Timing of Perioperative Pharmacologic Thromboprophylaxis Initiation and its Effect on Venous Thromboembolism and Bleeding Outcomes: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Perioperative thromboprophylaxis guidelines offer conflicting recommendations on when to start thromboprophylaxis. As a result, there is considerable variation in clinical practice, which can lead to worse patient outcomes. The objective of this study was to evaluate the association between the start time of perioperative thromboprophylaxis with venous thromboembolism (VTE) and bleeding outcomes. STUDY DESIGN: Embase, Medline, and CENTRAL (Cochrane Central Register of Controlled Trials) databases were searched on October 23, 2020. Randomized controlled trials that evaluated VTE and/or bleeding among groups receiving the initial dose of pharmacologic thromboprophylaxis at different times preoperatively, intraoperatively, or postoperatively were included. Only trials that randomized patients to the same medication among groups were eligible. Studies on any type of operation were included. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed. The Cochrane Collaboration risk of bias tool was used. The review was registered with PROSPERO (International Prospective Register of Systematic Reviews; CRD42019142079). The outcomes of interest were VTE and bleeding. Prespecified subgroup analyses of studies including orthopaedic and nonorthopaedic operations were performed. RESULTS: A total of 22 trials (n = 17,124 patients) met eligibility criteria. Pooled results showed a nonstatistically significant decrease in the rate of VTE with preoperative initiation of thromboprophylaxis compared with postoperative initiation (risk ratio 0.77; 95% CI, 0.55 to 1.08; I 2 = 0%, n = 1,933). There was also a nonstatistically significant increase in the rate of bleeding with preoperative compared with postoperative initiation (risk ratio 1.17; 95% CI, 0.94 to 1.46; I 2 = 35%, n = 2,752). Risk of bias was moderate. Heterogeneity between studies was low (I 2 = 0% to 35%). CONCLUSIONS: This meta-analysis found a nonstatistically significant decrease in the rate of VTE and an increase in the rate of bleeding when thromboprophylaxis was initiated preoperatively compared with postoperatively.
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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 | 0.012 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.040 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".