The journal of pain : official journal of the American Pain Society
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Randomized Controlled Trial
An Exploratory Human Laboratory Experiment Evaluating Vaporized Cannabis in the Treatment of Neuropathic Pain from Spinal Cord Injury and Disease.
Using 8-hour human laboratory experiments, we evaluated the analgesic efficacy of vaporized cannabis in patients with neuropathic pain related to injury or disease of the spinal cord, most of whom were experiencing pain despite traditional treatment. After obtaining baseline data, 42 participants underwent a standardized procedure for inhaling 4 puffs of vaporized cannabis containing either placebo, 2.9%, or 6.7% delta 9-THC on 3 separate occasions. A second dosing occurred 3 hours later; participants chose to inhale 4 to 8 puffs. This flexible dosing was used to attempt to reduce the placebo effect. Using an 11-point numerical pain intensity rating scale as the primary outcome, a mixed effects linear regression model showed a significant analgesic response for vaporized cannabis. When subjective and psychoactive side effects (eg, good drug effect, feeling high, etc) were added as covariates to the model, the reduction in pain intensity remained significant above and beyond any effect of these measures (all P < .0004). Psychoactive and subjective effects were dose-dependent. Measurement of neuropsychological performance proved challenging because of various disabilities in the population studied. Because the 2 active doses did not significantly differ from each other in terms of analgesic potency, the lower dose appears to offer the best risk-benefit ratio in patients with neuropathic pain associated with injury or disease of the spinal cord. ⋯ A crossover, randomized, placebo-controlled human laboratory experiment involving administration of vaporized cannabis was performed in patients with neuropathic pain related to spinal cord injury and disease. This study supports consideration of future research that would include longer duration studies over weeks to months to evaluate the efficacy of medicinal cannabis in patients with central neuropathic pain.
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There is increasing recognition that many if not most common chronic pain conditions are heterogeneous with a high degree of overlap or coprevalence of other common pain conditions along with influences from biopsychosocial factors. At present, very little attention is given to the high degree of overlap of many common pain conditions when recruiting for clinical trials. As such, many if not most patients enrolled into clinical studies are not representative of most chronic pain patients. The failure to account for the heterogeneous and overlapping nature of most common pain conditions may result in treatment responses of small effect size when these treatments are administered to patients with chronic overlapping pain conditions (COPCs) represented in the general population. In this brief review we describe the concept of COPCs and the putative mechanisms underlying COPCs. Finally, we present a series of recommendations that will advance our understanding of COPCs. ⋯ This brief review describes the concept of COPCs. A mechanism-based heuristic model is presented and current knowledge and evidence for COPCs are presented. Finally, a set of recommendations is provided to advance our understanding of COPCs.
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Accurate classification of chronic pain conditions requires reliable and valid pain assessment. Moreover, pain assessment serves several additional functions, including documenting the severity of the pain condition, tracking the longitudinal course of pain, and providing mechanistic information. Thorough pain assessment must address multiple domains of pain, including the sensory and affective qualities of pain, temporal dimensions of pain, and the location and bodily distribution of pain. Where possible, pain assessment should also incorporate methods to identify pathophysiological mechanisms underlying the pain. This article discusses assessment of chronic pain, including approaches available for assessing multiple pain domains and for addressing pathophysiological mechanisms. We conclude with recommendations for optimal pain assessment. ⋯ Pain assessment is a critical prerequisite for accurate pain classification. This article describes important features of pain that should be assessed, and discusses methods that can be used to assess the features and identify pathophysiological mechanisms contributing to pain.
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The past few decades have witnessed a huge leap forward in our understanding of the mechanistic underpinnings of pain, in normal states where it helps protect from injury, and also in pathological states where pain evolves from a symptom reflecting tissue injury to become the disease itself. However, despite these scientific advances, chronic pain remains extremely challenging to manage clinically. Although the number of potential treatment targets has grown substantially and a strong case has been made for a mechanism-based and individualized approach to pain therapy, arguably clinicians are not much more advanced now than 20 years ago, in their capacity to either diagnose or effectively treat their patients. The gulf between pain research and pain management is as wide as ever. We are still currently unable to apply an evidence-based approach to chronic pain management that reflects mechanistic understanding, and instead, clinical practice remains an empirical and often unsatisfactory journey for patients, whose individual response to treatment cannot be predicted. In this article we take a common and difficult to treat pain condition, chronic low back pain, and use its presentation in clinical practice as a framework to highlight what is known about pathophysiological pain mechanisms and how we could potentially detect these to drive rational treatment choice. We discuss how present methods of assessment and management still fall well short, however, of any mechanism-based or precision medicine approach. Nevertheless, substantial improvements in chronic pain management could be possible if a more strategic and coordinated approach were to evolve, one designed to identify the specific mechanisms driving the presenting pain phenotype. We present an analysis of such an approach, highlighting the major problems in identifying mechanisms in patients, and develop a framework for a pain diagnostic ladder that may prove useful in the future, consisting of successive identification of 3 steps: pain state, pain mechanism, and molecular target. Such an approach could serve as the foundation for a new era of individualized/precision pain medicine. The Analgesic, Anesthetic, and Addiction Clinical Trial Translations, Innovations, Opportunities, and Networks (ACTTION)-American Pain Society (APS) Pain Taxonomy (AAPT) includes pain mechanisms as 1 of the 5 dimensions that need to be considered when making a diagnostic classification. The diagnostic ladder proposed in this article is consistent with and an extension of the AAPT. ⋯ We discuss how identifying the specific mechanisms that operate in the nervous system to produce chronic pain in individual patients could provide the basis for a targeted and rational precision medicine approach to controlling pain, using chronic low back pain as our example.
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The Analgesic, Anesthetic, and Addiction Clinical Trial Translations, Innovations, Opportunities, and Networks-American Pain Society Pain Taxonomy (AAPT) is designed to be an evidence-based multidimensional chronic pain classification system that will facilitate more comprehensive and consistent chronic pain diagnoses, and thereby enhance research, clinical communication, and ultimately patient care. Core diagnostic criteria (dimension 1) for individual chronic pain conditions included in the initial version of AAPT will be the focus of subsequent empirical research to evaluate and provide evidence for their reliability and validity. Challenges to validating diagnostic criteria in the absence of clear and identifiable pathophysiological mechanisms are described. Based in part on previous experience regarding the development of evidence-based diagnostic criteria for psychiatric disorders, headache, and specific chronic pain conditions (fibromyalgia, complex regional pain syndrome, temporomandibular disorders, pain associated with spinal cord injuries), several potential approaches for documentation of the reliability and validity of the AAPT diagnostic criteria are summarized. ⋯ The AAPT is designed to be an evidence-based multidimensional chronic pain classification system. Conceptual and methodological issues related to demonstrating the reliability and validity of the proposed AAPT chronic pain diagnostic criteria are discussed.