Generic prognostic factors for musculoskeletal pain in primary care: a systematic review.

OBJECTIVES: To summarise the evidence for generic prognostic factors across a range of musculoskeletal (MSK) conditions. SETTING: primary care. METHODS AND OUTCOMES: Comprehensive systematic literature review. MEDLINE, CINAHL, PsychINFO and EMBASE were searched for prospective cohort studies, based in primary care (search period-inception to December 2015). Studies were included if they reported on adults consulting with MSK conditions and provided data on associations between baseline characteristics (prognostic factors) and outcome. A prognostic factor was identified as generic when significantly associated with any outcome for 2 or more different MSK conditions. Evidence synthesis focused on consistency of findings and study quality. RESULTS: 14 682 citations were identified and 78 studies were included (involving more than 48 000 participants with 18 different outcome domains). 51 studies were on spinal pain/back pain/low back pain, 12 on neck/shoulder/arm pain, 3 on knee pain, 3 on hip pain and 9 on multisite pain/widespread pain. Total quality scores ranged from 5 to 14 (mean 11) and 65 studies (83%) scored 9 or more. Out of a total of 78 different prognostic factors for which data were provided, the following factors are considered to be generic prognostic factors for MSK conditions: widespread pain, high functional disability, somatisation, high pain intensity and presence of previous pain episodes. In addition, consistent evidence was found for use of pain medications not to be associated with outcome, suggesting that this factor is not a generic prognostic factor for MSK conditions. CONCLUSIONS: This large review provides new evidence for generic prognostic factors for MSK conditions in primary care. Such factors include pain intensity, widespread pain, high functional disability, somatisation and movement restriction. This information can be used to screen and select patients for targeted treatment in clinical research as well as to inform the management of MSK conditions in primary care

Lateral epicondylitis in general practice: Course and prognostic indicators of outcome

Objective. To investigate the course of lateral epicondylitis and identify prognostic indicators associated with short- and longterm outcome of pain intensity. Methods. We prospectively followed patients (n = 349) from 2 randomized controlled trials investigating conservative interventions for lateral epicondylitis in primary care. Uni- and multivariate linear regression analyses were used to investigate the association between potential prognostic indicators and pain intensity (0-100 point scale) measured at 1,6, and 12 months after randomization. Potential prognostic factors were duration of elbow complaints, concomitant neck pain, concomitant shoulder pain, previous elbow complaints, baseline pain scores, age, gender, involvement of dominant side, social class, and work status. The variables "study" and "treatment" were included as covariates in all models. Results. Pain scores at 1 month followup were higher in patients with severe pain, a long duration of elbow complaints, and concomitant shoulder pain. At 12 month followup, the only different prognostic indicator for poor outcome was concomitant neck pain, in place of shoulder pain. Patients from higher social classes reported lower pain scores at 12 month followup than patients from lower social classes. Conclusions. Lateral epicondylitis seems to be a self-limiting condition in most patients. Long duration of elbow complaints, concomitant neck pain, and severe pain at presentation are associated with poor outcome at 12 months. Our results will help care providers give patients accurate information regarding their prognosis and assist in medical decision-making

Costs of shoulder pain in primary care consulters: a prospective cohort study in The Netherlands

BACKGROUND: Shoulder pain is common in primary care, and has an unfavourable outcome in many patients. Information on the costs associated with health care use and loss of productivity in patients with shoulder pain is very scarce. The objective of this study was to determine shoulder pain related costs during the 6 months after first consultation in general practice METHODS: A prospective cohort study consisting of 587 patients with a new episode of shoulder pain was conducted with a follow-up period of 6 months. Data on costs were collected by means of a cost diary during 6 months. RESULTS: 84% of the patients completed all cost diaries. The mean consumption of direct health care and non-health related care was low. During 6 months after first consultation for shoulder pain, the mean total costs a patient generated were €689. Almost 50% of this total concerned indirect costs, caused by sick leave from paid work. A small proportion (12%) of the population generated 74% of the total costs. CONCLUSION: The total costs in the 6 months after first consultation for shoulder pain in primary care, mostly generated by a small part of the population, are not alarmingly high

Patient characteristics and clinical management of patients with shoulder pain in U.S. primary care settings: Secondary data analysis of the National Ambulatory Medical Care Survey

BACKGROUND: Although shoulder pain is a commonly encountered problem in primary care, there are few studies examining its presenting characteristics and clinical management in this setting. METHODS: We performed secondary data analysis of 692 office visits for shoulder pain collected through the National Ambulatory Medical Care Survey (Survey years 1993–2000). Information on demographic characteristics, history and place of injury, and clinical management (physician order of imaging, physiotherapy, and steroid intraarticular injection) were examined. RESULTS: Shoulder pain was associated with an injury in one third (33.2% (230/692)) of office visits in this population of US primary care physicians. Males, and younger adults (age ≤ 52) more often associated their shoulder pain with previous injury, but there were no racial differences in injury status. Injury-related shoulder pain was related to work in over one-fifth (21.3% (43/202)) of visits. An x-ray was performed in 29.0% (164/566) of office visits, a finding that did not differ by gender, race, or by age status. Other imaging (CT scan, MRI, or ultrasound) was infrequently performed (6.5%, 37/566). Physiotherapy was ordered in 23.9% (135/566) of visits for shoulder pain. Younger adults and patients with a history of injury more often had physiotherapy ordered, but there was no significant difference in the ordering of physiotherapy by gender or race. Examination of the use of intraarticular injection was not possible with this data set. CONCLUSION: These data from the largest sample of patients with shoulder pain presenting to primary care settings offer insights into the presenting characteristics and clinical management of shoulder pain at the primary care level. The National Ambulatory Medical Care Survey is a useful resource for examining the clinical management of specific symptoms in U.S. primary care offices

Brief pain re-assessment provided more accurate prognosis than baseline information for low-back or shoulder pain

Background Research investigating prognosis in musculoskeletal pain conditions has only been moderately successful in predicting which patients are unlikely to recover. Clinical decision making could potentially be improved by combining information taken at baseline and re-consultation. Methods Data from four prospective clinical cohorts of adults presenting to UK and Dutch primary care with low-back or shoulder pain was analysed, assessing long-term disability at 6 or 12 months and including baseline and 4–6 week assessments of pain. Baseline versus short-term assessments of pain, and previously validated multivariable prediction models versus repeat assessment, were compared to assess predictive performance of long-term disability outcome. A hypothetical clinical scenario was explored which made efficient use of both baseline and repeated assessment to identify patients likely to have a poor prognosis and decide on further treatment. Results Short-term repeat assessment of pain was better than short-term change or baseline score at predicting long-term disability improvement across all cohorts. Short-term repeat assessment of pain was only slightly more predictive of long-term recovery (c-statistics 0.78, 95% CI 0.74 to 0.83 and 0.75, 95% CI 0.69 to 0.82) than a multivariable baseline prognostic model in the two cohorts presenting such a model (c-statistics 0.71, 95% CI 0.67 to 0.76 and 0.72, 95% CI 0.66 to 0.78). Combining optimal prediction at baseline using a multivariable prognostic model with short-term repeat assessment of pain in those with uncertain prognosis in a hypothetical clinical scenario resulted in reduction in the number of patients with an uncertain probability of recovery, thereby reducing the instances where patients may be inappropriately referred or reassured. Conclusions Incorporating short-term repeat assessment of pain into prognostic models could potentially optimise the clinical usefulness of prognostic information

Bone marrow mesenchymal stem cells do not enhance intra-synovial tendon healing despite engraftment and homing to niches within the synovium

Intra-synovial tendon injuries display poor healing, which often results in reduced functionality and pain. A lack of effective therapeutic options has led to experimental approaches to augment natural tendon repair with autologous mesenchymal stem cells (MSCs) although the effects of the intra-synovial environment on the distribution, engraftment and functionality of implanted MSCs is not known. This study utilised a novel sheep model which, although in an anatomically different location, more accurately mimics the mechanical and synovial environment of the human rotator cuff, to determine the effects of intra-synovial implantation of MSCs

Keele Aches and Pains Study Protocol: validity, acceptability and feasibility of the Keele STarT MSK Tool for subgrouping musculoskeletal patients in primary care

Musculoskeletal conditions represent a considerable burden worldwide, and are predominantly managed in primary care. Evidence suggests that many musculoskeletal conditions share similar prognostic factors. Systematically assessing patient’s prognosis, and matching treatments based on prognostic subgroups (stratified care), has been shown to be clinically and cost effective. This study (Keele Aches and Pains Study: KAPS) aims to refine and examine the validity of a brief questionnaire (Keele STarT MSK Tool), designed to enable risk-stratification of primary care patients with the five most common musculoskeletal pain presentations. We will also describe the subgroups of patients, and explore the acceptability and feasibility of using the tool, and how the tool is best implemented in clinical practice. The study design is mixed methods: a prospective, quantitative observational cohort study with a linked qualitative focus group and interview study. Patients who have consulted their General Practitioner or Healthcare Practitioner (GP/HCP) about a relevant musculoskeletal condition will be recruited from General practice. Participating patients will complete a baseline questionnaire (shortly after consultation), plus questionnaires 2 and 6 months later. A sub-sample of patients, along with participating GPs and HCPs, will be invited to take part in qualitative focus groups and interviews. The Keele STarT MSK Tool will be refined based on face, discriminant, construct and predictive validity at baseline and 2 months, and validated using data from 6 month follow-up. Patient and clinician perspectives about using the tool will be explored. This study will provide a validated prognostic tool (the Keele STarT MSK Tool) with established cut-points to stratify patients with the five most common musculoskeletal presentations into low, medium and high risk subgroups. The qualitative analysis of patient and healthcare perspectives will inform how to embed the tool into clinical practice using established general practice IT systems and clinician support packages

Study protocol for the development and internal validation of Schizophrenia Prediction of Resistance to Treatment (SPIRIT): a clinical tool for predicting risk of treatment resistance to antipsychotics in first-episode schizophrenia.

INTRODUCTION: Treatment-resistant schizophrenia (TRS) is associated with significant impairment of functioning and high treatment costs. Identification of patients at high risk of TRS at the time of their initial diagnosis may significantly improve clinical outcomes and minimise social and functional disability. We aim to develop a prognostic model for predicting the risk of developing TRS in patients with first-episode schizophrenia and to examine its potential utility and acceptability as a clinical decision tool. METHODS AND ANALYSIS: We will use two well-characterised longitudinal UK-based first-episode psychosis cohorts: Aetiology and Ethnicity in Schizophrenia and Other Psychoses and Genetics and Psychosis for which data have been collected on sociodemographic and clinical characteristics. We will identify candidate predictors for the model based on current literature and stakeholder consultation. Model development will use all data, with the number of candidate predictors restricted according to available sample size and event rate. A model for predicting risk of TRS will be developed based on penalised regression, with missing data handled using multiple imputation. Internal validation will be undertaken via bootstrapping, obtaining optimism-adjusted estimates of the model's performance. The clinical utility of the model in terms of clinically relevant risk thresholds will be evaluated using net benefit and decision curves (comparative to competing strategies). Consultation with patients and clinical stakeholders will determine potential thresholds of risk for treatment decision-making. The acceptability of embedding the model as a clinical tool will be explored using qualitative focus groups with up to 20 clinicians in total from early intervention services. Clinicians will be recruited from services in Stafford and London with the focus groups being held via an online platform. ETHICS AND DISSEMINATION: The development of the prognostic model will be based on anonymised data from existing cohorts, for which ethical approval is in place. Ethical approval has been obtained from Keele University for the qualitative focus groups within early intervention in psychosis services (ref: MH-210174). Suitable processes are in place to obtain informed consent for National Health Service staff taking part in interviews or focus groups. A study information sheet with cover letter and consent form have been prepared and approved by the local Research Ethics Committee. Findings will be shared through peer-reviewed publications, conference presentations and social media. A lay summary will be published on collaborator websites

The search for stable prognostic models in multiple imputed data sets

<p>Abstract</p> <p>Background</p> <p>In prognostic studies model instability and missing data can be troubling factors. Proposed methods for handling these situations are bootstrapping (B) and Multiple imputation (MI). The authors examined the influence of these methods on model composition.</p> <p>Methods</p> <p>Models were constructed using a cohort of 587 patients consulting between January 2001 and January 2003 with a shoulder problem in general practice in the Netherlands (the Dutch Shoulder Study). Outcome measures were persistent shoulder disability and persistent shoulder pain. Potential predictors included socio-demographic variables, characteristics of the pain problem, physical activity and psychosocial factors. Model composition and performance (calibration and discrimination) were assessed for models using a complete case analysis, MI, bootstrapping or both MI and bootstrapping.</p> <p>Results</p> <p>Results showed that model composition varied between models as a result of how missing data was handled and that bootstrapping provided additional information on the stability of the selected prognostic model.</p> <p>Conclusion</p> <p>In prognostic modeling missing data needs to be handled by MI and bootstrap model selection is advised in order to provide information on model stability.</p