Systematic Review and Meta-Analysis of Case-Matched Studies Comparing Open and Laparoscopic Distal Pancreatectomy
Bibliographic record
Abstract
OBJECTIVES: Distal pancreatectomies and enucleations have become the most popular laparoscopic pancreatic resections and in some centers outnumber the traditional open approach. The aim of this study was to systematically review the literature on the safety of laparoscopic distal pancreatectomies (LDP) in relation to open distal pancreatectomies in the management of adult patients and, where possible, perform a meta-analysis of reported outcomes. METHODS: We searched MEDLINE, EMBASE, Web of knowledge, and the Cochrane Database of Systematic Reviews using the following keywords: pancreas, pancreatectomy, pancreatic, laparoscopic, laparoscopy. Publication dates and language restrictions were applied. The Newcastle Ottawa scale was used for study quality assessment. RESULTS: Four eligible studies were identified with a total of 665 patients. On average, LDPs had a longer operation time by 17.7 minutes (9.5%) and a reduced hospital stay by 2.7 days. Morbidity and mortality were low using both approaches. CONCLUSIONS: This study represents the strongest evidence (level 3a) to date that LDPs are a safe operation. However, there is still a need for randomized controlled trials to confirm this.
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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 | 0.017 | 0.061 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.028 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".