Postoperative prophylactic anticoagulation in the prevention of portal venous thrombosis in patients after laparoscopic splenectomy: a Meta-analysis
Bibliographic record
Abstract
Objective To study the effectiveness and safety of prophylactic anticoagulation in the prevention of portal venous thrombosis (PVST) in patients after laparoscopic splenectomy. Methods A systematic search of the PubMed, Embase, Cochrane Library, Sinomed, Wangfang, Weipu and CNKI databases was performed to identify studies which compared outcomes in patients with or without prophylactic anticoagulation after laparoscopic splenectomy. The quality of the included studies was assessed using the Cochrane collaboration tool and the Newcastle-Ottawa Scale. Heterogeneity was evaluated using the χ2 and I2 tests. The primary outcome was the incidence of postoperative PVST. Results Five studies were included into this review, which involved 206 and 168 patients with or without prophylactic anticoagulation, respectively. The incidence of PVST was significantly reduced with prophylactic anticoagulation with an odds ratio (OR) of 0.32 [95% confidence interval (CI), 0.13~0.79, P<0.05]. Conclusion Prophylactic anticoagulation resulted in a significant reduced incidence of PVST after laparoscopic splenectomy. Key words: Portal vein system thrombosis; Anticoagulants; Laparoscopic splenectomy; Meta-analysis
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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 | 0.011 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.039 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".