Clinical guidelines recommend epidural steroid injection (ESI) for severe sciatica but there is uncertainty of effectiveness. The POiSE study aims to identify factors, routinely collected in clinical practice that predict outcome in patients who have ESI. This presentation describes characteristics and early clinical outcomes of POiSE participants. Prospective cohort study in 19 NHS spinal services in England, inviting patients with sciatica listed for an ESI. Participant baseline characteristics and 6-week follow-up outcomes are presented. Outcomes include pain intensity (0–10 NRS), disability (Oswestry Disability Index 0–100) and global change in symptoms.Background
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Clinical guidelines recommend epidural steroid injection (ESI) as a treatment option for severe disc-related sciatica, but there is considerable uncertainty about its effectiveness. Currently, we know very little about factors that might be associated with good or poor outcomes from ESI. The aim of this systematic review was to synthesize and appraise the evidence investigating prognostic factors associated with outcomes following ESI for patients with imaging confirmed disc-related sciatica. The search strategy involved the electronic databases Medline, Embase, CINAHL Plus, PsycINFO and reference lists of eligible studies. Selected papers were quality appraised independently by two reviewers using the Quality in Prognosis Studies (QUIPS) tool. Between study heterogeneity precluded statistical pooling of results.Background
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Guidelines recommend epidural steroid injections (ESI) for treating severe disc-related sciatica based on trial data showing modest reductions in leg pain, disability and surgery avoidance. Despite their widespread use, there is no clear evidence about which patients are more likely to benefit from ESI. The aim of this study was to generate consensus on potential predictors of outcome following ESI for disc-related sciatica to include in data collection in a future cohort study. A list of potential predictors of outcome following ESI was generated from existing literature and a consensus meeting with seven experts. Items were subsequently presented in a two-round on-line modified Delphi study to generate consensus among experts on which items are agreed as potential predictors of outcome from ESI (consensus defined as 70% agreement with ranking of remaining items).Background
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The EU-funded Back-UP project aims to develop a cloud computer platform to guide the treatment of low back and neck pain (LBNP) in first contact care and early rehabilitation. In order to identify evidence-based treatment options that can be recommended and are accessible to people with LBNP across Europe, we conducted a systematic review of recently published guidelines. Electronic databases, including Medline, Embase, CINAHL, PsycINFO, HMIC, Epistemonikos, PEDro, TRIP, NICE, SIGN, WHO, Guidelines International Network (G-I-N) and DynaMed Plus were searched. We searched for guidelines published by European health professional or guideline development organisations since 2013, focusing on the primary care management of adult patients presenting with back or neck pain (including whiplash associated symptoms, radicular pain, and pregnancy-related LBP). The AGREE-II tool was used to assess the quality of guideline development and reporting.Background and aims
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Criticisms about overuse of MRI in low back pain are well documented. Yet, with the exception of suspicion of serious pathology, little is known about factors that influence clinicians' preference for MRI. We investigated the factors associated with physiotherapists' preference for MRI for patients consulting with benign low back and leg pain (LBLP) including sciatica. Data were collected from 607 primary care patients consulting with LBLP and assessed by 7 physiotherapists, in the ATLAS cohort study. Following clinical assessment, physiotherapists documented whether he/she wanted the patient to have an MRI. Factors potentially associated with clinicians' preference for imaging were selected a priori, from patient characteristics and clinical assessment findings. A mixed-effect logistic regression model examined the associations between these factors and physiotherapists' preference for MRI.Background
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Recruitment to time and target in clinical trials is a key challenge requiring careful estimation of numbers of potential participants. The SCOPiC trial ((HTA 12/201/09) (ISRCTN75449581)) is investigating the clinical and cost-effectiveness of stratified care for patients with sciatica in primary care. Here, we describe the approaches followed to achieve recruitment of our required sample size (n=470), the challenges encountered and required adaptations. We used recruitment data from the SCOPiC trial and its internal pilot, to show the differences between estimated and actual numbers of patients from consultation to participation in the trial. Patients were consented to the trial if they had a clinical diagnosis of sciatica (with at least 70% confidence) and met the trial eligibility criteria.Background
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Low back-related leg pain (LBLP) is clinically diagnosed as referred leg pain or sciatica. Within the spectrum of LBLP there may be unrecognised subgroups of patients. This study aimed to identify and describe clusters of LBLP patients using latent class analysis (LCA). 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 described and compared to the clinically defined groups of LBLP patients.Background
Methods
Identification of nerve root involvement (NRI) in patients with low back-related leg pain (LBLP) can be challenging. Diagnostic models have mainly been developed in secondary care with conflicting reference standards and predictor selection. This study aims to ascertain which cluster of items from clinical assessment best identify NRI in primary care consulters with LBLP Cross-sectional data on 395 LBLP consulters were analysed. Potential NRI indicators were seven clinical assessment items. Two definitions of NRI formed the reference standards: (i) high confidence (≥80%) NRI clinical diagnosis (ii) high confidence (≥80%) NRI clinical diagnosis with confirmatory magnetic resonance imaging (MRI) findings. Multivariable logistic regression models were constructed and compared for both reference standards. Model performances were summarised using the Hosmer-Lemeshow statistic and area under the curve (AUC). Bootstrapping assessed internal validity.Background:
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Leg pain frequently accompanies low back pain and is associated with increased levels of disability and higher health costs than simple low back pain. Distinguishing between different types of low back- related leg pain (LBLP) is important for clinical management and research applications. The aim of this systematic review was to identify, describe and appraise papers that classify or subgroup populations with LBLP. The search strategy involved nine electronic databases including Medline and Embase, reference lists of eligible studies and relevant reviews. Selected papers were quality appraised independently by two reviewers using a standardised scoring tool.Background
Methods
Pain with radiation to the leg is a common presentation in back pain patients. Radiating leg pain is either referred pain or radicular, commonly described as sciatica. Clinically distinguishing between these types of leg pain is recognized as difficult but important for management purposes. The aim of this study was to investigate inter-therapist agreement when diagnosing referred or radicular pain. Thirty-six primary care consulters with low back-related leg pain were assessed and diagnosed as referred or radicular leg pain by one of six trained experienced musculoskeletal physiotherapists. Assessments were videoed, excluding any diagnosis discourse, and viewed by a second physiotherapist who made an independent diagnosis. Therapists rated their confidence with diagnosis and reasons for their decision. Data was summarized using percentage agreements and kappa (K) coefficients with two sided 95% confidence intervals (CI).Background
Methods