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Ideal management of alcohol withdrawal syndrome (AWS) incorporates a symptom driven approach, whereby patients are regularly assessed using a standardized scoring system (Clinical Institute Withdrawal Assessment for Alcohol-Revised; CIWA-Ar) and treated according to severity. Among the domains assessed by the CIWA-Ar, tremor is the most objective indicator of withdrawal severity, however, the ability of clinicians to reliably quantify tremor is highly dependent on experience. The objective of this study was to prospectively validate an objective, reliable tool to standardize and quantify the severity of alcohol withdrawal tremor using the built-in accelerometer of an iOS application.  Methods:  A prospective observational study of patients ≥18 years presenting to an academic emergency department in alcohol withdrawal was conducted from Oct 2014 to Aug 2015. Assessments were videotaped by a research assistant and subsequently reviewed by 3 clinical experts, blinded to the primary clinical assessment. Tremor severity was scored using the 8-point CIWA scale (0=no tremor, 7=severe tremor). Accelerometer derived results were compared to expert assessments of each video. Inter-rater agreement was estimated using Cohen’s kappa ( k ) statistic.  Results:  76 patients with 78 tremor recordings were included. Accelerometer derived tremor scores matched exactly with expert assessor scores in 36 (46.2%) cases, within 1 point for 73 (93.6%) cases and differed by ≥ 2 points in 5 (6.4%) cases. The overall kappa for agreement within 1 point for tremor severity was ‘very good’ 0.92 (95% CI: 0.86, 0.99).  Conclusion:  iOS accelerometer based assessment of the tremor component of the CIWA-Ar score is reliable and has potential to more accurately assess the severity of patients in alcohol withdrawal. We anticipate this resource will be easily disseminated and will impact and improve the care of patients with alcohol withdrawal.

LO028: Prospective validation of an iOS app to evaluate tremor in patients with alcohol withdrawal syndrome