**4. Diagnostics**

AUD is a medical condition where one experiences difficulty in stopping or controlling the use of alcohol, despite experiencing adverse social, occupational, or health consequences [8].

AUD is a significant patient safety issue in the hospitalized patient, associated with morbidity and mortality, especially when it goes undiagnosed or undertreated. Although many patients present self-reporting alcohol use disorder or withdrawal while requesting treatment, many present for new or related illnesses and complications without proper disclosure, risk stratification, assessment, or treatment and either progress to alcohol withdrawal or have other conditions that mask it due to overlapping symptomatology. For example, a patient may present with pancreatitis and not fully inform of recent or regular alcohol use. Others may present later in the disease course with symptoms or complications that may cause the clinician to overlook AUD as an etiology. Another example would be a new onset seizure in an encephalopathic patient, prompting a neurological evaluation and empiric treatment with ineffective antiepileptic agents, leaving the alcohol withdrawal untreated. A patient who fell and suffered a subdural hematoma may not be suspected of recent intoxication or alcohol related neuropathy as the cause of the fall and can then be at risk for experiencing alcohol withdrawal. These patients will be at risk of developing severe alcohol withdrawal that can result in severe complications, including permanent disability and death.

Clinicians should inquire about a patient's drinking habits, including quantity and duration of alcohol consumption, and any history of AWS to identify patients with AUD and to gauge the likelihood of AWS. Several questionnaires are useful in aiding this history taking [9]. Once screening has been performed, clinicians can then utilize additional scoring tools for risk stratification and therapy. The various screening tools that can be used for identifying alcohol use disorder in the hospital include AUDIT (Alcohol Use Disorders Identification Test), AUDIT-C (the Shortened Alcohol Use Disorders Identification Test), the CAGE questionnaire (Cut down Annoyed, Guilty, Eye-opener), the TACE (Tolerance, Annoyed Cut down, Eye-opener; mainly for pregnant patients) and SBIRT (Screening and Brief Intervention Tool). Although the in-depth description of these screening tools is beyond the focus of this chapter, it is important that hospital systems utilize a screening tool to assist in identifying and diagnosing patients with alcohol use disorder, so that they can then risk stratify who may be at risk for withdrawal and implement a treatment plan, all while evaluating and treating for common comorbidities. Risk stratification can also be performed utilizing the PAWSS score (The Prediction of Alcohol Withdrawal Severity Scale) while the most common treatment assessment tool is Clinical Institute Withdrawal Assessment (CIWA). These tools are further described in subsequent sections.

Comorbidities and other clinical clues useful for identifying alcohol use disorder may include common diagnostic findings, such as transaminitis (AST > ALT in 2–3:1 ratio, generally <500 U/L), macrocytic anemia, thrombocytopenia, and electrolyte derangements – most commonly hyponatremia, hypokalemia, and hypocalcemia; and therefore, QT prolongation and risk of dysrhythmia. Commonly associated conditions include traumatic injuries, pancreatitis, gastritis, gastrointestinal bleeding, alcoholic ketoacidosis, malnutrition, dehydration, acute kidney injury, hypertension. All of these findings should be reason to consider a patient for potentially having alcohol use disorder and being at risk for withdrawal.

Evaluation of the patient identified with alcohol use disorder or withdrawal syndrome should include electrocardiogram, complete blood count, complete metabolic panel, magnesium (especially if hypokalemic), INR, lipase if any gastrointestinal symptoms, serum ethanol concentration, and if any alteration of mental status, computed tomography of brain. CT imaging of brain should be considered particularly if any concern for traumatic injury. Further evaluation for cardiac ischemia or cardiomyopathy should also be considered. Obtaining a serum ethanol concentration is important as is it not possible for clinicians to commonly predict degree of intoxication based on assessment of clinical sobriety. An elevated serum ethanol concentration in a presenting patient should be reason to evaluate for alcohol use disorder, and should prompt concern for possible withdrawal. Although patients may begin to withdraw at elevated serum ethanol concentrations, many may not start to withdraw for easily six hours after they metabolize all their ethanol. In this case, a predictive timeline can be generated, utilizing the average ethanol metabolism of 15 mg/kg/hr., to determine how long to observe for symptomatology.

The PAWSS score is a clinical scoring tool that can be utilized to assess patients identified with AUD to risk stratify the likelihood of developing AWS (**Table 1**). Severity can then be monitored with CIWA or SEWS [10, 11]. A PAWSS score < 4 portends a low risk of moderate to severe AWS, whereas a score > 4 places a patient at high risk of experiencing severe AWS [10]. The prospective validation study of PAWSS resulted in a sensitivity of 93% and specificity of 99.5% in predicting severe withdrawal for hospitalized patients, making it a highly useful tool for the modernday practitioner in treating AWS [12].


#### **Table 1.**

*Prediction of Alcohol Withdrawal severity scale (PAWSS).*


#### **Table 2.**

*Clinical Institute of Alcohol Withdrawal Score – Revised (CIWA-R).*

Once a patient is identified as potentially having AUD and is then risk stratified for possibly developing AWS, several scoring systems are available for further monitoring and treatment. The revised Clinical Institute Withdrawal Assessment for Alcohol Scale (CIWA) was among the first scores designed to appropriately guide treatment for AWS [13]. The CIWA score has been adopted across numerous health systems worldwide and is the most common clinical tool utilized for AWS. The score takes several minutes to calculate and ranges from 0 to 67 with severity of withdrawal being associated with higher scores (scores >20 indicates severe AWS). The questionnaire assesses for nausea, diaphoresis, tremor, hallucinations, among other symptoms indicative of AWS (**Table 2**). The score can then be tied to escalating doses of medications, such as benzodiazepines, for symptom triggered treatment. CIWA has been shown to result in more reliable benzodiazepine (BZD) dosing, decreased length of hospital stay, and decreased rate of severe complications when compared to unscored symptom-based dosing [14]. However, there are limitations to CIWA as several components of the questionnaire are subjective in nature and may result in variability between clinicians.

The Severity of Ethanol Withdrawal Scale (SEWS) is another clinical scoring tool that can be used to guide treatment for AWS [15]. Similar to CIWA, SEWS generates a calculated score ranging from 0 to 24 with higher scores (scores >13) indicating severe AWS (**Table 3**). SEWS is not as often utilized as CIWA currently, however in a 2019 quality assurance study, it was shown to decrease hospital length of stay by one day by allowing for more aggressive BZD treatment without over sedation risk when compared to CIWA [15]. SEWS also showed to be more objective, utilizing vital signs, and more easily performed by provider, likely since it has less questions. Further prospective studies are needed for external validation, however in the meantime, initial results appear promising in using SEWS to guide treatment for AWS.

To summarize, the three clinical scoring tools presented (CIWA, SEWS, PAWSS) are crucial when it comes to risk stratifying and treating AWS. In addition, clinicians must be mindful of the many co-morbidities that patient's suffering from AWS frequently present with and obtain appropriate diagnostic testing for these as well. Appropriately recognizing AUD, AWS and related co-morbidities is paramount for patient safety.


#### **Table 3.**

*Severity of ethanol Withdrawal scale (SEWS).*

*Improving the Safety of Admitted Patients with Alcohol Use Disorder and Withdrawal DOI: http://dx.doi.org/10.5772/intechopen.110030*
