BackgroundThe reported prevalence of chronic pain after spinal cord injury (SCI) varies widely due, in part, to differences in the taxonomy of chronic pain. A widely used classification system is available to describe subcategories of chronic pain in SCI, but the prevalence of chronic pain in SCI based on this system is unknown.ObjectiveThe primary objective of this systematic review and meta-analysis is to determine the prevalence of chronic pain after SCI based on the International Spinal Cord Injury Pain (ISCIP) classification system.Evidence reviewA comprehensive search of databases from January 1980 to August 2019 was conducted. The risk of bias was assessed using a modified tool developed for uncontrolled studies. The Grading of Recommendations, Assessment, Development and Evaluation approach was used to assess certainty in prevalence estimates.FindingsA total of 1305 records were screened, and 37 studies met inclusion criteria. The pooled prevalence of overall chronic pain was 68% (95% CI 63% to 73%). The pooled prevalence of neuropathic pain in 13 studies was 58% (95% CI 49% to 68%); the pooled prevalence of musculoskeletal pain in 11 studies was 56% (95% CI 41% to 70%); the pooled prevalence of visceral pain in 8 studies was 20% (95% CI 11% to 29%) and the pooled prevalence of nociceptive pain in 2 studies was 45% (95% CI 13% to 78%). Meta-regression of risk of bias (p=0.20), traumatic versus non-traumatic etiology of injury (p=0.59), and studies where pain was a primary outcome (p=0.32) demonstrated that these factors were not significant moderators of heterogeneity. Certainty in prevalence estimates was judged to be low due to unexplained heterogeneity.ConclusionThis systematic review and meta-analysis extends the findings of previous studies by reporting the prevalence of chronic pain after SCI based on the ISCIP classification system, thereby reducing clinical heterogeneity in the reporting of pain prevalence related to SCI.
Anatomical Variations in Intrahepatic Bile Ducts: A Systematic Review, Meta-analysis, and Creation of a Prevalence-based Classification System
