The "Prediction of Alcohol Withdrawal Severity Scale" (PAWSS)
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 (i.e., 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 (i.e., autonomic instability). The goal of this study is to evaluate the psychometric properties (e.g., predictive validity) of the new tool, the Prediction of Alcohol Withdrawal Severity Scale (PAWSS), on identifying which patients are at risk for developing moderate to severe AWS (i.e., seizures, hallucinosis, delitium tremens) during admission to a medical unit.
Alcohol Withdrawal Syndrome
|Study Design:||Observational Model: Cohort
Time Perspective: Prospective
|Official Title:||The "Prediction of Alcohol Withdrawal Severity Scale" (PAWSS): Development and Psychometric Characteristics of a New Scale for the Prediction of Moderate to Severe Alcohol Withdrawal Syndrome.|
- Moderate to severe alcohol withdrawal [ Time Frame: During the first 72 hours after admission. ] [ Designated as safety issue: Yes ]
- Amount of benzodiazepines administered [ Time Frame: During the first 72 hours after admission. ] [ Designated as safety issue: No ]
- Development of delirium tremens (DT's) [ Time Frame: During the first 72 hours after admission. ] [ Designated as safety issue: Yes ]
- Development of seizures (in absence of underlying seizure disorder) [ Time Frame: During the first 72 hours after admission. ] [ Designated as safety issue: Yes ]
- Transfer to ICU due to severe AWS [ Time Frame: During the first 5 days after admission. ] [ Designated as safety issue: No ]
- Development of delirium [ Time Frame: During the first 72 hours after admission. ] [ Designated as safety issue: Yes ]
- Length of hospital stay [ Time Frame: Participants will be followed for the duration of hospital stay, an expected average of 7 days. ] [ Designated as safety issue: Yes ]
|Study Start Date:||May 2012|
|Estimated Study Completion Date:||March 2013|
|Estimated Primary Completion Date:||December 2012 (Final data collection date for primary outcome measure)|
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 moderate to severe AWS in hospitalized medical 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 3 or greater will be associated with a high risk for the development of moderate to severe AWS.
Patients will be undergo examination with the PAWSS within 24 hours of admission. Thereafter, all patients will undergo daily examinations with the Clinical Institute Withdrawal Assessment (CIWA) and Alcohol Withdrawal Severity scale (AWSS) 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 SIPAT-tool's psychometirc 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 moderate-severe AWS it will enable them to prophylax (i.e., preventively treat) patients at risk and thus decrease patients' morbidity and mortality, length of hospital stay, and minimize the significant burden on the nursing and medical staff.
|Contact: Yelizaveta Sher, M.D.||(650) email@example.com|
|Contact: Heavenly Swendsen, M.S.||(650) firstname.lastname@example.org|
|United States, California|
|Stanford Hospitals and Clinics||Recruiting|
|Stanford, California, United States, 94305|
|Contact: Heavenly Swendsen email@example.com|
|Principal Investigator: José R. Maldonado, M.D.|
|Principal Investigator:||Jose R Maldonado, MD||Stanford University|