Article

Awissi DK, Lebrun G, Coursin DB, et al. Alcohol withdrawal and delirium tremens in the critically ill: A systematic review and commentary

Pharmacy Department, Hôpital Maisonneuve-Rosemont, 5415 Boulevard de l'Assomption, Montreal, PQ, H1T 2M4, Canada.
Intensive Care Medicine (Impact Factor: 7.21). 11/2012; 39(1). DOI: 10.1007/s00134-012-2758-y
Source: PubMed

ABSTRACT

Introduction:
Alcohol withdrawal is common among intensive care unit (ICU) patients, but no current practice guidelines exist. We reviewed published manuscripts for prevalence, risk factors, screening tools, prophylactic and treatment strategies, and outcomes for alcohol withdrawal syndrome (AWS) and delirium tremens (DT) in the critically ill.

Methods:
The following databases: PubMed, MEDLINE, Embase, Cochrane Database of Systematic Reviews and Central Register of Controlled Trials, CINAHL, Scopus, Web of Knowledge, pain, anxiety and delirium (PAD) Guidelines REFWORKS, International Pharmaceutical Abstracts and references for published papers were searched. Publications with high or moderate Grading of Recommendations Assessment, Development and Evaluation (GRADE) and Oxford levels of evidence were included.

Results:
Reported AWS rates range from <1 % in 'all ICU comers' to 60 % in highly selected alcohol-dependent ICU patients. Alcohol dependence and a history of withdrawal are significant risk factors for AWS occurrence. No screening tools for withdrawal have been validated in the ICU. The benefit of alcohol withdrawal prophylaxis is unproven, and proposed regimens appear equivalent. Early and aggressive titration of medication guided by symptoms is the only feature associated with improved treatment outcome.

Conclusions:
Treatment of AWS is associated with higher ICU complication rates and resource utilization. The optimal means of identification, prevention and treatment of AWS in order to establish evidence-based guidelines remain to be determined.

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    • "Approximately 15% to 20% of hospitalized patients and 50% of trauma patients suffer from alcohol use disorders[1,2]. Many of these patients manifest signs and symptoms of alcohol withdrawal syndrome (AWS) when their alcohol consumption is abruptly stopped or significantly reduced[3,4]. "
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    ABSTRACT: Purpose: To perform a systematic review of the clinical trials concerning the use of barbiturates for the treatment of acute alcohol withdrawal syndrome (AWS). Materials and methods: A literature search of MEDLINE, EMBASE, and the Cochrane Library, together with a manual citation review was conducted. We selected English-language clinical trials (controlled and observational studies) evaluating the efficacy and safety of barbiturates compared with benzodiazepine (BZD) therapy for the treatment of AWS in the acute care setting. Data extracted from the included trials were duration of delirium, number of seizures, length of intensive care unit and hospital stay, cumulated doses of barbiturates and BZDs, and respiratory or cardiac complications. Results: Seven studies consisting of 4 prospective controlled and 3 retrospective trials were identified. Results from all the included studies suggest that barbiturates alone or in combination with BZDs are at least as effective as BZDs in the treatment of AWS. Furthermore, barbiturates appear to have acceptable tolerability and safety profiles, which were similar to those of BZDs in patients with AWS. Conclusions: Although the evidence is limited, based on our findings, adding phenobarbital to a BZD-based regimen is a reasonable option, particularly in patients with BZD-refractory AWS.
    No preview · Article · Dec 2015 · Journal of critical care
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    • "Although the " AUDIT-plus " successfully identified all patients going through withdrawal, it overestimated the risk, and if used as a prediction tool it would have led to half of the patients receiving prophylaxis unnecessarily. It is important to note that to date no screening tools for AWS have been validated in the ICU (Awissi et al., 2013). Similarly, there are no validated tools for the prediction of severe AWS in the medically ill. "
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    ABSTRACT: Background To date, no screening tools for alcohol withdrawal syndromes (AWS) have been validated in the medically ill. Although several tools quantify the severity of AWS (e.g., Clinical Institute Withdrawal Assessment for Alcohol [CIWA]), none identify subjects at risk of AWS, thus missing the opportunity for timely prophylaxis. Moreover, there are no validated tools for the prediction of severe AWS in the medically ill. Objectives Our goals were (1) to conduct a systematic review of the published literature on AWS to identify clinical factors associated with the development of AWS, (2) to use the identified factors to develop a tool for the prediction of alcohol withdrawal among patients at risk, and (3) to conduct a pilot study to assess the validity of the tool. Methods For the creation of the Prediction of Alcohol Withdrawal Severity Scale (PAWSS), we conducted a systematic literature search using PRISMA (preferred reporting items for systematic reviews and meta-analyses) guidelines for clinical factors associated with the development of AWS, using PubMed, PsychInfo, MEDLINE, and Cochrane Databases. Eligibility criteria included: (i) manuscripts dealing with human subjects, age 18 years or older, (ii) manuscripts directly addressing descriptions of AWS or its predisposing factors, including case reports, naturalistic case descriptions, and all types of clinical trials (e.g., randomized, single-blind, or open label studies), (iii) manuscripts describing characteristics of alcohol use disorder (AUD), and (iv) manuscripts dealing with animal data (which were considered only if they directly dealt with variables described in humans). Obtained data were used to develop the Prediction of Alcohol Withdrawal Severity Scale, in order to assist in the identification of patients at risk for moderate to severe AWS. For the Pilot Study A pilot study was conducted to assess the new tool’s psychometric qualities on patients admitted to a general inpatient medicine unit over a 2-week period, who agreed to participate in the study. Blind to PAWSS results, a separate group of researchers retrospectively examined the medical records for evidence of AWS. Results The search produced 2802 articles describing factors potentially associated with increased risk for AWS, increased severity of withdrawal symptoms, and potential characteristics differentiating subjects with various forms of AWS. Of these, 446 articles met inclusion criteria and underwent further scrutiny, yielding a total of 233 unique articles describing factors predictive of AWS. A total of 10 items were identified as correlated with moderate to severe AWS (i.e., withdrawal hallucinosis, withdrawal-related seizures, and delirium tremens) and used to construct the PAWSS. During the pilot study, a total of 68 subjects underwent evaluation with PAWSS. In this pilot sample the sensitivity, specificity, and positive and negative predictive values of PAWSS were 100%, using the threshold score of 4. Discussion The results of the literature search identified 10 items which may be correlated with risk for moderate to severe AWS. These items were assembled into a tool to assist in the identification of patients at risk: PAWSS. The results of this pilot study suggest that PAWSS may be useful in identifying risk of moderate to severe AWS in medically ill, hospitalized individuals. PAWSS is the first validated tool for the prediction of severe AWS in the medically ill and its use may aid in the early identification of patients at risk for moderate to severe AWS, allowing for prophylaxis against AWS before severe alcohol withdrawal syndromes develop.
    Full-text · Article · Jun 2014 · Alcohol (Fayetteville, N.Y.)
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    • "Benzodiazepines and opioid withdrawal syndromes may represent an important cause of delirium after discontinuation of sedation. Alcohol withdrawal syndrome often is evoked in a patient with a history of alcohol dependence who develops encephalopathy [78]. The predominance of psychomotor agitation and autonomic signs are suggestive of the diagnosis. "
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    ABSTRACT: Sepsis often is characterized by an acute brain dysfunction, which is associated with increased morbidity and mortality. Its pathophysiology is highly complex, resulting from both inflammatory and noninflammatory processes, which may induce significant alterations in vulnerable areas of the brain. Important mechanisms include excessive microglial activation, impaired cerebral perfusion, blood--brain-barrier dysfunction, and altered neurotransmission. Systemic insults, such as prolonged inflammation, severe hypoxemia, and persistent hyperglycemia also may contribute to aggravate sepsis-induced brain dysfunction or injury. The diagnosis brain dysfunction in sepsis relies essentially on neurological examination and neurological tests, such as EEG and neuroimaging. A brain MRI should be considered in case of persistent brain dysfunction after control of sepsis and exclusion of major confounding factors. Recent MRI studies suggest that septic shock can be associated with acute cerebrovascular lesions and white matter abnormalities. Currently, the management of brain dysfunction mainly consists of control of sepsis and prevention of all aggravating factors, including metabolic disturbances, drug overdoses, anticholinergic medications, withdrawal syndromes, and Wernicke's encephalopathy. Modulation of microglial activation, prevention of blood--brain-barrier alterations, and use of antioxidants represent relevant therapeutic targets that may impact significantly on neurologic outcomes. In the future, investigations in patients with sepsis should be undertaken to reduce the duration of brain dysfunction and to study the impact of this reduction on important health outcomes, including functional and cognitive status in survivors.
    Full-text · Article · May 2013 · Annals of Intensive Care
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