Severe alcohol withdrawal syndrome: review of the literature

Abstract

Purpose The purpose of this paper is to identify published literature from a general hospital setting that may highlight variables implicated in the development of severe alcohol withdrawal syndrome (SAWS) in patients who have alcohol dependence syndrome (ADS). Design/methodology/approach A systematic literature review was carried out using the electronic databases: MEDLINE, Medline in Process, Cinahl, Embase and PsycINFO from 1989 to 2017. The focus of this search was on English language studies of individuals over 16 years admitted to general hospital with ADS, delirium tremens (DTs), alcohol-related seizure (ARS) or alcohol withdrawal syndrome (AWS). Findings Of the 205 studies screened, eight met the criteria for inclusion. Six studies were quantitative retrospective cohort and two were retrospective case-control. Six studies investigated risk factors associated with DTs, one examined SAWS and one alcohol kindling. Descriptive analysis was performed to summarise the empirical evidence from studies were 22 statistically significant risk factors were found; including the reason for admission to hospital, daily alcohol consumption, previous DTs and prior ARS. The last two factors mentioned appeared in two studies. Research limitations/implications Further research should consider the quality and completeness of the alcohol history data and competence of staff generating the data in retrospective studies. Originality/value The paper suggests that the factors linked to SAWS development from the literature may not fully explain why some individuals who have ADS develop SAWS, and others do not.

Risk Factors for Severe Alcohol Withdrawal Syndrome in an Acute Hospital Population

“…AWS spans a spectrum that ranges from mild and, in the most extreme circumstances, severe that includes DTs and ARS. However, the SAWS literature presents findings that are conflicting and inconclusive, prompting this study (Benson et al, 2019). Accounting for the limitations of the SAWS literature, in this analysis, we compared a group of patients who had ADS and developed SAWS or not in a randomly selected acute hospital population.…”

“…The systematic literature review carried out by the authors and published previously identified a number of flaws in the SAWS literature (Benson, Roberts, McCallum, & McPherson, 2019). The flaws included inconsistent data coding and databases that were not recognized or validated, which made it difficult to extrapolate to a wider population.…”

“…The literature presented findings based on evidence from studies that failed to include a validated screening questionnaire, treatment tool, and data generation from staff competent in alcohol assessment (Booth & Blow, 1993;Eyer et al, 2011;Ferguson et al, 1996;Lee et al, 2005;Lukan et al, 2002;Mennecier et al, 2008;Monte et al, 2010;Wright et al, 2006). Although poor alcohol assessment is a frequent criticism of general hospital clinicians, the competence levels of the staff who generated the primary alcohol data within the literature were rarely explored (Benson et al, 2019;Griffiths, Stone, Tran, Fernandez, & Ford, 2007;Schwarz & Oyserman, 2001;Stehman & Mycyk, 2013;The Royal College of Physicians, 2010;Williams & Mitchell, 2013).…”

Development of an alcohol withdrawal risk stratification tool based on patients referred to an addiction liaison nursing service in Glasgow

“…The decision to admit to hospital for alcohol detoxification is not supported by the lack of a tool to inform physicians in this decision (Benson et al, 2019;NICE, 2016;Stephens et al, 2014;Repper-DeLisi et al, 2008). Despite a number of retrospective studies investigating risk factors and SAWS, the only protocol located for the identification of low SAWS risk was developed by Stephens et al (2014).…”

“…The aim of this study and described in this paper is to investigate whether the GMAWS and the quantitative variables identified through a systematic literature review (Benson et al, 2019) can be used in the emergency department to help stratifying a person's risk of developing SAWS and support clinicians in their decision to admit or not. The variables were; previous SAWS, ARS, DT`s, hours since last drink, age, post code, gender, reason for admission, physical observations, blood results, co-morbidities, and level of ADS.…”