Meta-analysis of pancreaticojejunostomy <i>versus</i> pancreaticogastrostomy reconstruction after pancreaticoduodenectomy: Authors' comment (<i>Br J Surg</i> 2006; 93: 929–936)
Bibliographic record
Abstract
Sir Our recent article collated the cumulative experience of comparative studies examining outcomes following pancreaticoduodenectomy with reconstruction using either pancreaticojejunostomy (PJ) or pancreaticogastrostomy (PG). Recognizing that meta-analyses are limited by the quality of the primary studies included, we combined the results of eleven studies that were heterogeneous in quality. Of these, eight were observational cohort studies, two were non-randomized prospective studies, and one was a randomized clinical trial (RCT). These studies, when combined, appeared to show a lower rate of pancreatic leak/fistula, overall morbidity, and mortality in the group reconstructed using the PG technique. However, within the last year, two very high quality RCTs have been published that studied this topic1,2. Given the methodological limitations of the non-randomized trials, we have performed a meta-analysis of the three published RCTs1–3. This shows that the risk of pancreatic fistula following pancreaticoduodenectomy has a relative risk that approximates one (Fig 1). While observational cohort study data suggest that the safer means of pancreatic reconstruction after pancreaticoduodenectomy is PG, the current randomized trial data show no advantage over PJ. Presently there is equipoise, and both methods of reconstruction are effective. Pancreatic surgeons should continue to use the technique with which they are most familiar. Meta—analysis of the three RCTs
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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 | 0.065 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".