Neurobiology of osteoarthritis: a systematic review and activation likelihood estimation meta-analysis.

Osteoarthritis (OA) affects 240 million people worldwide. Neuroimaging has been increasingly used to investigate brain changes in OA, however, there is considerable heterogeneity in reported results. The goal of this systematic review and meta-analysis was to synthesise existing literature and identify consistent brain alterations in OA. Six databases were searched from inception up to June, 2022. Full-texts of original human studies were included if they had: (i) neuroimaging data by site of OA (e.g. hand, knee, hip); (ii) data in healthy controls (HC); (iii) > 10 participants. Activation likelihood estimation (ALE) was conducted using GingerALE software on studies that reported peak activation coordinates and sample size. Our search strategy identified 6250 articles. Twenty-eight studies fulfilled the eligibility criteria, of which 18 were included in the meta-analysis. There were no significant differences in brain structure or function between OA and healthy control contrasts. In exploratory analysis, the right insula was associated with OA vs healthy controls, with less activity, connectivity and brain volume in OA. This region was implicated in both knee and hip OA, with an additional cluster in the medial prefrontal cortex observed only in the contrast between healthy controls and the hip OA subgroup, suggesting a possible distinction between the neural correlates of OA subtypes. Despite the limitations associated with heterogeneity and poor study quality, this synthesis identified neurobiological outcomes associated with OA, providing insight for future research. PROSPERO registration number: CRD42021238735.

Risk factors for low back pain outcome: Does it matter when they are measured?

BACKGROUND: The early identification of factors that increase risk of poor recovery from acute low back pain (LBP) is critical to prevent the transition to chronicity. Although most studies of risk factors for poor outcome in LBP tend to investigate the condition once it is already persistent, there is evidence to suggest that this differs from risk factors measured during the early-acute stage. This study aimed to identify early risk factors for poor outcome in the short- and long-term in individuals with acute LBP, and to compare this with factors identified at 3 months in the same cohort. METHODS: One hundred and thirty-three individuals were recruited within 2 weeks of an acute LBP episode and completed questionnaires related to their sociodemographic, psychological, clinical and history/treatment status at baseline and 3 months later, and their pain-level fortnightly for 12 months. RESULTS: Of the 133 participants recruited, follow-up data were provided by 120 at 3 months, 97 at 6 months, 85 at 9 months and 94 at 12 months. Linear regression identified various factors at baseline (acute phase) and 3 months later that predicted short- and long-term outcome (pain level, change in pain). Key findings were that: (1) depressive symptoms at baseline most consistently predicted worse outcome; (2) psychological factors in general at 3 months were more predictive of outcome than when measured at baseline; (3) early health care utilization predicted better outcome, whereas use of pain medication later (3 months) predicted worse outcome; and (4) sex and BMI predicted outcome inconsistently over 12-months. CONCLUSIONS: The results highlight the multidimensional nature of risk factors for poor outcome in LBP and the need to consider time variation in these factors. Significance This study attempts to consider the impact of time variation of candidate risk factors on long-term outcome from the very early onset of acute low back pain. Risk factors across domains (sociodemographic, psychological, clinical, history/treatment) were identified, but their relationship with outcome often depended on when (acute phase vs. 3 months later) they were measured after back pain onset. Findings highlight the need to consider both a diverse range of factors and their potential time variance when assessing risk of poor outcome.