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Journal of neurotrauma · Feb 2017
Characterising the severity of autonomic cardiovascular dysfunction after spinal cord injury using a novel 24 hour ambulatory blood pressure analysis software.
- David W Popok, Christopher R West, Michele Hubli, Katharine D Currie, and Andrei V Krassioukov.
- 1 International Collaboration on Repair Discoveries (ICORD), University of British Columbia , Vancouver, British Columbia, Canada .
- J. Neurotrauma. 2017 Feb 1; 34 (3): 559-566.
AbstractCardiovascular disease is one of the leading causes of morbidity and mortality in the spinal cord injury (SCI) population. SCI may disrupt autonomic cardiovascular homeostasis, which can lead to persistent hypotension, irregular diurnal rhythmicity, and the development of autonomic dysreflexia (AD). There is currently no software available to perform automated detection and evaluation of cardiovascular autonomic dysfunction(s) such as those generated from 24 h ambulatory blood pressure monitoring (ABPM) recordings in the clinical setting. The objective of this study is to compare the efficacy of a novel 24 h ABPM Autonomic Dysfunction Detection Software against manual detection and to use the software to demonstrate the relationships between level of injury and the degree of autonomic cardiovascular impairment in a large cohort of individuals with SCI. A total of 46 individuals with cervical (group 1, n = 37) or high thoracic (group 2, n = 9) SCI participated in the study. Outcome measures included the frequency and severity of AD, frequency of hypotensive events, and diurnal variations in blood pressure and heart rate. There was good agreement between the software and manual detection of AD events (Bland-Altman limits of agreement = ±1.458 events). Cervical SCI presented with more frequent (p = 0.0043) and severe AD (p = 0.0343) than did high thoracic SCI. Cervical SCI exhibited higher systolic and diastolic blood pressure during the night and lower heart rate during the day than high thoracic SCI. In conclusion, our ABPM AD Detection Software was equally as effective in detecting the frequency and severity of AD and hypotensive events as manual detection, suggesting that this software can be used in the clinical setting to expedite ABPM analyses.
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