Fluctuation phenotyping based on daily fraction of exhaled nitric oxide values in asthmatic children

Fraction of exhaled nitric oxide (Feno), a marker of airway inflammation, has been proposed to be useful for asthma management, but conclusions are inconsistent. This might be due to the failure of mean statistics to characterize individual variability in Feno values, which is possibly a better indicator of asthma control than single measurements.

Fluctuation analysis of lung function as a predictor of long-term response to beta2-agonists

The response to beta(2)-agonists differs between asthmatics and has been linked to subsequent adverse events, even death. Possible determinants include beta(2)-adrenoceptor genotype at position 16, lung function and airway hyperresponsiveness. Fluctuation analysis provides a simple parameter alpha measuring the complex correlation properties of day-to-day peak expiratory flow. The present study investigated whether alpha predicts clinical response to beta(2)-agonist treatment, taking into account other conventional predictors. Analysis was performed on previously published twice-daily peak expiratory flow measurements in 66 asthmatic adults over three 6-month randomised order treatment periods: placebo, salbutamol and salmeterol. Multiple linear regression was used to determine the association between alpha during the placebo period and response to treatment (change in the number of days with symptoms), taking into account other predictors namely beta(2)-adrenoceptor genotype, lung function and its variability, and airway hyperresponsiveness. The current authors found that alpha measured during the placebo period considerably improved the prediction of response to salmeterol treatment, taking into account genotype, lung function or its variability, or airway hyperresponsiveness. The present study provides further evidence that response to beta(2)-agonists is related to the time correlation properties of lung function in asthma. The current authors conclude that fluctuation analysis of lung function offers a novel predictor to identify patients who may respond well or poorly to treatment.

Risk of severe asthma episodes predicted from fluctuation analysis of airway function

Asthma is an increasing health problem worldwide, but the long-term temporal pattern of clinical symptoms is not understood and predicting asthma episodes is not generally possible. We analyse the time series of peak expiratory flows, a standard measurement of airway function that has been assessed twice daily in a large asthmatic population during a long-term crossover clinical trial. Here we introduce an approach to predict the risk of worsening airflow obstruction by calculating the conditional probability that, given the current airway condition, a severe obstruction will occur within 30 days. We find that, compared with a placebo, a regular long-acting bronchodilator (salmeterol) that is widely used to improve asthma control decreases the risk of airway obstruction. Unexpectedly, however, a regular short-acting beta2-agonist bronchodilator (albuterol) increases this risk. Furthermore, we find that the time series of peak expiratory flows show long-range correlations that change significantly with disease severity, approaching a random process with increased variability in the most severe cases. Using a nonlinear stochastic model, we show that both the increased variability and the loss of correlations augment the risk of unstable airway function. The characterization of fluctuations in airway function provides a quantitative basis for objective risk prediction of asthma episodes and for evaluating the effectiveness of therapy.

The dementia cognitive fluctuation scale, a new psychometric test for clinicians to identify cognitive fluctuations in people with dementia.

OBJECTIVES Cognitive fluctuation (CF) is a common feature of dementia and a core diagnostic symptom for dementia with Lewy bodies (DLB). CF remains difficult to accurately and reliably detect clinically. This study aimed to develop a psychometric test that could be used by clinicians to facilitate the identification of CF and improve the recognition and diagnosis of DLB and Parkinson disease, and to improve differential diagnosis of other dementias. METHODS We compiled a 17-item psychometric test for identifying CF and applied this measure in a cross-sectional design. Participants were recruited from the North East of England, and assessments were made in individuals' homes. We recruited people with four subtypes of dementia and a healthy comparison group, and all subjects were administered this pilot scale together with other standard ratings. The psychometric properties of the scale were examined with exploratory factor analysis. We also examined the ability of individual items to identify CF to discriminate between dementia subtypes. The sensitivity and specificity of discriminating items were explored along with validity and reliability analyses. RESULTS Participants comprised 32 comparison subjects, 30 people with Alzheimer disease, 30 with vascular dementia, 29 with DLB, and 32 with dementia associated with Parkinson disease. Four items significantly discriminated between dementia groups and showed good levels of sensitivity (range: 78.6%-80.3%) and specificity (range: 73.9%-79.3%). The scale had very good levels of test-retest (Cronbach's alpha: 0.82) and interrater (0.81) reliabilities. The four items loaded onto three different factors. These items were: 1) marked differences in functioning during the daytime; 2) daytime somnolence; 3) daytime drowsiness; and 4) altered levels of consciousness during the day. CONCLUSIONS We identified four items that provide valid, sensitive, and specific questions for reliably identifying CF and distinguishing the Lewy body dementias from other major causes of dementia (Alzheimer disease and vascular dementia).