Systematic review and meta-analysis of cost-effectiveness of minimally invasive versus open pancreatic resections
Bibliographic record
Abstract
Abstract Background The systematic review is aimed to evaluate the cost-effectiveness of minimally invasive surgery (MIS) and open distal pancreatectomy and pancreaticoduodenectomy. Method The MEDLINE, CENTRAL, EMBASE, Centre for Reviews and Dissemination, and clinical trial registries were systematically searched using the PRISMA framework. Studies of adults aged ≥ 18 year comparing laparoscopic and/or robotic versus open DP and/or PD that reported cost of operation or index admission, and cost-effectiveness outcomes were included. The risk of bias of non-randomised studies was assessed using the Newcastle–Ottawa Scale, while the Cochrane Risk of Bias 2 (RoB2) tool was used for randomised studies. Standardised mean differences (SMDs) with 95% confidence intervals (CI) were calculated for continuous variables. Results Twenty-two studies (152,651 patients) were included in the systematic review and 15 studies in the meta-analysis (3 RCTs; 3 case-controlled; 9 retrospective studies). Of these, 1845 patients underwent MIS (1686 laparoscopic and 159 robotic) and 150,806 patients open surgery. The cost of surgical procedure (SMD 0.89; 95% CI 0.35 to 1.43; I 2 = 91%; P = 0.001), equipment (SMD 3.73; 95% CI 1.55 to 5.91; I 2 = 98%; P = 0.0008), and operating room occupation (SMD 1.17, 95% CI 0.11 to 2.24; I 2 = 95%; P = 0.03) was higher with MIS. However, overall index hospitalisation costs trended lower with MIS (SMD − 0.13; 95% CI − 0.35 to 0.06; I 2 = 80%; P = 0.17). There was significant heterogeneity among the studies. Conclusion Minimally invasive major pancreatic surgery entailed higher intraoperative but similar overall index hospitalisation costs.
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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 | 0.023 | 0.068 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.028 | 0.045 |
| Bibliometrics | 0.011 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| 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".