Phenobarbital to manage severe gamma-hydroxybutyrate withdrawal: A case series.

INTRODUCTION: Management of a withdrawal syndrome following cessation of regular gamma-hydroxybutyrate (GHB) use, and its precursors, can represent a clinical challenge due to rapid onset delirium and/or seizures. Severe GHB withdrawal can be characterised by persistent or worsening features despite increasing benzodiazepine doses and regular baclofen. Barbiturates, such as phenobarbital, are an appealing option in this context due to their unique GABA-A receptor action. CASE SERIES: This series describes the use of phenobarbital in 13 cases, 12 patients, across two hospitals in Sydney, Australia, with persistent or progressive GHB withdrawal despite benzodiazepine-based management. A median cumulative dose of oral diazepam prior to commencing phenobarbital was 120 mg (range 80-255 mg). The median time from the last GHB use to the first dose of phenobarbital was 24 h (range 7-57 h). Eight cases received phenobarbital orally on a general ward and 5 intravenously in intensive care units. An improvement in GHB withdrawal symptoms was observed after phenobarbital in all cases and there were no adverse events related to phenobarbital. DISCUSSION AND CONCLUSION: This case series suggests that phenobarbital for the management of benzodiazepine-resistant GHB withdrawal can be safe, even in general inpatient settings, and may avert the progression of delirium. Most data on the management of GHB withdrawal comes from case reports or series, such as this one. This highlights the need for prospective trials to establish an evidence base for therapeutic approaches, including validated measures of withdrawal severity and more information relating to the safe and effective dosing of phenobarbital.

Real-time Data Fusion Platforms: The Need of Multi-dimensional Data-driven Research in Biomedical Informatics.

Systems designed to expedite data preprocessing tasks such as data discovery, interpretation, and integration that are required before data analysis drastically impact the pace of biomedical informatics research. Current commercial interactive and real-time data integration tools are designed for large-scale business analytics requirements. In this paper we identify the need for end-to-end data fusion platforms from the researcher's perspective, supporting ad-hoc data interpretation and integration.