Neostigmine Administered With MoviPrep Improves Bowel Preparation for Elective Colonoscopy in Patients With Spinal Cord Injury
Bibliographic record
Abstract
BACKGROUND: Poor preparation for elective colonoscopy is exceedingly common in persons with spinal cord injury (SCI). This unsatisfactory outcome is likely due to long-standing difficulty with evacuation and decreased colonic motility, which may result in inadequate responses to conventional bowel preparation regimens. We determined whether the addition of neostigmine to MoviPrep before elective colonoscopy produced a higher percentage of acceptable bowel preparations in patients with SCI. METHODS: Twenty-seven SCI subjects were prospectively randomized to 1 of 2 arms: low-volume polyethylene glycol-electrolyte lavage with ascorbic acid (MoviPrep) or MoviPrep plus neostigmine methylsulfate and glycopyrrolate (MoviPrep+NG); 28 able-bodied subjects received MoviPrep alone. The quality of the cleansing preparation for colonoscopy was determined by gastroenterologists "calibrated" to use the Ottawa Scoring System, with an acceptable Ottawa Score (OS) considered to be ≤3. RESULTS: The administration of MoviPrep alone resulted in suboptimal bowel cleansing in the SCI group compared with the able-bodied group (50% vs. 89% of subjects had an acceptable OS; χ=7.94, P=0.05). However, when NG was added to MoviPrep in the SCI group, it markedly improved the quality of the bowel preparation, with 85% of patients then having an acceptable OS. The use of NG resulted in minimal bloating and distention before bowel evacuation (P=0.0005), and eye and muscle twitching; these were resolved within 1 hour after NG administration. No significant differences were noted among the preparation groups for adenoma detection rate (P=0.41). CONCLUSIONS: The combination of MoviPrep+NG was safe, well tolerated, and an effective approach to prepare the bowel for elective colonoscopy in patients with SCI. The side effects of this preparation were significant compared with the other treatment groups but were considered mild and anticipated.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".