Predicting outcome in acute low back pain using different models of patient profiling

Study Design: Prospective observational study of prognostic indicators, utilising data from a randomised, controlled trial of physiotherapy care of acute low back pain (ALBP) with follow up at 6 weeks, 3 months and 6 months. Objective: To evaluate which patient profile offers the most useful guide to long-term outcome in ALBP. Summary of Background Data: The evidence used to inform prognostic decision-making is derived largely from studies where baseline data is used to predict future status. Clinicians often see patients on multiple occasions so may profile patients in a variety of ways. It is worth considering if better prognostic decisions can be made from alternative profiles. Methods: Clinical, psychological and demographic data were collected from a sample of 54 ALBP patients. Three clinical profiles were developed from information collected at baseline, information collected at 6 weeks, and the change in status between these two time points. A series of regression models were used to determine the independent and relative contributions of these profiles to the prediction of chronic pain and disability. Results: The baseline profile predicted long-term pain only. The 6-week profile predicted both long-term pain and disability. The change profile only predicted long-term disability (p \u3c 0.01). When predicting long-term pain, after the baseline profile had been added to the model, the 6-week profile did not add significantly when forced in at the second step (p \u3e 0.05). A similar result was obtained when the order of entry was reversed. When predicting long-term disability, after the 6-week profile was entered at the first step, the change profile was not significant when forced in at the second step. However, when the change profile was entered at the first step and the 6-week clinical profile was forced in at the second step, a significant contribution of the 6-week profile was found. Conclusions: The profile derived from information collected at 6 weeks provided the best guide to long-term pain and disability. The baseline profile and change in status offered less predictive value

Multilocus sequence typing of Cronobacter spp. from powdered infant formula and milk powder production factories

This study applied the Cronobacter spp. multilocus sequence typing (MLST) scheme to three strain collections, then known as Enterobacter sakazakii, which had been isolated between 1988 and 2009 from 14 countries. The results revealed the predominance (85%) of C. 29 sakazakii (72 strains) in all three collections. The remaining strains were C. turicensis (10%), C. malonaticus (4%), and C. muytjensii (1%). No strains of C. dublinensis, C. universalis or C. condimenti were identified. Twenty-one out of seventy two C. sakazakii strains were in the clinically significant ST4 clonal complex, and were found in all three strain collections. These results confirm C. sakazakii ST4 is one of the predominant clonal complexes over the past 20 years in several parts of the world. Further understanding of the ecosystem and sources of the organism may be used for the development of improved intervention strategies in the dairy industry

International low back pain guidelines: A comparison of two research based models of care for the management of acute low back pain.

Evidence based guidelines for the management of acute low back pain (ALBP) have been formulated by numerous countries. There are discrepancies between guidelines regarding physiotherapy treatment. The aim of this study was to compare two research based models derived from international LBP guidelines. A single-blind randomised controlled trial was undertaken in a physiotherapy outpatients department. Subjects with ALBP were randomly allocated to an ‘assess/advise/treat’ group (n = 50) or an ‘assess/advise/wait’ group (n = 52). The primary outcome measure was the Roland and Morris Disability Questionnaire (RMDQ). Secondary outcome measures of pain (VAS, usual pain intensity) depressive symptoms (MZSRDS) somatic distress (MSPQ) anxiety (STAIS) quality of life (SF36) and general health (EuroQol) were also obtained. Outcomes were assessed at 6-weeks, 3-months and 6-months. At 6-weeks subjects in the assess/advise/treat group demonstrated less LBP related disability (p = 0.02) and depressive symptoms (p = 0.01), as well as better general health (p = 0.006, p = 0.05), vitality (p \u3c 0.001), social functioning (p = 0.004) and mental health (p = 0.002). At long-term assessment (3 and 6 months) subjects in the assess/advise/treat group were less distressed (p = 0.004), anxious (p = 0.01) and had fewer depressive symptoms (p = 0.001), as well as reporting better general health (p = 0.009, p = 0.05), emotional role (p = 0.03) and mental health (p = 0.04). Active physiotherapy produces better short-term outcomes than advice. Delaying treatment has no long-term consequences on pain or disability, but affects the development of psychosocial features

Romantic Partnerships and the Dispersion of Social Ties: A Network Analysis of Relationship Status on Facebook

A crucial task in the analysis of on-line social-networking systems is to identify important people --- those linked by strong social ties --- within an individual's network neighborhood. Here we investigate this question for a particular category of strong ties, those involving spouses or romantic partners. We organize our analysis around a basic question: given all the connections among a person's friends, can you recognize his or her romantic partner from the network structure alone? Using data from a large sample of Facebook users, we find that this task can be accomplished with high accuracy, but doing so requires the development of a new measure of tie strength that we term `dispersion' --- the extent to which two people's mutual friends are not themselves well-connected. The results offer methods for identifying types of structurally significant people in on-line applications, and suggest a potential expansion of existing theories of tie strength.Comment: Proc. 17th ACM Conference on Computer Supported Cooperative Work and Social Computing (CSCW), 201

The effectiveness of interventions targeting physical activity and/or sedentary behaviour in people with Multiple Sclerosis: a systematic review

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Optimising physiotherapy care for acute low back pain – identifying non-responders to treatment

Recent evidence suggests that positive effects of physiotherapy for acute low back pain patients can be achieved if treatment is delivered early enough. However it is clear that not all patients treated with physiotherapy are likely to report equally positive outcomes from their treatment. The identification of clinical characteristics of those patients who do less well will help refine models of care for acute low back pain. Aim: To identify non-responders to early active physiotherapy. Method: A secondary analysis was conducted on the data from a recently published randomised controlled trial of early physiotherapy for acute low back pain. All patients were randomised into two groups: immediate physiotherapy or advice and wait list and completed a series of physical, psychological and pain measures at baseline and again at six weeks. Multivariate statistical analysis was conducted to identify which patient baseline characteristics were associated with unsuccessful outcomes at the six week follow up. Control group comparisons permitted only those relationships associated with the intervention to be described. Results: Data analysis indicated that subgroups of patients who responded poorly to their physiotherapy treatment could be identified by a priori knowledge of their pain, mental health and physical function (p\u3c0.05). Conclusions: The results of the current analysis suggest that there are identifiable subgroups of patients who respond less well to physiotherapy treatment. Attention to these patient characteristics needs to be included in models of care for acute low back pain so that effects of therapy for all patients can be optimised

Human-Data Interaction: The Human Face of the Data-Driven Society

The increasing generation and collection of personal data has created a complex ecosystem, often collaborative but sometimes combative, around companies and individuals engaging in the use of these data. We propose that the interactions between these agents warrants a new topic of study: Human-Data Interaction (HDI). In this paper we discuss how HDI sits at the intersection of various disciplines, including computer science, statistics, sociology, psychology and behavioural economics. We expose the challenges that HDI raises, organised into three core themes of legibility, agency and negotiability, and we present the HDI agenda to open up a dialogue amongst interested parties in the personal and big data ecosystems