Exercise and other non-pharmaceutical interventions for cancer-related fatigue in patients during or after cancer treatment: a systematic review incorporating an indirect-comparisons meta-analysis.

To assess the relative effects of different types of exercise and other non-pharmaceutical interventions on cancer-related fatigue (CRF) in patients during and after cancer treatment. Systematic review and indirect-comparisons meta-analysis. Articles were searched in PubMed, Cochrane CENTRAL and published meta-analyses. Randomised studies published up to January 2017 evaluating different types of exercise or other non-pharmaceutical interventions to reduce CRF in any cancer type during or after treatment. Risk of bias assessment with PEDro criteria and random effects Bayesian network meta-analysis. We included 245 studies. Comparing the treatments with usual care during cancer treatment, relaxation exercise was the highest ranked intervention with a standardisedmean difference (SMD) of -0.77 (95% Credible Interval (CrI) -1.22 to -0.31), while massage (-0.78; -1.55 to -0.01), cognitive-behavioural therapy combined with physical activity (combined CBT, -0.72; -1.34 to -0.09), combined aerobic and resistance training (-0.67; -1.01 to -0.34), resistance training (-0.53; -1.02 to -0.03), aerobic (-0.53; -0.80 to -0.26) and yoga (-0.51; -1.01 to 0.00) all had moderate-to-large SMDs. After cancer treatment, yoga showed the highest effect (-0.68; -0.93 to -0.43). Combined aerobic and resistance training (-0.50; -0.66 to -0.34), combined CBT (-0.45; -0.70 to -0.21), Tai-Chi (-0.45; -0.84 to -0.06), CBT (-0.42; -0.58 to -0.25), resistance training (-0.35; -0.62 to -0.08) and aerobic (-0.33; -0.51 to -0.16) showed all small-to-moderate SMDs. Patients can choose among different effective types of exercise and non-pharmaceutical interventions to reduce CRF

Reliability of the Multidimensional Pain Inventory and stability of the MPI classification system in chronic back pain

Contains fulltext : 109346.pdf (publisher's version ) (Open Access)ABSTRACT: BACKGROUND: This cross validation study examined the reliability of the Multidimensional Pain Inventory (MPI) and the stability of the Multidimensional Pain Inventory Classification System of the empirically derived subgroup classification obtained by cluster analysis in chronic musculoskeletal pain. Reliability of the German Multidimensional Pain Inventory was only examined once in the past in a small sample. Previous international studies mainly involving fibromyalgia patients showed that retest resulted in 33-38% of patients being assigned to a different Multidimensional Pain Inventory subgroup classification. METHODS: Participants were 204 persons with chronic musculoskeletal pain (82% chronic non-specific back pain). Subgroup classification was conducted by cluster analysis at 4 weeks before entry (=test) and at entry into the pain management program (=retest) using Multidimensional Pain Inventory scale scores. No therapeutic interventions in this period were conducted. Reliability was quantified by intraclass correlation coefficients (ICC) and stability by kappa coefficients (kappa). RESULTS: Reliability of the Multidimensional Pain Inventory scales was least with ICC = 0.57 for the scale life control and further ranged from ICC = 0.72 (negative mood) to 0.87 (solicitous responses) in the other scales. At retest, 82% of the patients in the Multidimensional Pain Inventory cluster interpersonally distressed (kappa = 0.69), 80% of the adaptive copers (kappa = 0.58), and 75% of the dysfunctional patients (kappa = 0.70) did not change classification. In total, 22% of the patients changed Multidimensional Pain Inventory cluster group, mainly into the adaptive copers subgroup. CONCLUSION: Test-retest reliability of the German Multidimensional Pain Inventory was moderate to good and comparable to other language versions. Multidimensional Pain Inventory subgroup classification is substantially stable in chronic back pain patients when compared to other diagnostic groups and other examiner-based subgroup Classification Systems. The MPI Classification System can be recommended for reliable and stable specification of subgroups in observational and interventional studies in patients with chronic musculoskeletal pain

Development and validation of two clinical prediction models to inform clinical decision-making for lumbar spinal fusion surgery for degenerative disorders and rehabilitation following surgery: protocol for a prospective observational study

INTRODUCTION: Potential predictors of poor outcome will be measured at baseline: (1) preoperatively to develop a clinical prediction model to predict which patients are likely to have favourable outcome following lumbar spinal fusion surgery (LSFS) and (2) postoperatively to predict which patients are likely to have favourable long-term outcomes (to inform rehabilitation). METHODS AND ANALYSIS: Prospective observational study with a defined episode inception of the point of surgery. Electronic data will be collected through the British Spine Registry and will include patient-reported outcome measures (eg, Fear-Avoidance Beliefs Questionnaire) and data items (eg, smoking status). Consecutive patients (≥18 years) undergoing LSFS for back and/or leg pain of degenerative cause will be recruited. EXCLUSION CRITERIA: LSFS for spinal fracture, inflammatory disease, malignancy, infection, deformity and revision surgery. 1000 participants will be recruited (n=600 prediction model development, n=400 internal validation derived model; planning 10 events per candidate prognostic factor). The outcome being predicted is an individual's absolute risk of poor outcome (disability and pain) at 6 weeks (objective 1) and 12 months postsurgery (objective 2). Disability and pain will be measured using the Oswestry Disability Index (ODI), and severity of pain in the previous week with a Numerical Rating Scale (NRS 0-10), respectively. Good outcome is defined as a change of 1.7 on the NRS for pain, and a change of 14.3 on the ODI. Both linear and logistic (to dichotomise outcome into low and high risk) multivariable regression models will be fitted and mean differences or ORs for each candidate predictive factor reported. Internal validation of the derived model will use a further set of British Spine Registry data. External validation will be geographical using two spinal registries in The Netherlands and Switzerland. ETHICS AND DISSEMINATION: Ethical approval (University of Birmingham ERN_17-0446A). Dissemination through peer-reviewed journals and conferences

Neural correlates of processing sentences and compound words in Chinese - Fig 2

<p><b>Significant activations elicited by the main conditions of sentence (A), word list (B) and character list (C) against baseline (fixations & blanks).</b> Voxel-wise: uncorrected <i>ps</i> = 0.001; Cluster-wise: <i>ps</i> = FDR_{<i>0</i>.<i>001</i>}.</p

Predictive validity of the Chelsea Critical Care Physical Assessment tool (CPAx) in critically ill, mechanically ventilated adults: a prospective clinimetric study

Purpose To investigate the predictive validity of the Chelsea Critical Care Physical Assessment tool (CPAx) at intensive care unit (ICU) discharge in critically ill adults for their 90-day outcomes. Materials and methods This prospective clinimetric study investigated four theory-driven, a-priori hypotheses in critically ill adults recruited within 72-144 h of mechanical ventilation. The primary hypothesis was a moderate accuracy (AUROC = 0.750) in predicting residence at home within 90 days. Secondary hypotheses included discrimination between hospital discharge destinations, correlation with subsequent health-related quality of life and length of ICU stay. Results We observed a good accuracy (AUROC = 0.778) of the CPAx at ICU discharge in predicting a return to home within 90 days. The CPAx score significantly increased between the discharge groups "undesirable" <= "rehabilitation" <= "home" (p < 0.001), but was not associated with 90-day health-related quality of life (physical: r = 0.261, mental: r = 0.193). Measured at baseline, CPAx scores correlated as expected with length of ICU stay (r = -0.443). Conclusions The CPAx at ICU discharge had a good predictive validity in projecting residence at home within 90 days and general discharge destinations. The CPAx might therefore have clinical value in prediction, though it does not seem useful to predict subsequent health-related quality of life