Predictors for Severe Alcohol Withdrawal Syndrome in Clinical Practice

Authors and affiliation (s):

Julliyan Dilleban Arokiadoss^1,*, Narayanan Venkateshan², Denilah Pauline³, Karthika³, Bhavani Suba Niranjana³

¹Department of Pharmacy Practice, Arulmigu Kalasalingam College of Pharmacy, Krishnankoil, Tamil Nadu, INDIA.
²Department of Pharmaceutical Chemistry, Arulmigu Kalasalingam College of Pharmacy, Krishnankoil, Tamil Nadu, INDIA.
³Department of Pharmacy Practice, Arulmigu Kalasalingam College of Pharmacy, Krishnankoil, Tamil Nadu, INDIA

ABSTRACT

Alcohol Withdrawal Syndrome (AWS) presents a significant clinical challenge due to its complex neurochemical underpinnings and varied symptom severity. This review explores the predictors of severe AWS, focusing on the pathophysiology driven by neuroadaptive changes in GABAergic and glutamatergic systems. Key findings indicate that early identification and accurate assessment are critical for managing AWS effectively and preventing severe complications such as delirium tremens and seizures. Tools like the Clinical Institute Withdrawal Assessment for Alcohol (CIWA-Ar) and the Total Severity Assessment Scale (TSA) are essential for evaluating withdrawal severity and guiding treatment. Predictive factors, including the history of alcohol use, presence of comorbid conditions and individual patient characteristics, significantly influence treatment outcomes. This article highlights the critical importance of understanding and managing Alcohol Withdrawal Syndrome (AWS) through early identification and intervention to improve patient outcomes.

Keywords: Alcohol Withdrawal Syndrome, Glutamate, Tremors, Seizures, Neurochemical Imbalances.