Leveraging Accelerometry as a Prognostic Indicator for Increase in Opioid Withdrawal Symptoms

Tamara P. Lambert; Asim H. Gazi; Anna B. Harrison; Sevda Gharehbaghi; Michael Chan; Malik Obideen; Parvaneh Alavi; Nancy Murrah; Lucy Shallenberger; Emily G. Driggers; Rebeca Alvarado Ortega; Brianna Washington; Kevin M. Walton; Yi-Lang Tang; Rahul Gupta; Jonathon A. Nye; Justine W. Welsh; Viola Vaccarino; Amit J. Shah; J. Douglas Bremner; Omer T. Inan

Leveraging Accelerometry as a Prognostic Indicator for Increase in Opioid Withdrawal Symptoms

2022

Treating opioid use disorder (OUD) is a significant healthcare challenge in the United States. Remaining abstinent from opioids is challenging for individuals with OUD due to withdrawal symptoms that include restlessness. However, to our knowledge, studies of acute withdrawal have not quantified restlessness using involuntary movements. We hypothesized that wearable accelerometry placed mid-sternum could be used to detect withdrawal-related restlessness in patients with OUD. To study this, 23 patients with OUD undergoing active withdrawal participated in a protocol involving wearable accelerometry, opioid cues to elicit craving, and non-invasive Vagal Nerve Stimulation (nVNS) to dampen withdrawal symptoms. Using accelerometry signals, we analyzed how movements correlated with changes in acute withdrawal severity, measured by the Clinical Opioid Withdrawal Scale (COWS). Our results revealed that patients demonstrating sinusoidal–i.e., predominantly single-frequency oscillation patterns in their motion almost exclusively demonstrated an increase in the COWS, and a strong relationship between the maximum power spectral density and increased withdrawal over time, measured by the COWS (R = 0.92, <i>p</i> = 0.029). Accelerometry may be used in an ambulatory setting to indicate the increased intensity of a patient’s withdrawal symptoms, providing an objective, readily-measurable marker that may be captured ubiquitously.

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