Assessment Method for the Sinterability of Matrices in Ceramic Composites

To date, it remains unknown which patients report a clinically-relevant improvement in fatigue following pulmonary rehabilitation (PR). The purpose of this study was to identify and characterize these responders. Demographics, lung function, anxiety (anxiety subscale of the 90-item symptom checklist (SCL-90-A)), depression (Beck depression inventory for primary care (BDI-PC)), exercise tolerance (six-minute walking distance test (6MWD)), and health status (Nijmegen clinical screening instrument (NCSI)) were assessed before and after a 12-week PR programme. Fatigue was assessed using the checklist individual strength (CIS)-Fatigue. Patients with a decline ≥ 10 points (minimally clinically important difference, MCID) on the CIS-Fatigue were defined as responders. Chronic obstructive pulmonary disease (COPD) patients (n = 446, 61 ± 9 years, 53% male, forced expiratory volume in 1 s (FEV1) 43% ± 18% predicted, 75% severe fatigue) were included. Mean change in fatigue after PR was 10 ± 12 points (p 0.01). Responders on fatigue reported a greater improvement in anxiety, depression, 6MWD, dyspnoea (all p-values < 0.001), and most health status parameters. PR reduces fatigue in COPD. Responders on fatigue have worse fatigue and HRQoL scores at baseline, and are also likely to be responders on other outcomes of PR

The prevalence and related factors of fatigue in patients with COPD:a systematic review

Background Fatigue is a distressing symptom in patients with COPD. Little is known about the factors that contribute to fatigue in COPD. This review summarises existing knowledge on the prevalence of fatigue, factors related to fatigue and the instruments most commonly used to assess fatigue in COPD. Methods Pubmed, PsycINFO, EMBASE, Cochrane and CINAHL databases were searched for studies from inception up to 7 January 2020 using the medical subject headings “COPD” and “Fatigue”. Studies were reviewed in accordance with PRISMA guidelines. Results 196 studies were evaluated. The prevalence of fatigue ranged from 17–95%. Age (r=−0.23 to r=0.27), sex (r=0.11), marital status (r=−0.096), dyspnoea (r=0.13 to r=0.78), forced expiatory volume in 1 s % predicted (r=−0.55 to r=−0.076), number of exacerbations (r=0.27 to r=0.38), number of comorbidities (r=0.10), number of medications (r=0.35), anxiety (r=0.36 to r=0.61), depression (r=0.41 to r=0.66), muscle strength (r=−0.78 to r=−0.45), functional capacity (r=−0.77 to r=−0.14) and quality of life (r=0.48 to r=0.77) showed significant associations with fatigue. Conclusions Fatigue is a prevalent symptom in patients with COPD. Multiple physical and psychological factors seem to be associated with fatigue. Future studies are needed to evaluate these underlying factors in integral analyses in samples of patients with COPD

Fatigue is Highly Prevalent in Patients with Asthma and Contributes to the Burden of Disease

The 2018 update of the Global Strategy for Asthma Management and Prevention does not mention fatigue-related symptoms. Nevertheless, patients with asthma frequently report tiredness, lack of energy, and daytime sleepiness. Quantitative research regarding the prevalence of fatigue in asthmatic patients is lacking. This retrospective cross-sectional study of outpatients with asthma upon referral to a chest physician assessed fatigue (Checklist Individual Strength-Fatigue (CIS-Fatigue)), lung function (spirometry), asthma control (Asthma Control Questionnaire (ACQ)), dyspnea (Medical Research Council (MRC) scale), exercise capacity (six-minute walk test (6MWT)), and asthma-related Quality-of-Life (QoL), Asthma Quality of Life Questionnaire (AQLQ) during a comprehensive health-status assessment. In total, 733 asthmatic patients were eligible and analyzed (47.4 &#177; 16.3 years, 41.1% male). Severe fatigue (CIS-Fatigue &#8805; 36 points) was detected in 62.6% of patients. Fatigue was not related to airflow limitation (FEV1, &#961; = &#8722;0.083); was related moderately to ACQ (&#961; = 0.455), AQLQ (&#961; = &#8722;0.554), and MRC (&#961; = 0.435; all p-values &lt; 0.001); and was related weakly to 6MWT (&#961; = &#8722;0.243, p &lt; 0.001). In stepwise multiple regression analysis, 28.9% of variance in fatigue was explained by ACQ (21.0%), MRC (6.5%), and age (1.4%). As for AQLQ, 42.2% of variance was explained by fatigue (29.8%), MRC (8.6%), exacerbation rate (2.6%), and age (1.2%). Severe fatigue is highly prevalent in asthmatic patients; it is an important determinant of disease-specific QoL and a crucial yet ignored patient-related outcome in patients with asthma

Beta-alanine supplementation in patients with COPD receiving non-linear periodised exercise training or neuromuscular electrical stimulation: protocol of two randomised, double-blind, placebo-controlled trials

International audienceIntroduction: Exercise intolerance is common in patients with chronic obstructive pulmonary disease (COPD) and, although multifactorial, it is largely caused by lower-limb muscle dysfunction. Research has shown that patients with severe to very severe COPD have significantly lower levels of muscle carnosine, which acts as a pH buffer and antioxidant. Beta-alanine (BA) supplementation has been shown to consistently elevate muscle carnosine in a variety of populations and may therefore improve exercise tolerance and lower-limb muscle function. The primary objective of the current studies is to assess the beneficial effects of BA supplementation in enhancing exercise tolerance on top of two types of exercise training (non-linear periodised exercise (NLPE) training or neuromuscular electrical stimulation (NMES)) in patients with COPD.Methods and analysis: Two randomised, double-blind, placebo-controlled trials have been designed. Patients will routinely receive either NLPE (BASE-TRAIN trial) or NMES (BASE-ELECTRIC trial) as part of standard exercise-based care during their 8-to-10 week pulmonary rehabilitation (PR) programme. A total of 222 patients with COPD (2×77 = 154 patients in the BASE-TRAIN trial and 2×34 = 68 patients in the BASE-ELECTRIC trial) will be recruited from two specialised PR centres in The Netherlands. For study purposes, patients will receive 3.2 g of oral BA supplementation or placebo per day. Exercise tolerance is the primary outcome, which will be assessed using the endurance shuttle walk test (BASE-TRAIN) or the constant work rate cycle test (BASE-ELECTRIC). Furthermore, quadriceps muscle strength and endurance, cognitive function, carnosine levels (in muscle), BA levels (in blood and muscle), markers of oxidative stress and inflammation (in blood, muscles and lungs), physical activity and quality of life will be measured.Ethics and dissemination: Both trials were approved by CMO Regio Arnhem-Nijmegen, The Netherlands (NL70781.091.19. and NL68757.091.19).Trial registration number: NTR8427 (BASE-TRAIN) and NTR8419 (BASE-ELECTRIC)

Classifying the diagnosis of study participants in clinical trials: a structured and efficient approach

Background: A challenge in imaging research is a diagnostic classification of study participants. We hypothesised that a structured approach would be efficient and that classification by medical students, residents, and an expert panel whenever necessary would be as valid as classification of all patients by experts. Methods: OPTIMACT is a randomised trial designed to evaluate the effectiveness of replacing chest x-ray for ultra-low-dose chest computed tomography (CT) at the emergency department. We developed a handbook with diagnostic guidelines and randomly selected 240 cases from 2,418 participants enrolled in OPTIMACT. Each case was independently classified by two medical students and, if they disagreed, by the students and a resident in a consensus meeting. Cases without consensus and cases classified as complex were assessed by a panel of medical specialists. To evaluate the validity, 60 randomly selected cases not referred to the panel by the students and the residents were reassessed by the specialists. Results: Overall, the students and, if necessary, residents were able to assign a diagnosis in 183 of the 240 cases (76% concordance; 95% confidence interval [CI] 71–82%). We observed agreement between students and residents versus medical specialists in 50/60 cases (83% concordance; 95% CI 74–93%). Conclusions: A structured approach in which study participants are assigned diagnostic labels by assessors with increasing levels of medical experience was an efficient and valid classification method, limiting the workload for medical specialists. We presented a viable option for classifying study participants in large-scale imaging trials (Netherlands National Trial Register number NTR6163)