The "Prediction of Alcohol Withdrawal Severity Scale" (PAWSS)

Phase

N/A

Condition

Alcohol Use Disorder

Alcohol Dependence

Treatment

N/A

Clinical Study ID

NCT01637415

22731

Ages > 18
All Genders
Accepts Healthy Volunteers

Study Summary

Although there are several tools that can be used to evaluate the severity of ongoing alcohol withdrawal syndrome (AWS), there is no available tool that can predict which patients are at risk for developing AWS at the time admission, before the patient has developed AWS. Unfortunately, there are severe symptoms of alcohol withdrawal (e.g., seizures) which may develop early in the hospitalization, and before the development of other systemic symptoms which may warn medical personnel of the possibility of impeding alcohol withdrawal (e.g., autonomic instability, delirium). The goal of this study is to evaluate the psychometric properties (e.g., predictive validity) of a new tool, the Prediction of Alcohol Withdrawal Severity Scale (PAWSS), on identifying which patients are at risk for developing complicated AWS (i.e., seizures, hallucinosis, delirium tremens) among hospitalized, medically ill patients.

Eligibility Criteria

Inclusion

Inclusion Criteria:

Adult patients - defined as 18+ years of age
Able to understand and communicate in English.
Admission to the hospital within the last 24 hours to selected Stanford Hospital andClinics inpatient units from the ED, outpatient clinics/community, or other SHCmedical units.
Without an imminent discharge plan, (within 48 hours of study screening).
Willing and able to freely consent and participate.

Exclusion

Exclusion Criteria:

Unable or unwilling to consent and participate.
Unable to understand and communicate in English.
Patients transferred from outside medical facilities.
Patients with imminent discharge plan (i.e., not expected to remain in the hospitalfor at least 48 hours after enrollment into the study)
Uncontrolled active seizure disorder.
Active severe AWS (as defined by CIWA = or > 20) on initial assessment.
Identified by the primary team as too sick to participate.

Study Design

May 01, 2012

June 30, 2014

Study Description

The investigators plan to study the psychometric properties of a new tool, the "Prediction of Alcohol Withdrawal Severity Scale" (PAWSS) on predicting the risk for the development of complicated AWS (i.e., seizures, delirium tremens) in hospitalized medically ill patients. This tool was developed through an extensive literature review which identified evidence-based predictors for AWS.

The scale consists of three portions relating to 1) an initial screening (threshold items), 2) patient's history of alcohol use and its consequences, and 3) measures of BAL and autonomic function. The investigators predict that a scale score 4 or greater will be associated with a high risk for the development of complicated AWS.

Patients will undergo examination with the PAWSS within 24 hours of hospital admission. Thereafter, all patients will undergo daily examinations with the Clinical Institute Withdrawal Assessment for Alcohol, revised (CIWA) and the Alcohol Withdrawal Severity scale (AWS scale) in order to measure the primary outcomes of the study, that is, the development and severity (i.e., moderate to severe) of AWS during the first 72-hours after admission. The study is designed to study the tool's psychometric properties including its validity and inter-rater reliability.

By providing clinicians with a tool (i.e., PAWSS) that allows them to correctly predict who will develop complicated AWS it will enable them to prophylax (i.e., preventively treat) patients at risk and thus decrease patients' morbidity and mortality, shorten length of hospital stay, minimize the significant burden on the nursing and medical staff, and improve overall patient care.

Connect with a study center

Stanford Hospitals and Clinics
Stanford, California 94305
United States
Site Not Available

Not the study for you?

Let us help you find the best match. Sign up as a volunteer and receive email notifications when clinical trials are posted in the medical category of interest to you.