Journal
PAIN
Volume 163, Issue 9, Pages 1812-1828Publisher
LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1097/j.pain.0000000000002577
Keywords
Pain mechanisms; Expert consensus; Clinical examination; Quantitative sensory testing; Imaging; Diagnostic tests; Questionnaires
Categories
Funding
- National Health and Medical Research Council (NHMRC) of Australia [APP1091302]
- University of Queensland
- NHMRC [APP1102905]
- Motor Accident Insurance Commission of Queensland
- National Institutes of Health [R01 AR073187, U24 NS112873, UH3 AR07638]
- Danish National Research Foundation [DNRF121]
- National Institute of Arthritis Musculoskeletal and Skin Disease of the National Institutes of Health (NIH) [R00AR071517]
- National Institute on Drug Abuse (NIDA) [K24 DA053564-01]
- Deutsche Forschungsgemeinschaft [SFB 1158]
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This study used the Delphi expert consensus method to identify classification features and generated a list of candidate features that could aid in discrimination between types of musculoskeletal pain.
Classification of musculoskeletal pain based on underlying pain mechanisms (nociceptive, neuropathic, and nociplastic pain) is challenging. In the absence of a gold standard, verification of features that could aid in discrimination between these mechanisms in clinical practice and research depends on expert consensus. 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. A group of international experts were recruited based on their expertise in the field of pain. The Delphi process involved 2 rounds: round 1 assessed expert opinion on features that are unique to a pain mechanism category or shared between 2 (based on a 40% agreement threshold); and round 2 reviewed features that failed to reach consensus, evaluated additional features, and considered wording changes. Forty-nine international experts representing a wide range of disciplines participated. Consensus was reached for 196 of 292 features presented to the panel (clinical examination-134 features, quantitative sensory testing-34, imaging and diagnostic testing-14, and pain-type questionnaires-14). From the 196 features, consensus was reached for 76 features as unique to nociceptive (17), neuropathic (37), or nociplastic (22) pain mechanisms and 120 features as shared between pairs of pain mechanism categories (78 for neuropathic and nociplastic pain). This consensus study generated a list of potential candidate features that are likely to aid in discrimination between types of musculoskeletal pain.
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