Factors Affecting the Quality of Bowel Preparation Before Colonoscopy in Outpatient: A Prospective Observational Study
Bibliographic record
Abstract
Colonoscopy is an effective method for screening colorectal cancer and adenoma, but the adenoma detection rate depends on the quality of bowel preparation. Our study investigates the influencing factors of the quality of bowel preparation before colonoscopy in outpatients and the influence of the number of walking steps on the quality of bowel preparation. We prospectively collected the clinical data of 150 outpatients undergoing colonoscopy in our department in 2019. Ordinal logistic regression shows that the overweight, not drinking, the number of walking steps before colonoscopy, and the time interval between start PEG and colonoscopy (4–6 hours) were independent factors affecting bowel preparation quality. There was a curving relationship between the reciprocal of Ottawa score and the number of walking steps before colonoscopy, and the regression equation is 1/ Ottawa score = −0.198 + 0.062 × ln steps ( p = .035), a minimum of 5,270 walking steps before a colonoscopy is required for a high quality of bowel preparation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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".