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Papers of the Week


Papers: 2 Nov 2019 - 8 Nov 2019


Human Studies


2020 Mar


Pain


161


3

Biomarkers for predicting central neuropathic pain occurrence and severity after spinal cord injury: results of a long-term longitudinal study.

Authors

Gruener H, Zeilig G, Gaidukov E, Rachamim-Katz O, Ringler E, Blumen N, Engel-Haber E, Defrin R
Pain. 2020 Mar; 161(3):545-556.
PMID: 31693542.

Abstract

Central neuropathic pain (CNP) after spinal cord injury (SCI) is debilitating and immensely impacts the individual. CNP is relatively resistant to treatment administered after it develops, perhaps owing to irreversible pathological processes. Although preemptive treatment may overcome this shortcoming, its administration necessitates screening patients with clinically relevant biomarkers that could predict CNP early post-SCI. The aim was to search for such biomarkers by measuring pro-nociceptive and for the first time, anti-nociceptive indices early post-SCI.Participantswere 47 patients with acute SCI and 20 healthy controls (HC). Pain adaptation, conditioned pain modulation (CPM), pain temporal summation (TSP), windup pain, and allodynia were measured above, at, and below the injury level, at 1.5 months post-SCI. HC were tested at corresponding regions. SCI patients were monitored for CNP emergence and characteristics at 3-4, 6-7, and 24 months post-SCI.CNP prevalence was 57.4%. CNP severity, quality and aggravating factors but not location somewhat changed over 24 months. SCI patients who eventually developed CNP exhibited early, reduced at-level pain adaptation and CPM magnitudes than those who did not. The best predictor for CNP emergence at 3-4 and 7-8 months was at-level pain adaptation with odds ratios of 3.17 and 2.83, respectively (∼77% probability) and a cut-off value with 90% sensitivity. Allodynia and at-level CPM predicted CNP severity at 3-4 and 24 months, respectively.Reduced pain inhibition capacity precedes, and may lead to CNP. At-level pain adaptation is an early CNP biomarker with which individuals at risk can be identify to initiate preemptive treatment.