Minimally invasive spleen-preserving distal pancreatectomy: real-world data from the Italian National Registry of Minimally Invasive Pancreatic Surgery (IGoMIPS)
Bibliographic record
Abstract
Aim: Minimally invasive distal pancreatectomy has become the standard of care for benign and low malignant lesions. Spleen preservation in this setting has been proposed to reduce surgical trauma and long-term sequelae. The aim of the current study is to present real-world data on indications, techniques, and outcomes of spleen-preserving distal pancreatectomy (SPDP). Methods: Patients who underwent SPDP and distal pancreatectomy with splenectomy (DPWS) were extracted from the 2019-2022 Italian National Registry for Minimally Invasive Pancreatic Surgery (IGoMIPS). Perioperative and pathological data were collected. Results: One hundred and ten patients underwent SPDP and five hundred and seventy-eight underwent DPWS. Patients undergoing SPDP were significantly younger (56 vs. 63.5 years; P < 0.001). Seventy-six percent of SPDP cases were performed in six out of thirty-four IGoMIPS centers. SPDP was performed predominantly for Neuroendocrine Tumors (43.6% vs.23.5%; P < 0.001) and for smaller lesions (T1 57.6% vs. 29.8%; P < 0.001). The conversion rate was higher in the case of DPWS (7.6% vs. 0.9%; P = 0.006), even when pancreatic cancer was ruled out (5.0% vs. 0.9%; P = 0.045). The robotic approach was most commonly used for SPDP (50.9% vs. 29.7%; P < 0.001). No difference in postoperative outcomes and length of stay was observed between the two groups, as well as between robotic and laparoscopic approaches in the SPDP group. A trend toward a lower rate of postoperative sepsis was observed after SPDP (0.9% vs. 5.2%; P = 0.056). In 84.7% of SPDP, splenic vessels were preserved (Kimura procedure) without an impact on short-term postoperative outcomes. Conclusion: In this registry analysis, SPDP was feasible and safe. The Kimura procedure was prevalent over the Warshaw procedure. The typical patient undergoing SPDP was young with a neuroendocrine tumor at an early stage. Robotic assistance was used more frequently for SPDP than for DPWS.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".