Exploring the Abilities of Peripheral Autonomic Parameters to Describe Pain: Another Dead End?

BACKGROUND: Pain is essential for survival, but it is also a major clinical, social, and economic problem that demands adequate management. The latter involves timely and accurate assessment, so several efforts have been made to develop accurate and reliable pain assessment tools. Advances in objective pain assessment include a large body of work focused on determining whether autonomic-mediated peripheral responses can be used to predict pain intensity. However, there is still no clinically validated autonomic marker for objective pain assessment. OBJECTIVES: In order to identify possible causes of this situation, the present study reviews the most recent advances examining peripheral autonomic markers' ability to describe pain intensity. STUDY DESIGN: Systematic literature review. METHODS: We conducted an online search on PubMed using terms such as "pain assessment," "experimental pain," "autonomic arousal," "heart rate," "heart rate variability," "electrodermal activity," "pupillary diameter," and "blood pressure." Articles published from 2010 through 2020 examining the abilities of peripheral autonomic markers to describe experimental pain intensity were collected and reviewed. From each of the included studies, we extracted information regarding autonomic parameters and stimulation modalities used by experimenters, as well as the sample size, gender, and health condition of the patients. RESULTS: Twenty-six articles were included for analysis, from which only 2 studies reported the use of multiple modalities. Half of the documents reported sample sizes ranging from 20 to 50 patients, and only 3 studies used formal power calculation to determine the sample size. Most of the articles included only healthy patients, so the influence of age, gender, and pre-existing health conditions on the autonomic peripheral parameters' capabilities to reflect the experience of pain remains unexplored. LIMITATIONS: It is possible that several documents were not retrieved due to a potential search engine bias or the use of very specific terms. Furthermore, only studies reporting pain intensity as a unique measure of its severity were included. CONCLUSION: The measurement of autonomic responses elicited by experimentally induced pain is one crucial step toward the development of reliable pain assessment tools. Still, several issues need to be addressed before continuing to explore the use of autonomic parameters for the assessment of pain. It is also recommended that future research endeavors in capturing the singularity of the pain experience involve the measurement of both peripheral (end organs) and central (brain) autonomic responses to pain.

Computational modeling of peripheral pain: a commentary.

This commentary is intended to find possible explanations for the low impact of computational modeling on pain research. We discuss the main strategies that have been used in building computational models for the study of pain. The analysis suggests that traditional models lack biological plausibility at some levels, they do not provide clinically relevant results, and they cannot capture the stochastic character of neural dynamics. On this basis, we provide some suggestions that may be useful in building computational models of pain with a wider range of applications.