The Effectiveness of Short Message Service to Assure the Preparation-to-Colonoscopy Interval before Bowel Preparation for Colonoscopy
Bibliographic record
Abstract
Background/Aims. The preparation-to-colonoscopy (PC) interval is one of several important factors for the bowel preparation. Short message service (SMS) reminder from a cellular phone has been suggested to improve compliance in various medical situations. We evaluated the effectiveness of SMS reminders to assure the PC interval for colonoscopy. Methodology. This prospective randomized study was investigator blinded. In the No-SMS group, patients took the first 2 L polyethylene glycol (PEG) between 6 and 8 PM on the day before colonoscopy and the second 2 L PEG approximately 6 hours before the colonoscopy without SMS. In the SMS group, patients took first 2 L PEG in the same manner as the No-SMS group and the second 2 L PEG after receiving an SMS 6 hours before the colonoscopy. Results. The SMS group had a lower score than the No-SMS group, according to the Ottawa Bowel Preparation Scale (P < 0.001). Multivariate logistic regression analysis showed that compliance with diet instructions (odds ratio (OR) 2.109; 95% confidence interval (CI), 1.11-3.99, P = 0.022) and intervention using SMS ((OR) 2.329; 95% (CI), 1.34-4.02, P = 0.002) were the independent significant factors for satisfactory bowel preparation. Conclusions. An SMS reminder to assure PC interval improved the bowel preparation quality for colonoscopy with bowel preparation.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".