The Neuropsychiatric Iceberg Under Withdrawal Syndrome.

Abstract

We have read with a great interest the article “Validation of the Withdrawal Assessment Tool-1 in Adult Intensive Care Patients,”1 by Capilnean and colleagues. The study emphasizes the importance of a validated tool to detect opioid withdrawal syndrome in adult intensive care units (ICUs), and yet we wonder if one possible explanation for the low accuracy of the Withdrawal Assessment Tool (WAT-1) in their study was that they included all patients with brain injury and a score of 9 or greater on the Glasgow Coma Scale (GCS) if the patient’s intracranial pressure was not increased. Although the number of patients in the study with nervous system disorders as the cause of admission to the ICU was low, we note that such patients made up nearly 15% of the patients in the study who had iatrogenic withdrawal syndrome.Although we suspect that using such broad inclusion criteria is a logical and reasonable way to improve the generalizability of such a small prospective study, this approach may have decreased the accuracy of the WAT-1 in their cohort. For instance, consider a patient with traumatic brain injury being evaluated in the ICU who has a right-sided patchy subarachnoid hemorrhage with a GCS score of 12. Such a patient’s WAT-1 score of 3 or greater could be due to probable autonomic dysfunction,2 increased tonus,3 and acute confusional state,4,5 all of which could be attributed to the organic involvement of subarachnoid hemorrhage. In this situation, if one uses the criteria in the Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition), unlike WAT-1, such patients would not be placed in the “withdrawal-positive” group because of the presence of another medical condition that better explains the symptoms.In an ongoing cohort study being conducted in our tertiary care university hospital, we have so far found the accuracy of WAT-1 to be nearly 85% in our preliminary analysis using more rigid criteria that excluded all patients with other neurologic and/or psychiatric disorders. We think an algorithm that separates patients with organic cerebral involvement from those without will shed much more light on this ambiguous issue of “opioid withdrawal syndrome.”