EFFECT OF BUSCOPAN COMPARED WITH GLUCAGON DURING GASTROSCOPY, COLONOSCOPY, AND ERCP- A NARRATIVE REVIEW
Bibliographic record
Abstract
Objective: To provide a comprehensive overview of Buscopan and glucagon, comparing their mechanisms, efficacy, safety profiles, and guidelines for use in gastrointestinal endoscopy and ERCP. This review aims to offer insights into the optimal use of these agents, emphasizing the importance of personalized medicine in endoscopic practice. A narrative review was conducted, analyzing studies, clinical trials, and guidelines from prominent gastroenterological associations, including the Canadian Association of Gastroenterology (CAG) and the British Society of Gastroenterology (BSG) to compare the effects and efficacy of Buscopan and Glucagon. Buscopan is effective in enhancing visualization and reducing patient discomfort during endoscopic procedures. However, its use is contraindicated in certain conditions such as angle-closure glaucoma and with specific drug interactions. The CAG recommends against its routine use in gastroscopy and colonoscopy but acknowledges its benefits in ERCP (Endoscopic Retrograde Cholangiopancreatography). Glucagon, with a rapid onset and short half-life, is a viable alternative, particularly for patients who cannot use Buscopan. It has minimal side effects but requires careful management of potential hyperglycemia. Buscopan remains the preferred choice for spasmolysis in endoscopic procedures due to its efficacy and cost-effectiveness. Glucagon serves as an important alternative in cases where Buscopan is contraindicated. Personalized medicine, considering individual patient needs and potential risks, is essential in optimizing the use of these agents in gastrointestinal endoscopy. This review highlights the need for clinicians to carefully select and dose these spasmolytic agents to enhance patient safety, comfort, and procedural outcomes.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".