Low-residue diet with oral nutritional supplements prior to colonoscopy improves the quality of bowel preparation: an endoscopist-blinded, randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Poor bowel preparation has been a great problem of endoscopists for a long time. Low-residue diet (LRD) is often recommended on the day before colonoscopy. However, the quality of bowel preparation with LRD alone is suboptimal. The aim of our study was to examine whether patients who consumed LRD with oral nutritional supplements (ONSs) had higher quality of bowel preparation than patients who consumed LRD alone before colonoscopy. METHODS: An endoscopist-blinded, randomized controlled trial was conducted in inpatients who scheduled for colonoscopy with sedation. Patients were randomized to the non-ONS group and the ONS group. The primary outcomes were the rates of adequate bowel preparation measured by the Boston Bowel Preparation Scale (BBPS), the Ottawa Bowel Preparation Scale (OBPS) and the Colon Endoscopic Bubble Scale (CEBuS). The secondary outcomes were the adenoma detection rate (ADR), polyp detection rate (PDR), intubation time, withdrawal time and rates of adverse events. RESULTS: In both groups, 100 patients were analyzed. The rates of adequate bowel preparation measured by the BBPS and OBPS and PDR were significantly higher in the ONS group than in the non-ONS group (all P < 0.05). However, no significant differences were observed in the CEBuS scores, ADR, intubation time and rates of adverse events between the two groups (all P > 0.05). The withdrawal time was longer in the non-ONS group than the in the ONS group (P < 0.05). CONCLUSIONS: LRD with ONSs helps increase the quality of bowel preparation. To help with colorectal cancer (CRC) screening, further studies are warrant. TRIAL REGISTRATION: [Chinese Clinical Trial Registry], [ChiCTR2400091660], [31/10/2024], [Retrospectively registered].
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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".