Colon Bowel Preparation in the Era of Artificial Intelligence: Is There Potential for Enhancing Colon Bowel Cleansing?
Boston bowel preparation scale
artificial intelligence
bowel preparation
colonoscopy
predictive scores
Journal
Medicina (Kaunas, Lithuania)
ISSN: 1648-9144
Titre abrégé: Medicina (Kaunas)
Pays: Switzerland
ID NLM: 9425208
Informations de publication
Date de publication:
15 Oct 2023
15 Oct 2023
Historique:
received:
18
09
2023
revised:
10
10
2023
accepted:
13
10
2023
medline:
30
10
2023
pubmed:
28
10
2023
entrez:
28
10
2023
Statut:
epublish
Résumé
Proper bowel preparation is of paramount importance for enhancing adenoma detection rates and reducing postcolonoscopic colorectal cancer risk. Despite recommendations from gastroenterology societies regarding the optimal rates of successful bowel preparation, these guidelines are frequently unmet. Various approaches have been employed to enhance the rates of successful bowel preparation, yet the quality of cleansing remains suboptimal. Intensive bowel preparation techniques, supplementary administration of bowel solutions, and educational interventions aimed at improving patient adherence to instructions have been commonly utilized, particularly among patients at a high risk of inadequate bowel preparation. Expedited strategies conducted on the same day as the procedure have also been endorsed by scientific organizations. More recently, the utilization of artificial intelligence (AI) has emerged for the preprocedural detection of inadequate bowel preparation, holding the potential to guide the preparation process immediately preceding colonoscopy. This manuscript comprehensively reviews the current strategies employed to optimize bowel cleansing, with a specific focus on patients with elevated risks for inadequate bowel preparation. Additionally, the prospective role of AI in this context is thoroughly examined. While a majority of outpatients may achieve cleanliness with standard cleansing protocols, dealing with hard-to-prepare patients remains a challenge. Rescue strategies based on AI are promising, but such evidence remains limited. To ensure proper bowel cleansing, a combination of strategies should be performed.
Sections du résumé
BACKGROUND AND OBJECTIVES
OBJECTIVE
Proper bowel preparation is of paramount importance for enhancing adenoma detection rates and reducing postcolonoscopic colorectal cancer risk. Despite recommendations from gastroenterology societies regarding the optimal rates of successful bowel preparation, these guidelines are frequently unmet. Various approaches have been employed to enhance the rates of successful bowel preparation, yet the quality of cleansing remains suboptimal. Intensive bowel preparation techniques, supplementary administration of bowel solutions, and educational interventions aimed at improving patient adherence to instructions have been commonly utilized, particularly among patients at a high risk of inadequate bowel preparation. Expedited strategies conducted on the same day as the procedure have also been endorsed by scientific organizations. More recently, the utilization of artificial intelligence (AI) has emerged for the preprocedural detection of inadequate bowel preparation, holding the potential to guide the preparation process immediately preceding colonoscopy. This manuscript comprehensively reviews the current strategies employed to optimize bowel cleansing, with a specific focus on patients with elevated risks for inadequate bowel preparation. Additionally, the prospective role of AI in this context is thoroughly examined.
CONCLUSIONS
CONCLUSIONS
While a majority of outpatients may achieve cleanliness with standard cleansing protocols, dealing with hard-to-prepare patients remains a challenge. Rescue strategies based on AI are promising, but such evidence remains limited. To ensure proper bowel cleansing, a combination of strategies should be performed.
Identifiants
pubmed: 37893552
pii: medicina59101834
doi: 10.3390/medicina59101834
pmc: PMC10608636
pii:
doi:
Substances chimiques
Cathartics
0
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : Spanish Society of Gastrointestinal Endoscopy
ID : FSEED grupo de trabajo 2022
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