150 resultados para Streptococcus, Asthma, Immunisation
em BORIS: Bern Open Repository and Information System - Berna - Suiça
Resumo:
BACKGROUND One aspect of a multidimensional approach to understanding asthma as a complex dynamic disease is to study how lung function varies with time. Variability measures of lung function have been shown to predict response to beta(2)-agonist treatment. An investigation was conducted to determine whether mean, coefficient of variation (CV) or autocorrelation, a measure of short-term memory, of peak expiratory flow (PEF) could predict loss of asthma control following withdrawal of regular inhaled corticosteroid (ICS) treatment, using data from a previous study. METHODS 87 adult patients with mild to moderate asthma who had been taking ICS at a constant dose for at least 6 months were monitored for 2-4 weeks. ICS was then withdrawn and monitoring continued until loss of control occurred as per predefined criteria. Twice-daily PEF was recorded during monitoring. Associations between loss of control and mean, CV and autocorrelation of morning PEF within 2 weeks pre- and post-ICS withdrawal were assessed using Cox regression analysis. Predictive utility was assessed using receiver operator characteristics. RESULTS 53 out of 87 patients had sufficient PEF data over the required analysis period. The mean (389 vs 370 l/min, p<0.0001) and CV (4.5% vs 5.6%, p=0.007) but not autocorrelation of PEF changed significantly from prewithdrawal to postwithdrawal in subjects who subsequently lost control, and were unaltered in those who did not. These changes were related to time to loss of control. CV was the most consistent predictor, with similar sensitivity and sensitivity to exhaled nitric oxide. CONCLUSION A simple, easy to obtain variability measure of daily lung function such as the CV may predict loss of asthma control within the first 2 weeks of ICS withdrawal.
Resumo:
It has been suggested that there are several distinct phenotypes of childhood asthma or childhood wheezing. Here, we review the research relating to these phenotypes, with a focus on the methods used to define and validate them. Childhood wheezing disorders manifest themselves in a range of observable (phenotypic) features such as lung function, bronchial responsiveness, atopy and a highly variable time course (prognosis). The underlying causes are not sufficiently understood to define disease entities based on aetiology. Nevertheless, there is a need for a classification that would (i) facilitate research into aetiology and pathophysiology, (ii) allow targeted treatment and preventive measures and (iii) improve the prediction of long-term outcome. Classical attempts to define phenotypes have been one-dimensional, relying on few or single features such as triggers (exclusive viral wheeze vs. multiple trigger wheeze) or time course (early transient wheeze, persistent and late onset wheeze). These definitions are simple but essentially subjective. Recently, a multi-dimensional approach has been adopted. This approach is based on a wide range of features and relies on multivariate methods such as cluster or latent class analysis. Phenotypes identified in this manner are more complex but arguably more objective. Although phenotypes have an undisputed standing in current research on childhood asthma and wheezing, there is confusion about the meaning of the term 'phenotype' causing much circular debate. If phenotypes are meant to represent 'real' underlying disease entities rather than superficial features, there is a need for validation and harmonization of definitions. The multi-dimensional approach allows validation by replication across different populations and may contribute to a more reliable classification of childhood wheezing disorders and to improved precision of research relying on phenotype recognition, particularly in genetics. Ultimately, the underlying pathophysiology and aetiology will need to be understood to properly characterize the diseases causing recurrent wheeze in children.
Resumo:
The evidence for an effect of breastfeeding on lung function is conflicting, in particular whether the effect is modified by maternal asthma.
Resumo:
Background: Several cross-sectional studies during the past 10 years have observed an increased risk of allergic outcomes for children living in damp or mouldy environments. Objective: The objective of this study was to investigate whether reported mould or dampness exposure in early life is associated with the development of allergic disorders in children from eight European birth cohorts. Methods: We analysed data from 31 742 children from eight ongoing European birth cohorts. Exposure to mould and allergic health outcomes were assessed by parental questionnaires at different time points. Meta-analyses with fixed- and random-effect models were applied. The number of the studies included in each analysis varied based on the outcome data available for each cohort. Results: Exposure to visible mould and/or dampness during first 2 years of life was associated with an increased risk of developing asthma: there was a significant association with early asthma symptoms in meta-analyses of four cohorts [0–2 years: adjusted odds ratios (aOR), 1.39 (95%CI, 1.05–1.84)] and with asthma later in childhood in six cohorts [6–8 years: aOR, 1.09(95%CI, 0.90–1.32) and 3–10 years: aOR, 1.10 (95%CI, 0.90–1.34)]. A statistically significant association was observed in six cohorts with symptoms of allergic rhinitis at school age [6–8 years: aOR, 1.12 (1.02–1.23)] and at any time point between 3 and 10 years [aOR, 1.18 (1.09–1.28)]. Conclusion: These findings suggest that a mouldy home environment in early life is associated with an increased risk of asthma particularly in young children and allergic rhinitis symptoms in school-age children.
Resumo:
Background The loose and stringent Asthma Predictive Indices (API), developed in Tucson, are popular rules to predict asthma in preschool children. To be clinically useful, they require validation in different settings. Objective To assess the predictive performance of the API in an independent population and compare it with simpler rules based only on preschool wheeze. Methods We studied 1954 children of the population-based Leicester Respiratory Cohort, followed up from age 1 to 10 years. The API and frequency of wheeze were assessed at age 3 years, and we determined their association with asthma at ages 7 and 10 years by using logistic regression. We computed test characteristics and measures of predictive performance to validate the API and compare it with simpler rules. Results The ability of the API to predict asthma in Leicester was comparable to Tucson: for the loose API, odds ratios for asthma at age 7 years were 5.2 in Leicester (5.5 in Tucson), and positive predictive values were 26% (26%). For the stringent API, these values were 8.2 (9.8) and 40% (48%). For the simpler rule early wheeze, corresponding values were 5.4 and 21%; for early frequent wheeze, 6.7 and 36%. The discriminative ability of all prediction rules was moderate (c statistic ≤ 0.7) and overall predictive performance low (scaled Brier score < 20%). Conclusion Predictive performance of the API in Leicester, although comparable to the original study, was modest and similar to prediction based only on preschool wheeze. This highlights the need for better prediction rules.
Resumo:
Two distinct, stable inflammatory phenotypes have been described in adults with asthma: eosinophilic and non-eosinophilic. Treatment strategies based on these phenotypes have been successful. This study evaluated sputum cytology in children with asthma to classify sputum inflammatory phenotypes and to assess their stability over time.
Resumo:
Previous studies in adults with asthma incorporating the control of sputum eosinophils into management strategies have shown significant reductions in exacerbations. A study was undertaken to investigate whether this strategy would be successful in children with severe asthma.
Resumo:
Lung function is a major criterion used to assess asthma control. Fluctuation analyses can account for lung function history over time, and may provide an additional dimension to characterise control. The relationships between mean and fluctuations in lung function with asthma control, exacerbation and quality of life were studied in two independent data sets.
Resumo:
Determination of future risk of exacerbations is a key issue in the management of asthma. We previously developed a method to calculate conditional probabilities (π) of future decreases in lung function by using the daily fluctuations in peak expiratory flow (PEF).