Development of an Algorithm to Perform a Comprehensive Study of Autonomic Dysreflexia in Animals with High Spinal Cord Injury Using a Telemetry Device

Journal of Visualized Experiments, 2016 · DOI: doi:10.3791/52809 · Published: July 29, 2016

Physiology Neurology Veterinary Medicine

Simple Explanation

Spinal cord injury (SCI) above the mid-thoracic level can lead to a potentially life-threatening hypertensive condition called autonomic dysreflexia (AD). This is often triggered by noxious or non-noxious somatic or visceral stimuli below the level of injury. One of the most common triggers of AD is the distension of pelvic viscera, such as during bladder and bowel distension or evacuation. This protocol presents a novel pattern recognition algorithm developed for a JAVA platform software to study the fluctuations of cardiovascular parameters as well as the number, severity and duration of spontaneously occurring AD events.

Study Duration

Not specified

Participants

Male Wistar rats at 7 weeks of age and weighing 300-350 g

Evidence Level

Not specified

Key Findings

1
The software characterizes spontaneous AD events by an increase in SBP greater than 20 mmHg accompanied by a decrease in HR of 40 bpm or greater.
2
The AD Detection software ensures the detected AD event is ‘real’ by checking for a HR drop of 40 bpm or greater with respect to the onset of the AD event.
3
The software can analyze oscillations in ABP and discern diurnal variations of hemodynamic parameters.

Research Summary

This protocol describes a detailed implementation of a novel JAVA platform AD Detection software which would be combined with a telemetry device, for a long-term thorough analysis of ABP in SCI-animals. This is the first software that allows for the characterization of ABP patterns to detect spontaneous AD events as they occur sporadically throughout the duration of the day. The novel AD Detection software efficiently, reliably and accurately detected and characterized spontaneous AD events in acute and chronic SCI animals.

Practical Implications

Improved AD Detection

The developed software provides a more accurate and reliable method for detecting and characterizing spontaneous AD events in SCI animals.

Potential Clinical Applications

The software may be applied as a vital tool clinically to monitor the onset of AD events in humans upon the advent of new continuous hemodynamic monitoring technologies.

Treatment Strategies

Detecting and characterizing AD events is critical for considering treatments for SCI patients, leading to improved patient outcomes.

Study Limitations

1
Telemetry devices are invasive and costly.
2
Recovery time after implantation is critically important for the survival of the animal.
3
There are currently no feasible noninvasive techniques available for humans that allow for chronic, beat by beat, monitoring of hemodynamic parameters.

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