People with a spinal cord injury (SCI) have limited ability to move and feel sensation below the level of the SCI. Doctors and researchers have tests which determine the level of function and sensation, this test was developed by the American Spinal Cord Injury Association (ASIA) and has been modified over the years to improve use and sensitivity. Most recently, the ASIA Injury classification Scale (AIS) was modified in 2011, but this test does not include the evaluation of autonomic nervous system (ANS) impairment. However, people with SCI do have impairment of the ANS and this may adversely affect how organ systems in the body function. Specifically, ANS impairment tends to result in changes in heart rate and blood pressure that may relate to the level of the SCI, but this is not fully understood. In this investigation we hope to develop simple tests which will allow doctors and scientist the ability to measure the amount of ANS impairment to the cardiovascular system, specifically the heart. The first part of the study will be to determine the heart rate response to several tests (administration of drugs and physical challenges) which will change heart rate. These tests will be given to people with and without SCI and the heart rate response will be compared between people with and without SCI. The bigger the difference in the heart rate response to these test between people with and without SCI the greater degree of ANS impairment in the people with SCI. Once this heart rate difference is determined, several simple tests (deep breathing, saliva test, Valsalva) will be performed in people with and without SCI to again compare the heart rate response. The second part of this study will be to determine if the heart rate responses to the first set of tests (administration of drugs and physical challenges) can predict the heart rate response to these simple tests (deep breathing, saliva test, Valsalva). The aim of this study is to develop a simple battery of tests which can be easily used by doctors and scientists to determine the degree of ANS impairment to the heart in persons with SCI.
Study Type
OBSERVATIONAL
Enrollment
177
James J Peters VA Medical Center
The Bronx, New York, United States
Autonomic Classification
To characterize the individual level and completeness of autonomic impairment using simultaneous pharmacological and physical provocation in persons with SCI with varying AIS classifications of motor/sensory impairment. From these studies we anticipate a more precise diagnosis of the degree of autonomic cardiovascular impairment in individuals with SCI. Data from the pharmacologic and physical interventions will be used to determine the validity of currently available clinical tools used in other populations of autonomic failure to diagnose the degree of cardiovascular autonomic impairment for use in the SCI population.
Time frame: January 2015
Edrophonium chloride as a test of cardio-vagal receptor integrity at the sinoatrial (SA) node
The heart rate (HR) response to exogenous cholinergic stimulation with edrophonium will be compared at rest and during the CFT between the non-SCI and SCI. We expect the resting HR response to edrophonium will be comparable in individuals with SCI and non-SCI controls, suggesting integral SA-node receptor responsiveness to acetylcholine (vagal) stimulation.
Time frame: January 2015
Glycopyrrolate as a test of cardio-vagal efferent integrity
The HR response to the CFT (bradycardia) will be compared with and without glycopyrrolate in the SCI and non-SCI subjects. We expect the HR response to the CFT (endogenous stimulation of cardio-vagal efferent activation), which induces bradycardia, will be blunted following glycopyrrolate administration in the non-SCI control subjects, but the HR response to the CFT will be unaffected by glycopyrrolate in the SCI subjects.
Time frame: January 2015
Esmolol hydrochloride as a test of cardiac-specific (β1) sympathetic receptor integrity
To compare the HR response to β1 receptor blockade in the resting and head-up tilt (HUT) states between individuals with SCI and non-SCI controls. We expect the resting HR will be lower and the HR response to HUT will be blunted following administration of Esmolol in the non-SCI controls; these HR responses will be attenuated in persons with SCI, and the degree of blunting will be categorically delineated by level of lesion (i.e., above T1, T2-T6, T7 and below).
Time frame: January 2015
Cold Face Test
For the CFT, the data will be analyzed using a three-factor mixed ANOVA. The dependent variable will be 20 second average heart rate. The ANOVA will incorporate two between-subjects factors: 1) groups (levels = control, low paraplegia, high paraplegia, and tetraplegia), and 2) drug (levels = placebo, edrophonium, glycopyrrolate, glycopyrrolate \& esmolol). The within subjects factor is time (levels = pre-CFT and post-CFT). From our previous pilot studies examining differences in HR response to CFT between control subjects and subjects grouped by SCI level, we found mean differences between groups \> 11 beats per minute with a pooled standard deviation of \~ 8.5 beats per minute. Using these estimates, with 10 subjects per group we will have over 99% power to detect differences between groups at an alpha level of 0.05. Using a 50% more conservative effect size estimate, with 10 subjects per group we will have \~ 85% power to detect differences between groups at an alpha level of 0.05.
Time frame: January 2015
Head-up Tilt Test
For the HUT, the data will be analyzed using a three-factor mixed ANOVA. The dependent variable will be 20 second average heart rate. The ANOVA will incorporate two between-subjects factors: 1) groups (levels = control, low paraplegia, high paraplegia, and tetraplegia), and 2) drug (levels = placebo, edrophonium, glycopyrrolate, and glycopyrrolate + esmolol). The within subjects factor is time (levels = pre-HUT and post-HUT). From our previous pilot studies examining differences in HR response to HUT between control subjects and subjects grouped by SCI level, we found mean differences between groups \> 3 beats per minute with a pooled standard deviation of \~ 5 beats per minute. Using these estimates, with 10 subjects per group we will have 85% power to detect differences between groups at an alpha level of 0.05.
Time frame: January 2015
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