Minimally invasive Distal Pancreatectomy eRgonOMic analysis – the DP-ROM trial: An explorative, prospective, observational, cohort study trial
Bibliographic record
Abstract
BACKGROUND: Minimally invasive distal pancreatectomy (DP) improves patient outcomes but also introduces significant ergonomic challenges for surgeons. This study quantitatively compares the ergonomic stress and mental workload associated with laparoscopic versus robot-assisted DP. METHODS: An exploratory, prospective, observational cohort trial was conducted with two experienced pancreatic surgeons performing 20 DPs (10 laparoscopic using IMAGE1 S Rubina and 10 robot-assisted using da Vinci® Si platform). Ergonomic stress was assessed using stabilometric analysis, kinematic pelvic movement analysis, ocular examinations, cortisol level monitoring, and the NASA Task Load Index (NASA-TLX). RESULTS: Robot-assisted DP demonstrated superior ergonomic performance, with reduced physical and mental demands compared to laparoscopic DP. Stabilometric tests indicated significantly greater postural stability during robot-assisted surgery, characterized by lower variance in body oscillations. Kinematic analyses confirmed smoother pelvic movements in robot-assisted procedures, suggesting reduced physical fatigue. Visual strain was markedly higher during laparoscopic surgery, likely due to prolonged screen exposure. The NASA-TLX indicated significantly lower overall workload scores for robot-assisted DP (35.3 ± 19.5) compared to laparoscopic DP (50.7 ± 21.7, p = 0.04). Cortisol analyses consistently showed elevated stress levels in the laparoscopic group compared to the robotic group, reinforcing the finding of greater physiological stress in the laparoscopic setting. CONCLUSION: Robot-assisted DP significantly reduces ergonomic stress, visual strain, and cognitive workload compared to laparoscopic DP. However, it also introduces specific ergonomic challenges, particularly involving neck and trapezius muscle strain. Future studies should investigate ergonomic modifications to further optimize surgeon well-being and performance during robot-assisted pancreatic procedures.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".