ABSTRACT
BACKGROUND AND OBJECTIVE: Pain is a major clinical challenge, and understanding the pathophysiology is critical for optimal management. The autonomic nervous system reacts to pain stimuli, and autonomic dysfunction may predict pain sensation. The most used assessment of autonomic function is based on electrocardiographic measures, and the ability of such measures to predict pain was investigated. DATABASES AND DATA TREATMENT: English articles indexed in PubMed and EMBASE were reviewed for eligibility and included when they reported electrocardiographic-derived measures' ability to predict pain response. The quality in prognostic studies (QUIPS) tool was used to assess the quality of the included articles. RESULTS: The search revealed 15 publications, five on experimental pain, five on postoperative pain, and five on longitudinal clinical pain changes, investigating a total of 1069 patients. All studies used electrocardiographically derived parameters to predict pain assessed with pain thresholds using quantitative sensory testing or different scales. Across all study modalities, electrocardiographic measures were able to predict pain. Higher parasympathetic activity predicted decreased experimental, postoperative, and long-term pain in most cases while changes in sympathetic activity did not consistently predict pain. CONCLUSIONS: Most studies demonstrated that parasympathetic activity could predict acute and chronic pain intensity. In the clinic, this may be used to identify which patients need more intensive care to prevent, for example postoperative pain and develop personalized chronic pain management. SIGNIFICANCE: Pain is a debilitating problem, and the ability to predict occurrence and severity would be a useful clinical tool. Basal autonomic tone has been suggested to influence pain perception. This systematic review investigated electrocardiographic-derived autonomic tone and found that increased parasympathetic tone could predict pain reduction in different types of pain.
Subject(s)
Autonomic Nervous System , Chronic Pain , Humans , Pain Threshold , Pain Perception , Pain, PostoperativeABSTRACT
Emerging evidence suggest that quantitative sensory testing (QST) may predict the treatment response to pain-relieving therapies. This systematic review and meta-analysis focus on the predictive value of QST for pain management of knee osteoarthritis (OA). MEDLINE and EMBASE were systematically searched for all studies from year 2000 to 2023 on pretreatment QST and treatment of OA including surgical, pharmaceutical, and nonsurgical and nonpharmaceutical therapies. Preclinical studies and reviews were excluded. The systematic review followed the PRISMA guidelines and was pre-registered on the Open Science Framework website (link: https://osf.io/4FETK/, Identifier: DOI 10.17605/OSF.IO/4FETK). Meta-analysis were conducted to demonstrate the strength of the pre-treatment QST predictions on pain outcomes after OA treatments. Sixteen surgical (all on total knee arthroplasty [TKA], N = 1967), 5 pharmaceutical (4 on non-steroidal anti-inflammatory drugs [NSAIDs], N = 271), and 4 exercise-based therapy studies (N = 232) were identified. Pretreatment QST parameters predicted pain-relieving treatment outcomes in 81% of surgical, 100% of pharmaceutical, and 50% of exercise-based therapy studies. Meta-analyses found pretreatment QST profiles to predicted pain outcomes after TKA (random effects: 0.309, 95% confidence interval [CI]: 0.206-0.405, P < 0.001), NSAIDs (random effects: 0.323, 95% CI: 0.194-0.441, P < 0.001), and exercise-based therapies (random effects: 0.417, 95% CI: 0.138-0.635, P = 0.004). The overall risk of bias for the included studies was low to moderate. This systematic review and meta-analysis demonstrate weak-to-moderate associations between pretreatment QST and pain outcomes after standard OA pain treatments. Based on this work, it is hypothesized that a subset of specific pain sensitive patients with OA exist and that these patients do not respond adequately to standard OA pain treatments.