Objectives: The clinical course of lumbar radiculopathy following microdiscectomy and post-operative physiotherapy varies substantially. No prior studies assessed this variability by deriving outcome trajectories. The primary aims of this study were to evaluate the variability in long-term recovery after lumbar microdiscectomy followed by post-operative physiotherapy and to identify outcome trajectories. The secondary aim was to assess whether demographic, clinical characteristics and patient-reported outcome measures routinely collected at baseline could predict poor outcome trajectories.
Methods: We conducted a prospective cohort study with a 24-month follow-up. We included 479 patients with clinical signs and symptoms of lumbar radiculopathy confirmed by Magnetic Resonance Imaging findings, who underwent microdiscectomy and post-operative physiotherapy. Outcomes were leg pain and back pain measured with Visual Analogue Scales, and disability measured with the Roland-Morris Disability Questionnaire. Descriptive statistics were performed to present the average and the individual clinical course. A latent class trajectory analysis was conducted to identify leg pain, back pain, and disability outcome trajectories. The best number of clusters was determined using the Bayesian Information Criterion, Akaike's information criteria, entropy, and overall interpretability. Prediction models for poor outcome trajectories were assessed using multivariable logistic regression analyses.
Results: Several outcome trajectories were identified. Most patients were assigned to the 'large improvement' trajectory (leg pain: 79.3%; back pain: 70.2%; disability: 59.5% of patients). Smaller proportions of patients were assigned to the 'moderate improvement' trajectory (leg pain: 7.9%; back pain: 10.6%; disability: 20.7% of patients), the 'minimal improvement' trajectory (leg pain: 4.9%, back pain: 6.7%, disability: 16.3% of patients) and the 'relapse' trajectory (leg pain: 7.9%; back pain: 12.5%; disability: 3.5%). Approximately one-third of patients (32.6%) belonged to one or more than one poor outcome trajectory. Patients with previous treatment (prior back surgery, injection therapy, and medication use) and those who had higher baseline pain and disability scores were more likely to belong to the poor outcome trajectories in comparison to the large improvement trajectories in back pain, leg pain and disability, and the moderate improvement trajectory in disability. The explained variance (Nagelkerke R2) of the prediction models ranged from 0.06 to 0.13 and the discriminative ability (Area Under the Curve) from 0.66 to 0.73.
Conclusion: The clinical course of lumbar radiculopathy varied following microdiscectomy and post-operative physiotherapy, and several outcome trajectories could be identified. Although most patients were allocated to favorable trajectories, one in three patients was assigned to one or more poor outcome trajectories following microdiscectomy and post-operative physiotherapy for lumbar radiculopathy. Routinely gathered data were unable to predict the poor outcome trajectories accurately. Prior to surgery, clinicians should discuss the high variability and the distinctive subgroups that are present in the clinical course with their patients.
Keywords: Disc herniation; Latent class analysis; Neurosurgery; Physical therapy; Sciatica.
Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.