Chronic pain is a significant public health problem throughout the world. In the United States alone, chronic pain accounts for an estimated $61 billion a year in lost work productivity and is the leading cause of disability and reduced quality of life in the working population. Treatment of pain is therefore an important and active area of research. For each new treatment modality or drug developed, quantitative evaluation is necessary to judge its efficacy and optimal target population. Quantitative Sensory Testing (QST) provides a standardized and quantifiable methodology to study pain sensitivity in humans. A QST protocol describes a series of noxious and nonnoxious stimuli (e.g., heat, pressure, or electrical) delivered to a patient, and a semi-objective method for the patient to rate their perception of each stimulus. Using this information, clinicians are able estimate the level of a patient’s pain sensitivity. This information can be used in the diagnosis of the pain source, the prediction of future pain occurrence, or the assessment of treatment efficacy. In traditional QST, fairly rudimentary devices have been used to deliver stimuli, such as manual dolorimeters or von Frey filaments; however, these methods suffer from inaccuracies primarily due to their operator dependence. More sophisticated QST devices that are also available are large and difficult to use, thus limiting their clinical applicability. This paper presents the motivation, design, and evaluation of a novel pressure-type QST system termed the multimodal automated sensory testing (MAST) system. The system’s primary benefit is that it significantly reduces operator based experimental variability by automatically delivering stimuli and prompting the patient for feedback. In addition, its small size and ease of use allow it to be used clinically at the point-of-care. We present encouraging results illustrating that the MAST system offers reduced experimental variability and is able to discriminate between healthy human subjects and those with chronic pain. The advantages of using this type of device in clinical research will be highlighted with additional data showing that this system permits evaluation of response variability and tissue characteristics previously hidden in the measurement “noise” of current pressure-type QST systems.
Multimodal Automated Quantitative Sensory Testing System for Pain Research
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Kruger, G., Harte, S. E., Ichesco, E., Mitra, M., Cheok, S. K., Yun, X., Clauw, D. J., and Shih, A. (June 14, 2011). "Multimodal Automated Quantitative Sensory Testing System for Pain Research." ASME. J. Med. Devices. June 2011; 5(2): 027530. https://doi.org/10.1115/1.3590873
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