JOURNAL ARTICLE
Preoperative fasting practice: optimising surgical patients' food and fluid intake.
Published In: Nursing Standard, 2026, v. 41, n. 4. P. 61 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Jefferies, Rachel; Crossland, Leigh 3 of 3
Abstract
Why you should read this article: • To enhance your understanding of the complications associated with preoperative fasting • To update your knowledge of evidence-based changes in preoperative fasting practice • To contribute towards revalidation as part of your 35 hours of CPD (UK readers) • To contribute towards your professional development and local registration renewal requirements (non-UK readers). In healthcare, the terms 'fasting' or 'nil by mouth' usually refer to a patient who is not allowed to have any form of food, drink or medicines orally for a specific time. Fasting is a contentious issue in perioperative care, and differing guidelines in this practice can cause confusion and pose unnecessary risks to patients. Prolonged fasting may lead to discomfort and increased risk of surgical complications, while studies have shown that shorter fasting periods can enhance patient outcomes. Evidence supports allowing patients to have sips of clear fluids preoperatively, as demonstrated by the SipTilSend protocol, which may reduce fasting times without increasing the risk of complications. This article explores and promotes evidence-based fasting protocols that could improve perioperative care and enhance the patient experience. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Nursing Standard. 2026/04, Vol. 41, Issue 4, p61
- Document Type:Article
- Subject Area:Health and Medicine
- Publication Date:2026
- ISSN:0029-6570
- DOI:10.7748/ns.2026.e12643
- Accession Number:192697189
- Copyright Statement:Copyright of Nursing Standard is the property of Royal College of Nursing of the United Kingdom (The) and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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