Types and Concentrations of Blood-Based Biomarkers in Adults With Peripheral Neuropathies: A Systematic Review and Meta-analysis.

Importance: Peripheral neuropathies are common conditions and can result in numbness, paresthesia, motor deficits, and pain. There is increasing evidence for the use of biomarkers as clinical indicators of the presence, severity, and prognosis of nerve lesions; however, biomarker identification has largely been focused on disorders of the central nervous system, and less is known about their role in the peripheral nervous system.

Objective: To assess blood-based biomarker concentrations associated with nerve involvement in patients with peripheral neuropathy compared with control participants.

Features and methods to discriminate between mechanism-based categories of pain experienced in the musculoskeletal system: a Delphi expert consensus study.

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.

Nerve pathology and neuropathic pain after whiplash injury: a systematic review and meta-analysis.

There is no clear understanding of the mechanisms causing persistent pain in patients with whiplash-associated disorder (WAD). The aim of this systematic review was to assess the evidence for nerve pathology and neuropathic pain in patients with WAD. EMBASE, PubMed, CINAHL (EBSCO), and MEDLINE were searched from inception to September 1, 2020.

Validation of a pain mechanism classification system (PMCS) in physical therapy practice.

The objective of this study was to validate the clinical application of a pain mechanism classification system (PMCS) in clinical practice. We analyzed data abstracted from the medical records of patients who were treated in the outpatient clinics of a large urban rehabilitation hospital in Chicago. We hypothesized that there would be good agreement between the PMCS determined by trained therapists and the PMCS category assigned based on a computer-generated statistical model using patients' signs and symptoms.