HOW CAN WE DISCRIMINATE BETWEEN PAIN MECHANISMS THAT EXPLAIN MUSCULOSKELETAL PAIN? A DELPHI EXPERT CONSENSUS STUDY

M. Shraim¹, M. Sterling¹, K. Sluka², P. Hodges¹

¹The University of Queensland, School of Health and Rehabilitation Science, Brisbane, Australia, ²University of Iowa, Department of Physical Therapy and Rehabilitation Science, Iowa City, United States

Background: Pain that manifests in the musculoskeletal system can be maintained by a variety of neurobiological mechanisms. According to the International Association for the Study of Pain, there are three major mechanism groups - nociceptive, neuropathic, and nociplastic pain. It is broadly agreed that identification of underlying mechanisms could guide personalisation of pain management, but there is a major challenge - there is considerable divergence of opinion and confusion regarding if and how the discrimination between pain mechanisms can be operationalised in clinical practice. Most experts agree that clusters of features that are characteristic of each pain mechanism might guide identification of the predominant mechanism that explains an individual’s pain. In the absence of a gold standard method, identification of the features that can aid this decision making depends on expert consensus.

Purpose: This Delphi expert consensus study aimed to:
(1) identify features and assessment findings that are unique to a pain mechanism category or shared between no more than 2 categories; and
(2) develop a ranked list of candidate features that could potentially discriminate between pain mechanisms.

Methods: A list of candidate features was developed from 2 extensive systematic reviews. A multidisciplinary group of international experts (including 2 consumers) were recruited based on their expertise in the field of pain. A Delphi process was undertake in 2 rounds. In round 1, candidate features were presented to experts who indicated which pain mechanisms would be indicated if the feature was identified in a patient. Features that were considered to be unique to one mechanism category or shared between 2 (based on a 40% agreement threshold) were identified. New features could be proposed. In round 2, features that failed to reach the threshold was confirmed, any newly proposed features were evaluated, and wording changes were considered.

Results: Forty-nine international experts representing a wide range of disciplines participated. From 292 candidate features, 196 were considered by at least 40% of the experts to be present in 1 or 2, but not 3 pain mechanisms categories. Of these features 134 were clinical examination features, 34 related to quantitative sensory testing, 14 involved imaging and diagnostic testing, and 14 were pain-type questionnaires. From the 196 features, 17 were considered unique to nociceptive, 37 to neuropathic, and 22 to nociplastic pain mechanisms. 120 features were considered to be shared between pairs of pain mechanism categories (e.g., 78 for neuropathic and nociplastic pain).

Conclusions: This consensus study generated a list of candidate features that are likely to aid in discrimination between types of musculoskeletal pain.

Implications: The list of candidate features can form the basis of an evidence-based assessment to discriminate between pain mechanism categories. Future work will refine the minimum set of measures required for identification of likely predominant pain mechanisms in a patient and whether classification leads to more effective outcomes from personalised management.

Funding acknowledgements: National Health and Medical Research Council (Australia)

Keywords:
Pain mechanism
personalised management
nociplastic pain

Topics:
Musculoskeletal
Pain & pain management
Orthopaedics

Did this work require ethics approval? Yes

Institution: The University of Queensland

Committee: Medical Research Ethics Committee

Ethics number: #2020002324