Evaluation of work-related psychosocial factors and regional musculoskeletal pain: results from a EULAR Task Force

Objectives: to establish whether review articles provide consistent conclusions on associations between workplace psychosocial factors and musculoskeletal pain and, if differences exist, to explore whether this is related to the methods used.Methods: reviews, reported up to February 2007, that included consideration of workplace psychosocial factors and upper limb, back or knee pain were identified through searches of multiple databases. The specific work-related psychosocial factors considered were job demands, support, job autonomy and job satisfaction. The conclusions of each review on one or more of the psychosocial/musculoskeletal pain associations were extracted.Results: 15 review articles were identified that considered one or more of the regional pain syndromes included in the study. For back pain, the most consistent conclusions (four reviews positive out of six) were with high job demands and low job satisfaction. The studies of upper limb pain were exclusively related to shoulder and/or neck pain, and the most consistent positive conclusions were with high and low job demands (four reviews positive out of six and two reviews positive out of three, respectively). For knee pain, only a single review was identified. For individual reviews of back and upper limb pain, there were marked differences in the number of associations concluded to be positive between reviews.Conclusions: the reasons for reviews coming to different conclusions included that they were often evaluating different bodies of evidence (according to their search criteria, the year when the review was conducted, the role that quality assessment played in whether studies contributed to evidence, and the combination of risk factors addressed in individual studies), but more important was whether the review specified explicit criteria for making conclusions on strength of evidence. These conclusions emphasise the importance of developing standardised methods for conducting such evaluations of existing evidence and the importance of new longitudinal studies for clarifying the temporal relationship between psychosocial factors and musculoskeletal pain in the workplac

Factors Influencing the Participation of Older People in Clinical Trials : Data Analysis from the MAVIS Trial

Peer reviewedPostprin

Prognosis research strategy (PROGRESS) 1: a framework for researching clinical outcomes

Understanding and improving the prognosis of a disease or health condition is a priority in clinical research and practice. In this article, the authors introduce a framework of four interrelated themes in prognosis research, describe the importance of the first of these themes (understanding future outcomes in relation to current diagnostic and treatment practices), and introduce recommendations for the field of prognosis researc

The science of clinical practice: disease diagnosis or patient prognosis? Evidence about "what is likely to happen" should shape clinical practice.

BACKGROUND: Diagnosis is the traditional basis for decision-making in clinical practice. Evidence is often lacking about future benefits and harms of these decisions for patients diagnosed with and without disease. We propose that a model of clinical practice focused on patient prognosis and predicting the likelihood of future outcomes may be more useful. DISCUSSION: Disease diagnosis can provide crucial information for clinical decisions that influence outcome in serious acute illness. However, the central role of diagnosis in clinical practice is challenged by evidence that it does not always benefit patients and that factors other than disease are important in determining patient outcome. The concept of disease as a dichotomous 'yes' or 'no' is challenged by the frequent use of diagnostic indicators with continuous distributions, such as blood sugar, which are better understood as contributing information about the probability of a patient's future outcome. Moreover, many illnesses, such as chronic fatigue, cannot usefully be labelled from a disease-diagnosis perspective. In such cases, a prognostic model provides an alternative framework for clinical practice that extends beyond disease and diagnosis and incorporates a wide range of information to predict future patient outcomes and to guide decisions to improve them. Such information embraces non-disease factors and genetic and other biomarkers which influence outcome. SUMMARY: Patient prognosis can provide the framework for modern clinical practice to integrate information from the expanding biological, social, and clinical database for more effective and efficient care

Individual participant data meta‐analysis to examine linear or non‐linear treatment‐covariate interactions at multiple time‐points for a continuous outcome

Individual participant data (IPD) meta‐analysis projects obtain, harmonise, and synthesise original data from multiple studies. Many IPD meta‐analyses of randomised trials are initiated to identify treatment effect modifiers at the individual level, thus requiring statistical modelling of interactions between treatment effect and participant‐level covariates. Using a two‐stage approach, the interaction is estimated in each trial separately and combined in a meta‐analysis. In practice, two complications often arise with continuous outcomes: examining non‐linear relationships for continuous covariates and dealing with multiple time‐points. We propose a two‐stage multivariate IPD meta‐analysis approach that summarises non‐linear treatment‐covariate interaction functions at multiple time‐points for continuous outcomes. A set‐up phase is required to identify a small set of time‐points; relevant knot positions for a spline function, at identical locations in each trial; and a common reference group for each covariate. Crucially, the multivariate approach can include participants or trials with missing outcomes at some time‐points. In the first stage, restricted cubic spline functions are fitted and their interaction with each discrete time‐point is estimated in each trial separately. In the second stage, the parameter estimates defining these multiple interaction functions are jointly synthesised in a multivariate random‐effects meta‐analysis model accounting for within‐trial and across‐trial correlation. These meta‐analysis estimates define the summary non‐linear interactions at each time‐point, which can be displayed graphically alongside confidence intervals. The approach is illustrated using an IPD meta‐analysis examining effect modifiers for exercise interventions in osteoarthritis, which shows evidence of non‐linear relationships and small gains in precision by analysing all time‐points jointly

A tree-based decision model to support prediction of the severity of asthma exacerbations in children

This paper describes the development of a tree-based decision model to predict the severity of pediatric asthma exacerbations in the emergency department (ED) at 2 h following triage. The model was constructed from retrospective patient data abstracted from the ED charts. The original data was preprocessed to eliminate questionable patient records and to normalize values of age-dependent clinical attributes. The model uses attributes routinely collected in the ED and provides predictions even for incomplete observations. Its performance was verified on independent validating data (split-sample validation) where it demonstrated AUC (area under ROC curve) of 0.83, sensitivity of 84%, specificity of 71% and the Brier score of 0.18. The model is intended to supplement an asthma clinical practice guideline, however, it can be also used as a stand-alone decision tool

What predicts change in pulmonary function and quality of life in asthma or COPD ?

Information about predictors of decline in pulmonary function (forced expiratory volume in 1 second [FE

Buprenorphine versus dihydrocodeine for opiate detoxification in primary care: a randomised controlled trial

Background Many drug users present to primary care requesting detoxification from illicit opiates. There are a number of detoxification agents but no recommended drug of choice. The purpose of this study is to compare buprenorphine with dihydrocodeine for detoxification from illicit opiates in primary care. Methods Open label randomised controlled trial in NHS Primary Care (General Practices), Leeds, UK. Sixty consenting adults using illicit opiates received either daily sublingual buprenorphine or daily oral dihydrocodeine. Reducing regimens for both interventions were at the discretion of prescribing doctor within a standard regimen of not more than 15 days. Primary outcome was abstinence from illicit opiates at final prescription as indicated by a urine sample. Secondary outcomes during detoxification period and at three and six months post detoxification were recorded. Results Only 23% completed the prescribed course of detoxification medication and gave a urine sample on collection of their final prescription. Risk of non-completion of detoxification was reduced if allocated buprenorphine (68% vs 88%, RR 0.58 CI 0.35–0.96, p = 0.065). A higher proportion of people allocated to buprenorphine provided a clean urine sample compared with those who received dihydrocodeine (21% vs 3%, RR 2.06 CI 1.33–3.21, p = 0.028). People allocated to buprenorphine had fewer visits to professional carers during detoxification and more were abstinent at three months (10 vs 4, RR 1.55 CI 0.96–2.52) and six months post detoxification (7 vs 3, RR 1.45 CI 0.84–2.49). Conclusion Informative randomised trials evaluating routine care within the primary care setting are possible amongst drug using populations. This small study generates unique data on commonly used treatment regimens