JOURNAL ARTICLE
Recognising and managing hypoglycaemia in adults with diabetes in the emergency department.
Published In: Emergency Nurse, 2025, v. 33, n. 2. P. 35 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Stewart, Martha 3 of 3
Abstract
Why you should read this article: • To enhance your understanding of the aetiology and signs and symptoms of hypoglycaemia • To read about the recommended management of hypoglycaemia in adults with diabetes in hospital • 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). Hypoglycaemia is a common cause of presentation to the emergency department (ED) for people with diabetes mellitus. Patients experiencing a hypoglycaemic episode require prompt treatment with fast-acting glucose to prevent brain fuel deprivation and functional brain failure, therefore it is vital that ED nurses can recognise the signs and symptoms of hypoglycaemia and are aware of the factors that can compound or mask it. This article discusses the aetiology and signs and symptoms of hypoglycaemia in adults with type 1 and type 2 diabetes and describes the use of an algorithm for the management of hypoglycaemia in this patient population in hospital. The author also discusses how ED nurses can try to identify the cause of the hypoglycaemic episode and work with patients, their relatives or carers and the wider multidisciplinary team to prevent reoccurrence. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Emergency Nurse. 2025/03, Vol. 33, Issue 2, p35
- Document Type:Article
- Subject Area:Consumer Health
- Publication Date:2025
- ISSN:1354-5752
- DOI:10.7748/en.2025.e2223
- Accession Number:186486024
- Copyright Statement:Copyright of Emergency Nurse 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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