with anti-fibrinolytic agents compared to patients receiving placebo was −409.50 mL (95%CI, −548.17 to −270.82; P< 0.00001, I2 = 89.6%). In 1557 patients, the relative risk (RR) for transfusion was 0.52 (95%CI, 0.42 to 0.64; P<0.00001, I2 = 58.0%). VTE did not appear to be increased in patients who received anti-fibrinolytic agents (RR 0.972 (95%CI, 0.885 to 1.06). Conclusions: Patients undergoing TKR or THA who receive anti-fibrinolytic agents appear to have reductions in blood loss and need for transfusion. Whether these medications increase VTE risk cannot be determined due to limited data. Study characteristics were heterogeneous and the optimal timing, dose, and type of anti-fibrinolytic therapy have yet to be determined. Further studies in this area are warranted.
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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 | 0.030 | 0.058 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.051 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".