Abstracts of Papers

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Alshelh, Z (University of Sydney, Sydney, New South Wales); Di. Pietro ...... Victorian Workcover Authority Health Disability and Strategy Group released.
Anaesth Intensive Care 2015 | 43:3

Abstracts of Papers 2015 Australian Pain Society 35th Annual Scientific Meeting, ‘Managing Pain: from Mechanism to Policy’, 15–18 March 2015, Brisbane Convention and Exhibition Centre, Queensland These abstracts are published as supplied and have not been subjected to editorial review, correction or styling.

Assessing sleep quality in low back pain: the validity of portable instruments Alsaadi, SM (University of Damman, Khobar, Saudi Arabia); McAuley, JM (University of New South Wales, Sydney, New South Wales); Hush, JM (Macquarie University, Sydney, New South Wales); Grunstein, RR (University of Sydney, Sydney, New South Wales); Bartlett, DJ (University of Sydney); McKeough, ZM (University of Sydney); Dungan, GC (University of Sydney); Maher, CG (University of Sydney).

Background and Aims: Although portable instruments have been used in the assessment of sleep disturbance for patients with low back pain, the accuracy of instruments in detecting sleep/wake episodes for this population is unknown. This study investigated the criterion validity of two portable instruments (Armband and Actiwatch) for assessing sleep disturbance in patients with low back pain. Methods: . 50 patients with low back pain had simultaneous overnight sleep recordings of Polysomnography (PSG), Armband and Actiwatch. Criterion validity was determined by calculating epoch-by-epoch agreement, sensitivity and specificity and prevalence and bias- adjusted kappa (PABAK) for sleep versus wake between both instruments and PSG. The relationship between PSG and the two instruments was assessed using intraclass correlation coefficients (ICC 2, 1), scatter plots and regression analyses. Results: Observed agreement with PSG was 85% for the Armband and 88% for the Actiwatch . Sensitivity was 0.90 for both instruments, specificity was 0.54 and 0.67 and PABAK was 0.69 and 0.77 for the Armband and Actiwatch respectively. The ICC (95% CI) was 0.76 (0.61 to 0.86) and 0.80 (0.46 to 0.92) for total sleep time, 0.52 (0.29 to 0.70) and 0.55 (0.14 to 0.77) for sleep efficiency, 0.64 (0.45 to 0.78) and 0.52 (0.23 to 0.73) for wake after sleep onset and 0.13 (-0.15 to 0.39) and 0.33 (-0.05 to 0.63) for sleep onset latency, for the Armband and Actiwatch, respectively.Conclusions: The Armband and the Actiwatch have varied criterion validity across the sleep parameters from excellent validity for measures of total sleep time, good validity for measures of sleep efficiency and wake after onset to poor validity for sleep onset latency.

Altered neural oscillations in neuropathic pain Alshelh, Z (University of Sydney, Sydney, New South Wales); Di Pietro, F (University of Sydney); Vickers, R (University of Sydney); Peck CC (University of Sydney); Murray, GM (University of Sydney); Henderson, LA (University of Sydney). Background and Aims: Trigeminal neuropathic pain (TNP) is an orofacial chronic pain condition characterised by sharp and shooting pain in the distribution of one or more branches of the trigeminal nerve. TNP is thought to reflect changes to the pattern of activity within the thalamocortical (TC) circuitry. Given this, we hypothesise that the pattern of activity in TC circuitry is altered in TNP, including changes in the ventral posteromedial thalamus (VPM), the

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somatosensory section of the thalamic reticular nucleus (TRN) and the somatosensory cortex. Further to these changes, we hypothesised changes in the pattern of activity at the primary synapse – the spinotrigeminal nucleus (SpV) in TNP. Methods: Thirteen TNP subjects (mean age 46.6) and 32 healthy controls (mean age 52.1) were recruited. Resting brain activity was measured using functional magnetic resonance imaging (fMRI). To assess on-going signal intensity fluctuations within the thalamus, a grid comprised of 3x3x3mm volumes of interest (VOI) was created. A frequency versus power domain was created for each VOI using a Fast Fourier Transform. Two sample t-tests (p