Randomised controlled trial of a supervised exercise rehabilitation program for colorectal cancer survivors immediately after chemotherapy: study protocol

Background Colorectal cancer (CRC) diagnosis and the ensuing treatments can have a substantial impact on the physical and psychological health of survivors. As the number of CRC survivors increases, so too does the need to develop viable rehabilitation programs to help these survivors return to good health as quickly as possible. Exercise has the potential to address many of the adverse effects of CRC treatment; however, to date, the role of exercise in the rehabilitation of cancer patients immediately after the completion of treatment has received limited research attention. This paper presents the design of a randomised controlled trial which will evaluate the feasibility and efficacy of a 12-week supervised aerobic exercise program (ImPACT Program) on the physiological and psychological markers of rehabilitation, in addition to biomarkers of standard haematological outcomes and the IGF axis. Methods/Design Forty CRC patients will be recruited through oncology clinics and randomised to an exercise group or a usual care control group. Baseline assessment will take place within 4 weeks of the patient completing adjuvant chemotherapy treatment. The exercise program for patients in the intervention group will commence a week after the baseline assessment. The program consists of three supervised moderate-intensity aerobic exercise sessions per week for 12 weeks. All participants will have assessments at baseline (0 wks), mid-intervention (6 wks), post-intervention (12 wks) and at a 6-week follow-up (18 wks). Outcome measures include cardio-respiratory fitness, biomarkers associated with health and survival, and indices of fatigue and quality of life. Process measures are participants' acceptability of, adherence to, and compliance with the exercise program, in addition to the safety of the program. Discussion The results of this study will provide valuable insight into the role of supervised exercise in improving life after CRC. Additionally, process analyses will inform the feasibility of implementing the program in a population of CRC patients immediately after completing chemotherapy.

Rural and Urban Differentials in Primary Care Management of Chronic Heart Failure: New Data from the CASE Study

Objective: To determine whether primary care management of chronic heart failure (CHF) differed between rural and urban areas in Australia. Design: A cross-sectional survey stratified by Rural, Remote and Metropolitan Areas (RRMA) classification. The primary source of data was the Cardiac Awareness Survey and Evaluation (CASE) study. Setting: Secondary analysis of data obtained from 341 Australian general practitioners and 23 845 adults aged 60 years or more in 1998. Main outcome measures: CHF determined by criteria recommended by the World Health Organization, diagnostic practices, use of pharmacotherapy, and CHF-related hospital admissions in the 12 months before the study. Results: There was a significantly higher prevalence of CHF among general practice patients in large and small rural towns (16.1%) compared with capital city and metropolitan areas (12.4%) (P < 0.001). Echocardiography was used less often for diagnosis in rural towns compared with metropolitan areas (52.0% v 67.3%, P < 0.001). Rates of specialist referral were also significantly lower in rural towns than in metropolitan areas (59.1% v 69.6%, P < 0.001), as were prescribing rates of angiotensin-converting enzyme inhibitors (51.4% v 60.1%, P < 0.001). There was no geographical variation in prescribing rates of β-blockers (12.6% [rural] v 11.8% [metropolitan], P = 0.32). Overall, few survey participants received recommended “evidence-based practice” diagnosis and management for CHF (metropolitan, 4.6%; rural, 3.9%; and remote areas, 3.7%). Conclusions: This study found a higher prevalence of CHF, and significantly lower use of recommended diagnostic methods and pharmacological treatment among patients in rural areas.

Application of machine learning in fault diagnostics of mechanical systems

A diagnostic method based on Bayesian Networks (probabilistic graphical models) is presented. Unlike conventional diagnostic approaches, in this method instead of focusing on system residuals at one or a few operating points, diagnosis is done by analyzing system behavior patterns over a window of operation. It is shown how this approach can loosen the dependency of diagnostic methods on precise system modeling while maintaining the desired characteristics of fault detection and diagnosis (FDD) tools (fault isolation, robustness, adaptability, and scalability) at a satisfactory level. As an example, the method is applied to fault diagnosis in HVAC systems, an area with considerable modeling and sensor network constraints.

Prevalence of malnutrition in Parkinson's disease : a systematic review

Parkinson's disease (PD) patients may be at higher risk of malnutrition because of the symptoms associated with the disease and the side effects of the medication used to manage it. A decline in nutritional status is associated with many adverse outcomes related to health and quality of life. It is not clear, however, to what extent this population is currently affected by malnutrition. The objective of this review was to systematically assess the methodology and outcomes of studies reporting the prevalence of malnutrition in PD patients. Studies that attempted to classify participants with PD into nutritional risk and/or malnutrition categories using body mass index, weight change, anthropometric measures, and nutritional screening and assessment scores were included. The prevalence of malnutrition ranged from 0% to 24% in PD patients, while 3–60% of PD patients were reported to be at risk of malnutrition. There was a large degree of variation among studies in the methods chosen, the definition of malnutrition using those methods, and the detail in which the methodological protocols were reported. The true extent of malnutrition in the PD population has yet to be accurately quantified. It is important, however, to screen for malnutrition at the time of PD diagnosis.