Tissue stress from laparoscopic grasper use and bowel injury in humans: establishing intraoperative force boundaries
Bibliographic record
Abstract
OBJECTIVES: We aim to determine what threshold of compressive stress small bowel and colon tissues display evidence of significant tissue trauma during laparoscopic surgery. DESIGN: This study included 10 small bowel and 10 colon samples from patients undergoing routine gastrointestinal surgery. Each sample was compressed with pressures ranging from 100 kPa to 600 kPa. Two pathologists who were blinded to all study conditions, performed a histological analysis of the tissues. Experimentation: November 2018-February 2019. Analysis: March 2019-May 2020. SETTING: An inner-city trauma and ambulatory hospital with a 40-bed inpatient general surgery unit with a diverse patient population. PARTICIPANTS: Patients were eligible if their surgery procured healthy tissue margins for experimentation (a convenience sample). 26 patient samples were procured; 6 samples were unusable. 10 colon and 10 small bowel samples were tested for a total of 120 experimental cases. No patients withdrew their consent. INTERVENTIONS: A novel device was created to induce compressive "grasps" to simulate those of a laparoscopic grasper. Experimentation was performed ex-vivo, in-vitro. Grasp conditions of 0-600 kPa for a duration of 10 s were used. RESULTS: Small bowel (10), M:F was 7:3, average age was 54.3 years. Colon (10), M:F was 1:1, average age was 65.2 years. All 20 patients experienced a significant difference (p<0.05) in serosal thickness post-compression at both 500 and 600 kPa for both tissue types. A logistic regression analysis with a sensitivity of 100% and a specificity of 84.6% on a test set of data predicts a safety threshold of 329-330 kPa. CONCLUSIONS: A threshold was discovered that corresponded to both significant serosal thickness change and a positive histological trauma score rating. This "force limit" could be used in novel sensorized laparoscopic tools to avoid intraoperative tissue injury.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".