Date of Award

2016

Document Type

Thesis

Degree Name

Master of Science in Nursing (MSN)

Committee Chair

Gayle Casterline

Abstract

Alcohol withdrawal syndrome (AWS) is a very serious problem that may affect the patient when admitted inpatient for a traumatic or non-traumatic diagnosis. Chronic Alcohol consumption in moderation may put the patient at risk for delirium tremens which is the most severe form of alcohol withdrawal. Management of alcohol withdrawal in acutely ill hospitalized patients is challenging for healthcare providers (Riddle, Bush, Tittle, & Dilkhush, 2010). Signs and symptoms of AWS are caused primarily by neurophysiologic changes in the brain, which may be mild to severe, and may develop within 6-72 hours after abstaining from alcohol. Mild symptoms of withdrawal may include anxiety, nausea, and diaphoresis, while severe symptoms of hyperthermia, severe tremors, and disorientation are possible (Skinner, 2014). An accurate nursing assessment on admission is essential for the identification and treatment of alcohol related health risks. The challenges involved in early detection of alcohol related health risks, such as AWS, support the need for improved assessment skills and tools for healthcare providers in acute care settings. Nurses need to be able to assess patients at risk for AWS as early as possible, and implement treatment for symptoms as they manifest in the patient.

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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