Risk factors for postoperative bleeding following endoscopic submucosal dissection in early gastric cancer: A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Early gastric cancer (EGC) presents a significant challenge in surgical management, particularly concerning postoperative bleeding following endoscopic submucosal dissection. Understanding the risk factors associated with postoperative bleeding is crucial for improving patient outcomes. METHODS: Adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, a systematic review and meta-analysis were conducted across PubMed, Embase, Web of Science, and the Cochrane Library without publication date restrictions. The inclusion criteria encompassed observational studies and randomized controlled trials focusing on EGC patients undergoing endoscopic submucosal dissection and their risk factors for postoperative bleeding. The Newcastle-Ottawa Scale was utilized for quality assessment. The effect size was calculated using random or fixed-effects models based on the observed heterogeneity. We assessed the heterogeneity between studies and conducted a sensitivity analysis. RESULTS: In our meta-analysis, 6 studies involving 4868 EGC cases were analyzed. The risk of postoperative bleeding was notably increased with intraoperative ulcer detection (odds ratio: 1.97, 95% confidence interval [CI]: 1.03-3.76, I2 = 61.0%, P = .025) and antithrombotic medication use (odds ratio: 2.02, 95% CI: 1.16-3.51, I2 = 57.2%, P = .039). Lesion resection size showed a significant mean difference (5.16, 95% CI: 2.97-7.98, P < .01), and longer intraoperative procedure time was associated with increased bleeding risk (mean difference: 11.69 minutes, 95% CI: 1.82-26.20, P < .05). Sensitivity analysis affirmed the robustness of these findings, and publication bias assessment indicated no significant bias. CONCLUSIONS: In EGC treatment, the risk of post-endoscopic submucosal dissection bleeding is intricately linked to factors like intraoperative ulcer detection, antithrombotic medication use, the extent of lesion resection, and the length of the surgical procedure. These interwoven risk factors necessitate careful consideration and integrated management strategies to enhance patient outcomes and safety in EGC surgeries.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.012 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".