Novel approach to characterising individuals with low back-related leg pain: cluster identification with latent class analysis and 12-month follow-up

摘要

Traditionally, low back-related leg pain (LBLP) is diagnosed clinically as referred leg pain or sciatica (nerve root involvement). However, within the spectrum of LBLP we hypothesised that there may be other, unrecognised patient subgroups. This study aimed to identify clusters of LBLP patients using latent class analysis (LCA) and describe their clinical course.The study population were 609 LBLP primary care consulters. Variables from clinical assessment were included in the LCA. Characteristics of the statistically identified clusters were compared and their clinical course over one year was described.A five cluster solution was optimal. Cluster 1 (n=104) had mild leg pain severity and was considered to represent a referred leg pain group with no clinical signs suggesting nerve root involvement (sciatica). Cluster 2 (n=122), cluster 3 (n=188) and cluster 4 (n=69) had mild, moderate and severe pain and disability respectively and response to clinical assessment items suggested categories of mild, moderate and severe sciatica. Cluster 5 (n=126) had high pain and disability, longer pain duration, more comorbidities and was difficult to map to a clinical diagnosis.Most improvement for pain and disability was seen in the first four months for all clusters. At 12 months the proportion of patients reporting recovery ranged from 27% for cluster 5 to 45% for cluster 2 (mild sciatica).This is the first study that empirically shows the variability in profile and clinical course of patients with LBLP including sciatica. More homogenous groups were identified which could be considered in future clinical and research settings.