Mechanical Analysis of Insertion Problems and Pain During Colonoscopy: Why Highly Skill-Dependent Colonoscopy Routines are Necessary in the First Place... and How They May be Avoided
Bibliographic record
Abstract
BACKGROUND: Colonoscopy requires highly skill-dependent manoeuvres that demand a significant amount of training, and can cause considerable discomfort to patients, which increases the use of sedatives. Understanding the underlying fundamental mechanics behind insertion difficulties and pain during colonoscopy may help to simplify colonoscopy and reduce the required extent of training and reliance on sedatives. METHODS: A literature search, anatomical studies, models of the colon and colonoscope, and bench tests were used to qualitatively analyze the fundamental mechanical causes of insertion difficulties and pain. A categorized review resulted in an overview of potential alternatives to current colonoscopes. RESULTS: To advance a colonoscope through the colon, the colon wall, ligaments and peritoneum must be stretched, thus creating tension in the colon wall, which resists further wall deformation. This resistance forces the colonoscope to bend and follow the curves of the colon. The deformations that cause insertion difficulties and pain (necessitating the use of complex conventional manoeuvres) are the stretching of ligaments, and stretching of colon wall in the transverse and longitudinal directions, and the peritoneum. CONCLUSIONS: Four fundamental mechanical solutions to prevent these deformations were extracted from the analysis. The current results may help in the development of new colonoscopy devices that reduce - or eliminate - the necessity of using highly skill-dependent manoeuvres, facilitate training and reduce the use of sedatives.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 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".