Chronic widespread pain in children and adolescents presenting in primary care: prevalence and associated risk factors

PAIN(2022)

Cited 4|Views9
No score
Abstract
A significant proportion of children/adolescents report chronic widespread pain (CWP), but little is known about clinically relevant CWP or what factors lead to onset in this population. Objectives were to report the primary care consultation prevalence of CWP and investigate risk factors associated with onset. A validated algorithm for identifying CWP status from primary care electronic healthcare records was applied to a child or adolescent population (aged 8-18 years). The algorithm records patients who have recurrent pain consultations (axial skeleton and upper or lower limbs) or those with a nonspecific generalised pain disorder (eg, fibromyalgia). Prevalence was described, and a nested case-control study was established to identify risk factors associated with CWP onset using logistic regression producing odds ratios (ORs) and 95% confidence intervals (95% CIs). Two hundred seventy-one children or adolescents were identified with CWP, resulting in a 5-year consultation prevalence of 3.19%. Risk factors significantly associated with CWP onset were as follows: mental health (eg, anxiety/neurosis consultations), neurological (eg, headaches), genitourinary (eg, cystitis), gastrointestinal (eg, abdominal pain), and throat problems (eg, sore throats). Children or adolescents with 1 or 2 risk factors (OR 2.15, 95% CI 1.6-2.9) or 3 or more risk factors (OR 9.17, 95% CI 5.9-14.3) were at significantly increased odds of CWP onset compared with those with none. Findings show a significant proportion of the child or adolescent primary care population has CWP. Most risk factors involved pain-related conditions, suggesting potential pathways of pain development. Further work is now needed to better understand the development of CWP in children and adolescents.
More
Translated text
Key words
Chronic widespread pain, Primary care, Risk, Children, Adolescents, Electronic healthcare records
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined