S2871 Evaluating the Efficacy and Safety of Hypovolemic Phlebotomy in Patients With Liver Surgery: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Introduction: Significant blood loss is common in major liver surgery, heightening the need for transfusions and increasing postoperative risks. Hypovolemic phlebotomy (HP) has surfaced as an effective method to reduce bleeding by decreasing central venous pressure, all without the need for volume replacement. This meta-analysis examines the safety and effectiveness of HP in reducing blood loss during liver resection. Methods: From inception until March 2025, a comprehensive literature review was performed using PubMed, Cochrane Central, and ScienceDirect. Risk ratios (RR) and weighted mean differences (WMD) for both categorical and continuous outcomes were aggregated utilizing the random effects model in Review Manager software version 5.4.1. A sensitivity analysis, which excluded one study at a time, was executed to evaluate heterogeneity. The assessment of quality was conducted using the Cochrane risk of bias tool and the Newcastle-Ottawa scale. Results: This meta-analysis includes 8 studies with a total of 1,901 patients. In the HP group, blood loss is significantly lower compared to the placebo group (MD: -440.13 mL; 95% CI: [-756.20, -124.07]; P = 0.006). The HP arm also sees a notable decrease in hospital stay length (MD = -15.98 days; 95% CI: [-21.36, -10.60]; P < 0.01). Other measures, including red blood cell transfusion (RR = 0.60; 95% CI:[0.35, 1.04]; P = 0.07), major complications (RR = 1.40; 95% CI: [0.93, 2.13]; P = 0.11), and overall complications (RR = 1.15; 95% CI: [0.86, 1.53]; P = 0.35), show comparable results between both groups. Conclusion: HP greatly minimizes blood loss during liver resection surgery and shortens hospital stays for patients while avoiding an increase in transfusion requirements or complications, demonstrating its safety and efficacy. Additional research could further enhance its implementation in clinical settings.
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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 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.035 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".