ATLANTA (FRONTLINE MEDICAL NEWS) A new scale for predicting complicated alcohol withdrawal syndrome in hospitalized medically ill patients had high sensitivity and specificity in a prospective validation study.

The Prediction of Alcohol Withdrawal Severity Scale (PAWSS) can help clinicians identify those at risk for complicated alcohol withdrawal syndrome (AWS), and either prevent or treat complicated AWS in a timely manner, Dr. José R. Maldonado of Stanford (Calif.) University said at the annual meeting of the American Psychiatric Association.

In 403 subjects hospitalized to general medicine and surgery units over a 12-month period, the PAWSS – along with the Clinical Institute Withdrawal Assessment–alcohol revised (CIWA-Ar) and clinical monitoring – was administered daily. Using a cutoff score of 4 on the 0-10 point PAWSS, the tool had sensitivity and positive predictive value of 93.1%, and specificity and negative predictive value of 99.5% for identifying complicated AWS, Dr. Maldonado said, noting that the tool also had excellent inter-rater reliability.

The findings are important because the prevalence of alcohol use disorders among hospitalized medically ill patients exceeds 40%, he said, noting that medically ill patients with AWS tend to have a significant number of complications, which makes them “not only very difficult to treat but also very high risk.”

Importantly, seizures – commonly known as “rum fits,” which occur in 5%-15% of cases – happen very early on in the course of AWS. This is a concern, because it has implications for prescribing, Dr. Maldonado said.

Another concern, and “probably the most dreadful of them all,” is delirium tremens (DTs), a severe symptom of alcohol withdrawal that occurs in about 10% of patients with AWS.

The overall mortality associated with DTs is 1% in non–medically ill patients, but in the medically ill, this figure increases to 20% because of the frequency of comorbidities, such as heart disease and diabetes in this population. Also, DTs tend to occur a few days into withdrawal, peaking on day 5, which could be problematic; a trauma patient who is intubated in the operating room, for example, still could go through withdrawal a few days later, as most medications being used in that patient are not going to prevent it, he explained.

Previously, no tool was available to predict complicated AWS to prevent seizures and DTs. Existing tools such as the CIWA and AWS scale assess AWS severity but do not predict who will withdraw, he noted, explaining that by the time the CIWA scale is positive, the patient already is in withdrawal.

One option is to treat everyone with benzodiazepines or other drugs that facilitate GABA (gamma-aminobutyric acid) transmission in patients at risk of AWS, but this unnecessarily puts 80% of patients at risk of numerous side effects, including excessive sedation, falls, respiratory depression, and medication-induced delirium.

A benzodiazepine-sparing protocol, which involved the use of alpha-2 agonists and anticonvulsants instead of benzodiazepines, was being studied at Stanford, comparing outcomes in patients treated with and without benzodiazepines.

“But before we started to use alpha-2 agonists and anticonvulsants … we wanted to make sure that we were actually treating the population that really needs it. That was the main motivation for creating this tool,” he said. “The other thing is we wanted to make sure that we don’t scare people away from treating patients with potential alcohol withdrawal, because the consequences of withdrawal are dreadful, not only immediately but also into the future.”

Every time someone goes through withdrawal, it is more severe than before, and it lowers the threshold for DTs, he added.

An extensive literature review for anything associated with the various phases of alcohol withdrawal was performed to help develop the PAWSS, which includes 10 highly predictive questions for any patients who first indicate that they have had alcohol in the prior 30 days, or who is admitted with a positive blood alcohol level test.

A pilot study involving 70 patients yielded a sensitivity and specificity of 100% each, leading to the larger study of hospitalized patients, which was published last year in Alcohol and Alcoholism (2015 May 21. doi: 10.1093/alcalc/agv043 ).

A check of admission notes would have increased the ultimate sensitivity of the scale to 100%, as false answers provided on the scale were easily identified. Blood alcohol level testing also would help.

But PAWSS is meant to provide timely information, which is important in patients at risk, and another purpose for developing PAWSS was to provide an affordable tool that can be used anywhere, including rural community hospitals or clinics where other tests might not be available, Dr. Maldonado said.

Currently, he and his colleagues are evaluating whether all 10 items on the scale are needed to make a diagnosis, or whether a shorter version would be equally useful.

“The incidence of alcoholism is extremely high. It is the most common drug problem in the United States, and we know that many physicians do not feel comfortable dealing with patients who have alcohol withdrawal,” Dr. Maldonado said, adding that this tool will simplify management.

For the Stanford study, patients with a negative PAWSS (score below 4) receive no treatment specifically for AWS. If they test positive (score of 4 or more), it is assumed that they will withdraw, and the AWS scale is administered to discriminate patients who are withdrawing from those at high risk of withdrawal. Patients with a positive PAWSS and a negative AWS scale or CIWA are directed to a prophylactic treatment arm. Those with a positive PAWSS and a positive AWS scale or CIWA are directed into a treatment arm, which involves more aggressive management.

The validation study was supported by the Chase Research Fund. Dr. Maldonado reported having no disclosures.


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