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

Variation of respiratory resistance suggests optimization of airway caliber

Physiologically optimized processes, such as respiration, walking, and cardiac function, usually show a range of variability about the optimized value. Airway resistance has, in the past, been noted as variable, and this variability has been connected to pulmonary disease (e.g., asthma). A hypothesis was presented many years ago that postulated airway resistance as an optimized parameter in healthy individuals, and we have noticed that respiratory measurements made with the airflow perturbation device (APD) tend to be variable in nature. It was posited that this variability indicates that respiratory resistance is optimized similarly to other physiological processes. Fifty subjects with a wide range of demographics volunteered to have 100 measurements made of their respiratory resistances. Resistances were separated into inhalation and exhalation phases. These were plotted and shown to have frequency distributions that were consistent with expectations for an optimized process. The frequency distributions were not quite symmetrical, being skewed slightly toward upper resistances. Comparison between subject data and data from a mechanical respiratory analog showed that subject resistance variation is overwhelmingly from the respiratory system and not from the APD.

[Prevention of COPD exacerbation: a fundamental challenge]

INTRODUCTION

Acute exacerbations of chronic obstructive pulmonary disease (AECOPD) are a cause of suffering for patients and a burden for healthcare systems and society. Their prevention represents individual and collective challenge. The present article is based on the work of a group of experts who met on 5th and 6th May 2011 and seeks to highlight the importance of AECOPD.

STATE OF THE ART

In the absence of easily quantifiable criteria, the definition of AECOPD varies in the literature, making identification difficult and affecting interpretation of study results. Exacerbations increase mortality and risk of cardiovascular disease. They also increase the risk of developing further exacerbations, accelerate the decline in lung function and contribute to reduction in muscle mass. By limiting physical activity and affecting mental state (anxiety, depression), AECOPD are disabling and impair quality of life. They increase work absenteeism and are responsible for about 60% of the global cost of COPD.

PERSPECTIVES

Earlier identification with simple criteria, possibly associated to patient phenotyping, could be helpful in preventing hospitalization.

CONCLUSIONS

Given their immediate and delayed impact, AECOPD should not be trivialized or neglected. Their prevention is a fundamental issue.

A method for analyzing temporal patterns of variability of a time series from Poincare plots

The Poincaré plot is a popular two-dimensional, time series analysis tool because of its intuitive display of dynamic system behavior. Poincaré plots have been used to visualize heart rate and respiratory pattern variabilities. However, conventional quantitative analysis relies primarily on statistical measurements of the cumulative distribution of points, making it difficult to interpret irregular or complex plots. Moreover, the plots are constructed to reflect highly correlated regions of the time series, reducing the amount of nonlinear information that is presented and thereby hiding potentially relevant features. We propose temporal Poincaré variability (TPV), a novel analysis methodology that uses standard techniques to quantify the temporal distribution of points and to detect nonlinear sources responsible for physiological variability. In addition, the analysis is applied across multiple time delays, yielding a richer insight into system dynamics than the traditional circle return plot. The method is applied to data sets of R-R intervals and to synthetic point process data extracted from the Lorenz time series. The results demonstrate that TPV complements the traditional analysis and can be applied more generally, including Poincaré plots with multiple clusters, and more consistently than the conventional measures and can address questions regarding potential structure underlying the variability of a data set.

Asthma outcomes: pulmonary physiology

BACKGROUND

Outcomes of pulmonary physiology have a central place in asthma clinical research.

OBJECTIVE

At the request of National Institutes of Health (NIH) institutes and other federal agencies, an expert group was convened to provide recommendations on the use of pulmonary function measures as asthma outcomes that should be assessed in a standardized fashion in future asthma clinical trials and studies to allow for cross-study comparisons.

METHODS

Our subcommittee conducted a comprehensive search of PubMed to identify studies that focused on the validation of various airway response tests used in asthma clinical research. The subcommittee classified the instruments as core (to be required in future studies), supplemental (to be used according to study aims and in a standardized fashion), or emerging (requiring validation and standardization). This work was discussed at an NIH-organized workshop in March 2010 and finalized in September 2011.

RESULTS

A list of pulmonary physiology outcomes that applies to both adults and children older than 6 years was created. These outcomes were then categorized into core, supplemental, and emerging. Spirometric outcomes (FEV(1), forced vital capacity, and FEV(1)/forced vital capacity ratio) are proposed as core outcomes for study population characterization, for observational studies, and for prospective clinical trials. Bronchodilator reversibility and prebronchodilator and postbronchodilator FEV(1) also are core outcomes for study population characterization and observational studies.

CONCLUSIONS

The subcommittee considers pulmonary physiology outcomes of central importance in asthma and proposes spirometric outcomes as core outcomes for all future NIH-initiated asthma clinical research.

Understanding the complexity of IgE-related phenotypes from childhood to young adulthood: a Mechanisms of the Development of Allergy (MeDALL) seminar

Mechanisms of the Development of Allergy (MeDALL), a Seventh Framework Program European Union project, aims to generate novel knowledge on the mechanisms of initiation of allergy. Precise phenotypes of IgE-mediated allergic diseases will be defined in MeDALL. As part of MeDALL, a scientific seminar was held on January 24, 2011, to review current knowledge on the IgE-related phenotypes and to explore how a multidisciplinary effort could result in a new integrative translational approach. This article provides a summary of the meeting. It develops challenges in IgE-related phenotypes and new clinical and epidemiologic approaches to the investigation of allergic phenotypes, including cluster analysis, scale-free models, candidate biomarkers, and IgE microarrays; the particular case of severe asthma was reviewed. Then novel approaches to the IgE-associated phenotypes are reviewed from the individual mechanisms to the systems, including epigenetics, human in vitro immunology, systems biology, and animal models. The last chapter deals with the understanding of the population-based IgE-associated phenotypes in children and adolescents, including age effect in terms of maturation, observed effects of early-life exposures and shift of focus from early life to pregnancy, gene-environment interactions, cohort effects, and time trends in patients with allergic diseases. This review helps to define phenotypes of allergic diseases in MeDALL.

Daily exhaled nitric oxide measurements and asthma exacerbations in children

BACKGROUND

Fractional exhaled Nitric Oxide (FeNO) is a biomarker for eosinophilic airway inflammation and can be measured at home on a daily basis. A short-term increase in FeNO may indicate a higher risk of future asthma exacerbations.

OBJECTIVE

To assess changes in FeNO before and after asthma exacerbations compared to a stable control period.

METHODS

A post hoc analysis was performed on daily FeNO measurements over 30 weeks in children with asthma (n = 77). Moderate exacerbations were defined by an increase in symptom scores and severe exacerbations by prescription of prednisone. Individual mean and maximum FeNO, the variability of FeNO assessed by the coefficient of variation (CV), and slopes of FeNO in time were all quantified in 3-week blocks. Cross-correlation of FeNO with symptoms and autocorrelation of FeNO were assessed in relation to exacerbations and examined as predictors for exacerbations compared to reference periods using logistic regression.

RESULTS

Fractional exhaled nitric oxide could be assessed in relation to 25 moderate and 12 severe exacerbations. The CV, slope, cross-correlation, and autocorrelation of daily FeNO increased before moderate exacerbations. Increases in slope were also randomly seen in 19% of 2-week blocks of children without exacerbations. At least 3-5 FeNO measurements in the 3 weeks before an exacerbation were needed to calculate a slope that could predict moderate exacerbations. No specific pattern of FeNO was seen before severe exacerbations.

CONCLUSION

Fractional exhaled nitric oxide monitoring revealed changes in FeNO prior to moderate exacerbations. Whether this can be used to prevent loss of asthma control should be further explored.

Oscillation mechanics of the respiratory system: applications to lung disease

Since its introduction in the 1950s, the forced oscillation technique (FOT) and the measurement of respiratory impedance have evolved into powerful tools for the assessment of various mechanical phenomena in the mammalian lung during health and disease. In this review, we highlight the most recent developments in instrumentation, signal processing, and modeling relevant to FOT measurements. We demonstrate how FOT provides unparalleled information on the mechanical status of the respiratory system compared to more widely used pulmonary function tests. The concept of mechanical impedance is reviewed, as well as the various measurement techniques used to acquire such data. Emphasis is placed on the analysis of lower, physiologic frequency ranges (typically less than 10 Hz) that are most sensitive to normal physical processes as well as pathologic structural alterations. Various inverse modeling approaches used to interpret alterations in impedance are also discussed, specifically in the context of three common respiratory diseases: asthma, chronic obstructive pulmonary disease, and acute lung injury. Finally, we speculate on the potential role for FOT in the clinical arena.

Modeling stochastic and spatial heterogeneity in a human airway tree to determine variation in respiratory system resistance

Asthma is a variable disease with changes in symptoms and airway function over many time scales. Airway resistance (Raw) is variable and thought to reflect changes in airway smooth muscle activity, but just how variation throughout the airway tree and the influence of gas distribution abnormalities affect Raw is unclear. We used a multibranch airway lung model to evaluate variation in airway diameter size, the role of coherent regional variation, and the role of gas distribution abnormalities on mean Raw (Raw) and variation in Raw as described by the SD (SDRaw). We modified an anatomically correct airway tree, provided by Merryn Tawhai (The University of Auckland, New Zealand), consisting of nearly 4,000 airways, to produce temporal and spatial heterogeneity. As expected, we found that increasing the diameter variation by twofold, with no change in the mean diameter, increased SDRaw more than fourfold. Perhaps surprisingly, Raw was proportional to SDRaw under several conditions-when either mean diameter was fixed, and its SD varied or when mean diameter varied, and SD was fixed. Increasing the size of a regional absence in gas distribution (ventilation defect) also led to a proportionate increase in both Raw and SDRaw. However, introducing regional dependence of connected airways strongly increased SDRaw by as much as sixfold, with little change in Raw. The model was able to predict previously reported Raw distributions and correlation of SDRaw on Raw in healthy and asthmatic subjects. The ratio of SDRaw to Raw depended most strongly on interairway coherent variation and only had a slight dependence on ventilation defect size. These findings may explain the linear correlation between variation and mean values of Raw but also suggest that regional alterations in gas distribution and local coordination in ventilation amplify any underlying variation in airway diameters throughout the airway tree.

Review and classification of variability analysis techniques with clinical applications

Analysis of patterns of variation of time-series, termed variability analysis, represents a rapidly evolving discipline with increasing applications in different fields of science. In medicine and in particular critical care, efforts have focussed on evaluating the clinical utility of variability. However, the growth and complexity of techniques applicable to this field have made interpretation and understanding of variability more challenging. Our objective is to provide an updated review of variability analysis techniques suitable for clinical applications. We review more than 70 variability techniques, providing for each technique a brief description of the underlying theory and assumptions, together with a summary of clinical applications. We propose a revised classification for the domains of variability techniques, which include statistical, geometric, energetic, informational, and invariant. We discuss the process of calculation, often necessitating a mathematical transform of the time-series. Our aims are to summarize a broad literature, promote a shared vocabulary that would improve the exchange of ideas, and the analyses of the results between different studies. We conclude with challenges for the evolving science of variability analysis.

Fluctuation analysis-based risk assessment for respiratory virus activity and air pollution associated asthma incidence

Asthma is a growing epidemic worldwide. Exacerbations of asthma have been associated with bacterial and viral respiratory tract infections and air pollution. We correlated the asthma admission rates with fluctuations in respiratory virus activity and traffic-related air pollution, namely particulate matter with an aerodynamic diameter ≤ 10 μm (PM₁₀), nitrogen dioxide (NO₂), carbon monoxide (CO), sulfur dioxide (SO₂), and ozone (O₃). A probabilistic risk assessment framework was developed based on a detrended fluctuation analysis to predict future respiratory virus and air pollutant associated asthma incidence. Results indicated a strong association between asthma admission rate and influenza (r=0.80, p<0.05) and SO₂ level (r=0.73, p<0.05) in Taiwan in the period 2001-2008. No significant correlation was found for asthma admission and PM₁₀, O₃, NO₂, and CO. The proposed fluctuation analysis provides a simple correlation exponent describing the complex interactions of respiratory viruses and air pollutants with asthma. This study revealed that there was a 95% probability of having exceeded 2987 asthma admissions per 100,000 population. It was unlikely (30% probability) that the asthma admission rate exceeded 3492 per 100,000 population. The probability of asthma admission risk can be limited to below 50% by keeping the correlation exponent of influenza to below 0.9. We concluded that fluctuation analysis based risk assessment provides a novel predictor of asthma incidence.

Systems medicine and integrated care to combat chronic noncommunicable diseases

We propose an innovative, integrated, cost-effective health system to combat major non-communicable diseases (NCDs), including cardiovascular, chronic respiratory, metabolic, rheumatologic and neurologic disorders and cancers, which together are the predominant health problem of the 21st century. This proposed holistic strategy involves comprehensive patient-centered integrated care and multi-scale, multi-modal and multi-level systems approaches to tackle NCDs as a common group of diseases. Rather than studying each disease individually, it will take into account their intertwined gene-environment, socio-economic interactions and co-morbidities that lead to individual-specific complex phenotypes. It will implement a road map for predictive, preventive, personalized and participatory (P4) medicine based on a robust and extensive knowledge management infrastructure that contains individual patient information. It will be supported by strategic partnerships involving all stakeholders, including general practitioners associated with patient-centered care. This systems medicine strategy, which will take a holistic approach to disease, is designed to allow the results to be used globally, taking into account the needs and specificities of local economies and health systems.

Scaling behavior of human locomotor activity amplitude: association with bipolar disorder

Scale invariance is a feature of complex biological systems, and abnormality of multi-scale behaviour may serve as an indicator of pathology. The hypothalamic suprachiasmatic nucleus (SCN) is a major node in central neural networks responsible for regulating multi-scale behaviour in measures of human locomotor activity. SCN also is implicated in the pathophysiology of bipolar disorder (BD) or manic-depressive illness, a severe, episodic disorder of mood, cognition and behaviour. Here, we investigated scaling behaviour in actigraphically recorded human motility data for potential indicators of BD, particularly its manic phase. A proposed index of scaling behaviour (Vulnerability Index [VI]) derived from such data distinguished between: [i] healthy subjects at high versus low risk of mood disorders; [ii] currently clinically stable BD patients versus matched controls; and [iii] among clinical states in BD patients.

Airflow pattern complexity and airway obstruction in asthma

The scientific and clinical value of a measure of complexity is potentially enormous because complexity appears to be lost in the presence of illness. The authors examined the effect of elevated airway obstruction on the complexity of the airflow (Q) pattern of asthmatic patients analyzing the airflow approximate entropy (ApEnQ). This study involved 11 healthy controls, 11 asthmatics with normal spirometric exams, and 40 asthmatics with mild (14), moderate (14), and severe (12) airway obstructions. A significant (P < 0.02) reduction in the ApEnQ was observed in the asthmatic patients. This reduction was significantly correlated with spirometric indexes of airway obstruction [FEV(1) (%): R = 0.31, P = 0.013] and the total respiratory impedance (R = -0.39; P < 0.002). These results are in close agreement with pathophysiological fundamentals and suggest that the airflow pattern becomes less complex in asthmatic patients, which may reduce the adaptability of the respiratory system to perform the exercise that is associated with daily life activities. This analysis was able to identify respiratory changes in patients with mild obstruction with an adequate accuracy (83%). Higher accuracies were obtained in patients with moderate and severe obstructions. The analysis of airflow pattern complexity by the ApEnQ was able to provide new information concerning the changes associated with asthma. In addition, this analysis was also able to contribute to the detection of the adverse effects of asthma. Because these measurements are easy to perform, such a technique may represent an alternative and/or a complement to other conventional exams to help the clinical evaluations of asthmatic patients.

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

BACKGROUND

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.

OBJECTIVE

We characterized fractal fluctuations in daily Feno values over time and the relationship between Feno values and symptom scores. We investigated whether these are associated with asthma severity, control, and exacerbation risk.

METHODS

Daily Feno values and symptom scores over 192 days in 41 atopic asthmatic children from the Childhood Asthma Respiratory Inflammatory Status Monitoring study were analyzed. Two methods of time-series analysis were used: detrended fluctuation analysis to quantify fractal patterns in fluctuations in daily Feno values (α value) and cross-correlation to quantify the strength of the relationship between daily Feno values and symptom scores. The associations of α values and cross-correlation with markers of asthma severity and control were assessed by means of regression analysis.

RESULTS

Daily fluctuations in Feno values exhibited fractal-type long-range correlations. Those subjects receiving higher doses of inhaled corticosteroids at study entry had a significantly lower α value, corresponding to more random fluctuations in Feno values in those with greater inhaled corticosteroid need. The cross-correlation between Feno values and symptom scores was significantly higher in those subjects who had exacerbations.

CONCLUSIONS

Fluctuation in Feno values and their cross-correlation to symptom scores contains information on asthma severity and control. Methods that quantify the complexity of asthma over time might assist in identifying asthmatic subjects with concordance between eosinophilic inflammation and symptoms and thus increased exacerbation risk.

Individual canine airway response variability to a deep inspiration

In healthy individuals, a DI can reverse (bronchodilation) or prevent (bronchoprotection) induced airway constriction. For individuals with asthma or COPD, these effects may be attenuated or absent. Previous work showed that the size and duration of a DI affected the subsequent response of the airways. Also, increased airway tone lead to increased airway size variability. The present study examined how a DI affected the temporal variability in individual airway baseline size and after methacholine challenge in dogs using High-Resolution Computed Tomography. Dogs were anesthetized and ventilated, and on 4 separate days, HRCT scans were acquired before and after a DI at baseline and during a continuous intravenous infusion of methacholine (Mch) at 3 dose rates (17, 67, and 200 μg/min). The Coefficient of Variation was used as an index of temporal variability in airway size.We found that at baseline and the lowest dose of Mch, variability decreased immediately and 5 minutes after the DI (P < 0.0001). In contrast, with higher doses of Mch, the DI caused a variable response. At a rate of 67 μg/min of Mch, the temporal variability increased after 5 minutes, while at a rate of 200 μg/min of Mch, the temporal variability increased immediately after the DI. Increased airway temporal variability has been shown to be associated with asthma. Although the mechanisms underlying this temporal variability are poorly understood, the beneficial effects of a DI to decrease airway temporal variability was eliminated when airway tone was increased. If this effect is absent in asthmatics, this may suggest a possible mechanism for the loss of bronchoprotective and bronchodilatory effects after a DI in asthma.

Temporal complexity in clinical manifestations of lung disease

In this review, we summarize results of recent research on the temporal variability of lung function, symptoms, and inflammatory biomarkers. Specifically, we demonstrate how fluctuation analysis borrowed from statistical physics can be used to gain insight into neurorespiratory control and complex chronic dynamic diseases such as asthma viewed as a system of interacting components (e.g., inflammatory, immunological, and mechanical). Fluctuation analysis tools are based on quantifying the distribution and the short- and long-term temporal history of tidal breathing and lung function parameters to assess neurorespiratory control and monitor chronic disease. The latter includes the assessment of severity and disease control, the impact of treatment and environmental triggers, the temporal characterization of disease phenotypes, and the individual risk of exacerbation. While in many cases specific mechanistic insight into the fluctuations still awaits further research, appropriate analyses of the fluctuations already impact on clinical science and practice.

Self-organized patterns of airway narrowing

The behavior of respiratory diseases such as asthma and COPD may involve complicated interactions among multiple factors. Theoretical and experimental data suggest that interdependence among the airways of the bronchial tree leads to the emergence of self-organized patterns of airway narrowing, ventilation defects, and other phenomena when a tipping point is passed. Additionally, evidence from several studies shows that the behavior of an isolated airway is different from an identical airway embedded in the bronchial tree so that experimental results of isolated elements such as airways, airway smooth muscle, or inflammatory pathways may not explain the whole organ behavior. However, there may be factors in the isolated elements that can dramatically change the complex system's behavior. More effective strategies for prevention or recovery from a disease, such as asthma, will depend on our progress in identifying and understanding the essential parts of the self-organized behavior that is involved.

Complex systems in pulmonary medicine: a systems biology approach to lung disease

The lung is a highly complex organ that can only be understood by integrating the many aspects of its structure and function into a comprehensive view. Such a view is provided by a systems biology approach, whereby the many layers of complexity, from the molecular genetic, to the cellular, to the tissue, to the whole organ, and finally to the whole body, are synthesized into a working model of understanding. The systems biology approach therefore relies on the expertise of many disciplines, including genomics, proteomics, metabolomics, physiomics, and, ultimately, clinical medicine. The overall structure and functioning of the lung cannot be predicted from studying any one of these systems in isolation, and so this approach highlights the importance of emergence as the fundamental feature of systems biology. In this paper, we will provide an overview of a systems biology approach to lung disease by briefly reviewing the advances made at many of these levels, with special emphasis on recent work done in the realm of pulmonary physiology and the analysis of clinical phenotypes.

Monitoring asthma control in children with allergies by soft computing of lung function and exhaled nitric oxide

BACKGROUND

Asthma control is emphasized by new guidelines but remains poor in many children. Evaluation of control relies on subjective patient recall and may be overestimated by health-care professionals. This study assessed the value of spirometry and fractional exhaled nitric oxide (FeNO) measurements, used alone or in combination, in models developed by a machine learning approach in the objective classification of asthma control according to Global Initiative for Asthma guidelines and tested the model in a second group of children with asthma.

METHODS

Fifty-three children with persistent atopic asthma underwent two to six evaluations of asthma control, including spirometry and FeNO. Soft computing evaluation was performed by means of artificial neural networks and principal component analysis. The model was then tested in a cross-sectional study in an additional 77 children with allergic asthma.

RESULTS

The machine learning method was not able to distinguish different levels of control using either spirometry or FeNO values alone. However, their use in combination modeled by soft computing was able to discriminate levels of asthma control. In particular, the model is able to recognize all children with uncontrolled asthma and correctly identify 99.0% of children with totally controlled asthma. In the cross-sectional study, the model prospectively identified correctly all the uncontrolled children and 79.6% of the controlled children.

CONCLUSIONS

Soft computing analysis of spirometry and FeNO allows objective categorization of asthma control status.

Respiratory muscle activity related to flow and lung volume in preterm infants compared with term infants

Infants with chronic lung disease (CLD) have a capacity to maintain functional lung volume despite alterations to their lung mechanics. We hypothesize that they achieve this by altering breathing patterns and dynamic elevation of lung volume, leading to differences in the relationship between respiratory muscle activity, flow and lung volume. Lung function and transcutaneous electromyography of the respiratory muscles (rEMG) were measured in 20 infants with CLD and in 39 healthy age-matched controls during quiet sleep. We compared coefficient of variations (CVs) of rEMG and the temporal relationship of rEMG variables, to flow and lung volume [functional residual capacity (FRC)] between these groups. The time between the start of inspiratory muscle activity and the resulting flow (tria)--in relation to respiratory cycle time--was significantly longer in infants with CLD. Although FRC had similar associations with tria and postinspiratory activity (corrected for respiratory cycle time), the CV of the diaphragmatic rEMG was lower in CLD infants (22.6 versus 31.0%, p = 0.030). The temporal relationship of rEMG to flow and FRC and the loss of adaptive variability provide additional information on coping mechanisms in infants with CLD. This technique could be used for noninvasive bedside monitoring of CLD.

Fluctuations and determinism of respiratory impedance in asthma and chronic obstructive pulmonary disease

Asthma and COPD are chronic respiratory diseases that fluctuate widely with regard to clinical symptoms and airway obstruction, complicating treatment and prediction of exacerbations. Time series of respiratory impedance obtained by the forced oscillation technique are a convenient tool to study the respiratory system with high temporal resolution. In previous studies it was suggested that power-law-like fluctuations exist also in the healthy lung and that respiratory system impedance variability differs in asthma. In this study we elucidate such differences in a population of well-characterized subjects with asthma (n = 13, GINA 1+2), COPD (n = 12, GOLD I+II), and controls (n = 10) from time series at single frequency (12 min, f = 8 Hz). Maximum likelihood estimation did not rule out power-law behavior, accepting the null hypothesis in 17/35 cases (P > 0.05) and with significant differences in exponents for COPD (P < 0.03). Detrended fluctuation analysis exhibited scaling exponents close to 0.5, indicating few correlations, with no differences between groups (P > 0.14). In a second approach, we considered asthma and COPD as dynamic diseases, corresponding to changes of unknown parameters in a deterministic system. The similarity in shape between the combined probability distributions of normalized resistance and reactance was quantified by Wasserstein distances and reliably distinguished the two diseases (cross-validated predictive accuracy 0.80; sensitivity 0.83, specificity 0.77 for COPD). Wasserstein distances between 3+3 dimensional phase space reconstructions resulted in marginally better classification (accuracy 0.84, sensitivity 0.83, specificity 0.85). These latter findings suggest that the dynamics of respiratory impedance contain valuable information for the diagnosis and monitoring of patients with asthma and COPD, whereas the value of the stochastic approach is not clear presently.

Aging effects on cardiac and respiratory dynamics in healthy subjects across sleep stages

STUDY OBJECTIVES

Respiratory and heart rate variability exhibit fractal scaling behavior on certain time scales. We studied the short-term and long-term correlation properties of heartbeat and breathing-interval data from disease-free subjects focusing on the age-dependent fractal organization. We also studied differences across sleep stages and night-time wake and investigated quasi-periodic variations associated with cardiac risk.

DESIGN

Full-night polysomnograms were recorded during 2 nights, including electrocardiogram and oronasal airflow.

SETTING

Data were collected in 7 laboratories in 5 European countries.

PARTICIPANTS

180 subjects without health complaints (85 males, 95 females) aged from 20 to 89 years.

INTERVENTIONS

None.

MEASUREMENTS AND RESULTS

Short-term correlations in heartbeat intervals measured by the detrended fluctuation analysis (DFA) exponent alpha1 show characteristic age dependence with a maximum around 50-60 years disregarding the dependence on sleep and wake states. Long-term correlations measured by alpha2 differ in NREM sleep when compared with REM sleep and wake, besides weak age dependence. Results for respiratory intervals are similar to those for alpha2 of heartbeat intervals. Deceleration capacity (DC) decreases with age; it is lower during REM and deep sleep (compared with light sleep and wake).

CONCLUSION

The age dependence of alpha1 should be considered when using this value for diagnostic purposes in post-infarction patients. Pronounced long-term correlations (larger alpha2) for heartbeat and respiration during REM sleep and wake indicate an enhanced control of higher brain regions, which is absent during NREM sleep. Reduced DC possibly indicates an increased cardiovascular risk with aging and during REM and deep sleep.

Assessing the exacerbations risk of influenza-associated chronic occupational asthma

The purpose of this article was to conduct a risk-based study based on a linkage of experimental human influenza infections and fluctuation analysis of airway function to assess whether influenza viral infection was risk factor for exacerbations of chronic occupational asthma. Here we provided a comprehensive probabilistic analysis aimed at quantifying influenza-associated exacerbations risk for occupational asthmatics, based on a combination of published distributions of viral shedding and symptoms scores and lung respiratory system properties characterized by long-range peak expiratory flow (PEF) dynamics. Using a coupled detrended fluctuation analysis-experimental human influenza approach, we estimated the conditional probability of moderate or severe lung airway obstruction and hence the exacerbations risk of influenza-associated occupational asthma in individuals. The long-range correlation exponent (alpha) was used as a predictor of future exacerbations risk of influenza-associated asthma. For our illustrative distribution of PEF fluctuations and influenza-induced asthma exacerbations risk relations, we found that the probability of exacerbations risk can be limited to below 50% by keeping alpha to below 0.53. This study also found that limiting wheeze scores to 0.56 yields a 75% probability of influenza-associated asthma exacerbations risk and a limit of 0.34 yields a 50% probability that may give a representative estimate of the distribution of chronic respiratory system properties. This study implicates that influenza viral infection is an important risk factor for exacerbations of chronic occupational asthma.

Airway smooth muscle modulation and airway hyper-responsiveness in asthma: new cellular and molecular paradigms

There is growing evidence indicating the existence of a causal relationship between abnormal airway smooth muscle (ASM) function and airway hyper-responsiveness, a poorly understood feature of asthma that can be defined as an excessive bronchospastic response. In recent years, there has been a veritable explosion of articles suggesting that ASM exposed to proasthmatic cytokines can elicit a hyper-responsive state to contractile G-protein-coupled receptor (GPCR) agonists. Aberrant airway responsiveness could result from abnormal calcium signaling, with changes occurring at various levels of GPCR-associated signal transduction. This review presents the latest observations describing novel mechanistic models that could explain the involvement of ASM in airway hyper-responsiveness. This review will discuss the role of ASM in beta(2)-agonist-mediated bronchial hyper-responsiveness and the clinical significance of cell-cell contact between ASM and mast cells recently described to be intimately infiltrated within the ASM tissues in asthmatic patients. The possibility that allergens could trigger airway hyper-responsiveness by directly acting on ASM via activation of immunoglobulin E receptors, FcepsilonRI and FCepsilonRII will also be discussed. These important findings further support the notion that targeting ASM could offer new treatment for many features of asthma, including airway hyper-responsiveness. Future therapeutic intervention includes: the prevention of ASM-inflammatory cell physical and/or functional interaction, the inhibition of Immunoglobulin E receptor-dependent signal transduction, and the abrogation of cytokine-dependent pathways that modulate receptor-associated calcium metabolism.

Fractals for physicians

There is increasing interest in the study of fractals in medicine. In this review, we provide an overview of fractals, of techniques available to describe fractals in physiological data, and we propose some reasons why a physician might benefit from an understanding of fractals and fractal analysis, with an emphasis on paediatric respiratory medicine where possible. Among these reasons are the ubiquity of fractal organisation in nature and in the body, and how changes in this organisation over the lifespan provide insight into development and senescence. Fractal properties have also been shown to be altered in disease and even to predict the risk of worsening of disease. Finally, implications of a fractal organisation include robustness to errors during development, ability to adapt to surroundings, and the restoration of such organisation as targets for intervention and treatment.

Modeling the dynamics of airway constriction: effects of agonist transport and binding

Recent advances have revealed that during exogenous airway challenge, airway diameters cannot be adequately predicted by their initial diameters. Furthermore, airway diameters can also vary greatly in time on scales shorter than a breath. To better understand these phenomena, we developed a multiscale model that allowed us to simulate aerosol challenge in the airways during ventilation. The model incorporates agonist-receptor binding kinetics to govern the temporal response of airway smooth muscle contraction on individual airway segments, which, together with airway wall mechanics, determines local airway caliber. Global agonist transport and deposition are coupled with pressure-driven flow, linking local airway constrictions with global flow dynamics. During the course of challenge, airway constriction alters the flow pattern, redistributing the agonist to less constricted regions. This results in a negative feedback that may be a protective property of the normal lung. As a consequence, repetitive challenge can cause spatial constriction patterns to evolve in time, resulting in a loss of predictability of airway diameters. Additionally, the model offers new insights into several phenomena including the intra- and interbreath dynamics of airway constriction throughout the tree structure.

Long-range correlations in rectal temperature fluctuations of healthy infants during maturation

Background

Control of breathing, heart rate, and body temperature are interdependent in infants, where instabilities in thermoregulation can contribute to apneas or even life-threatening events. Identifying abnormalities in thermoregulation is particularly important in the first 6 months of life, where autonomic regulation undergoes critical development. Fluctuations in body temperature have been shown to be sensitive to maturational stage as well as system failure in critically ill patients. We thus aimed to investigate the existence of fractal-like long-range correlations, indicative of temperature control, in night time rectal temperature (T_rec) patterns in maturing infants.

Methodology/Principal Findings

We measured T_rec fluctuations in infants every 4 weeks from 4 to 20 weeks of age and before and after immunization. Long-range correlations in the temperature series were quantified by the correlation exponent, α using detrended fluctuation analysis. The effects of maturation, room temperature, and immunization on the strength of correlation were investigated. We found that T_rec fluctuations exhibit fractal long-range correlations with a mean (SD) α of 1.51 (0.11), indicating that T_rec is regulated in a highly correlated and hence deterministic manner. A significant increase in α with age from 1.42 (0.07) at 4 weeks to 1.58 (0.04) at 20 weeks reflects a change in long-range correlation behavior with maturation towards a smoother and more deterministic temperature regulation, potentially due to the decrease in surface area to body weight ratio in the maturing infant. α was not associated with mean room temperature or influenced by immunization

Conclusions

This study shows that the quantification of long-range correlations using α derived from detrended fluctuation analysis is an observer-independent tool which can distinguish developmental stages of night time T_rec pattern in young infants, reflective of maturation of the autonomic system. Detrended fluctuation analysis may prove useful for characterizing thermoregulation in premature and other infants at risk for life-threatening events.

[Complexity in asthma: inflammation and scale-free networks]

Our understanding of asthma has traditionally been based on linear deterministic relationships of the type stimulus-bronchial hyperresponsiveness-obstruction-symptoms. This notion however neglects the fact that nonlinear relationships may be present. To better define the disease, some authors therefore suggest that we should think in terms of complex systems with a scale-free topology. The idea of multiple inflammatory hits proposed by the group of Pavord is in its broadest sense a further contribution to this line of thought. According to this theory, the coexistence of additional inflammatory stimuli, which may or may not be localized to the lungs, are responsible for deteriorating lung function. The effects of these stimuli may be additive or act in synergy with the underlying inflammation of asthma itself. In addition to the practical implications, this hypothesis serves as a reminder that the body is made up of interconnected parts and that the pathogenesis of asthma includes distinct elements linked together. If this hypothesis proves valid, future approaches should start to look for the hubs in this network that constitutes asthma, and attempt to integrate information from genomics, proteomics, and metabolomics.

Gene-environment interactions in asthma

Asthma is a complex disease, and its incidence is determined by an intricate interplay of genetic and environmental factors. The identification of novel genes for asthma suggests that many genes with small effects rather than few genes with strong effects contribute to the development of asthma. These genetic effects may in part differ with respect to a subject's environmental exposures, although some genes may also exert their effect independently of the environment. Whereas the geneticist uses highly advanced, rapid, comprehensive technologies to assess even subtle changes in the human genome, the researcher interested in environmental exposures is often confronted with crude information obtained from questionnaires or interviews. There is thus substantial need to develop better tools for individual exposure assessment in all relevant environmental fields. Despite these limitations, a number of important gene-environment interactions have been identified. These interactions point to the biology of environmental exposures as the involved genetic variation is suggestive of certain underlying mechanisms. Furthermore, the identification of subjects who are particularly susceptible to environmental hazards through genetic analyses helps to estimate better the strength of effect of environmental exposures. Finally, the analysis of gene-environment interactions may result in a reconciliation of seemingly contradictory findings from studies not taking environmental exposures into account.

Air pollution and asthma severity in adults

BACKGROUND/OBJECTIVES

There is evidence that exposure to air pollution affects asthma, but the effect of air pollution on asthma severity has not been addressed. The aim was to assess the relation between asthma severity during the past 12 months and home outdoor concentrations of air pollution.

METHODS

Asthma severity over the past 12 months was assessed in two complementary ways among 328 adult asthmatics from the French Epidemiological study on the Genetics and Environment of Asthma (EGEA) examined between 1991 and 1995. The four-class severity score integrated clinical events and type of treatment. The five-level asthma score is based only on the occurrence of symptoms. Nitrogen dioxide (NO(2)), sulphur dioxide (SO(2)) and ozone (O(3)) concentrations were assigned to each residence using two different methods. The first was based on the closest monitor data from 1991 to 1995. The second consisted of spatial models that used geostatistical interpolations and then assigned air pollutants to the geo-coded residences (1998).

RESULTS

Higher asthma severity score was significantly related to the 8-hour average of ozone during April-September (O(3)-8 h) and the number of days (O(3)-days) with 8-hour ozone averages above 110 microg.m(-3) (for a 36-day increase, equivalent to the interquartile range, in O(3)-days, odds ratio 2.22 (95% confidence interval 1.61 to 3.07) for one class difference in score). Adjustment for age, sex, smoking habits, occupational exposure, and educational level did not alter results. Asthma severity was unrelated to NO(2). Both exposure assessment methods and severity scores resulted in very similar findings. SO(2) correlated with severity but reached statistical significance only for the model-based assignment of exposure.

CONCLUSIONS

The observed associations between asthma severity and air pollution, in particular O(3), support the hypothesis that air pollution at levels far below current standards increases asthma severity.

Complexity of chronic asthma and chronic obstructive pulmonary disease: implications for risk assessment, and disease progression and control

Although assessment of asthma control is important to guide treatment, it is difficult since the temporal pattern and risk of exacerbations are often unpredictable. In this Review, we summarise the classic methods to assess control with unidimensional and multidimensional approaches. Next, we show how ideas from the science of complexity can explain the seemingly unpredictable nature of bronchial asthma and emphysema, with implications for chronic obstructive pulmonary disease. We show that fluctuation analysis, a method used in statistical physics, can be used to gain insight into asthma as a dynamic disease of the respiratory system, viewed as a set of interacting subsystems (eg, inflammatory, immunological, and mechanical). The basis of the fluctuation analysis methods is the quantification of the long-term temporal history of lung function parameters. We summarise how this analysis can be used to assess the risk of future asthma episodes, with implications for asthma severity and control both in children and adults.

Relative impact of respiratory muscle activity on tidal flow and end expiratory volume in healthy neonates

INTRODUCTION

It has been suggested that infants dynamically regulate their tidal flow and end-expiratory volume level. The interaction between muscle activity, flow and lung volume in spontaneously sleeping neonates is poorly studied, since it requires the assessment of transcutaneous electromyography of respiratory muscles (rEMG) in matched comparison to lung function measurements.

METHODS

After determining feasibility and repeatability of rEMG in 20 spontaneously sleeping healthy neonates, we measured the relative impact of intercostal and diaphragmatic EMG activity in direct comparison to the resulting tidal flow and FRC.

RESULTS

We found good feasibility, repeatability and correlation of timing indices between rEMG activity and flow. The rEMG amplitude was significantly dependent on the resistive load of the face mask. Diaphragm and intercostal muscle activity commenced prior to the onset of flow and remained active during the expiratory cycle. The relative contribution of intercostal and diaphragmatic activity to flow was variable and changed dynamically.

CONCLUSION

Using matched rEMG, air flow and lung volume measurements, we have found good feasibility and repeatability of intercostal and diaphragm rEMG measurements and provide the first quantitative measures of the temporal relationship between muscle activity and flow in spontaneously sleeping healthy neonates. Lung mechanical function is dynamically regulated and adapts on a breath to breath basis. So, non-invasive rEMG measurements alone or in combination with lung function might provide a more comprehensive picture of pulmonary mechanics in future studies. The data describing the timing of EMG and flow may be important for future studies of EMG triggered mechanical ventilation.

Temporal variability in the responses of individual canine airways to methacholine

Previous work showed that individual airway size, before any spasmogen, varied widely in the same animals on different days. The effect of this variable baseline size on the airway response to a subsequent challenge is unknown. The present study examined how the variability in individual airway baseline size in dogs was related to that after methacholine challenge on 4 different days using high-resolution computed tomography scans. Dogs were anesthetized and ventilated, and on 4 separate days randomly varying between 1 and 8 wk apart, baseline scans were acquired, followed by a continuous intravenous infusion of methacholine at three rates in increasing order (17, 67, and 200 microg/min). As the measure of variability, we used the coefficient of variation (CV) of the four airway luminal measurements of each airway at baseline and at each dose of methacholine. For most airways, there was wide variability both between and within dogs in the response to a given dose of methacholine (CV = 33-38%). Airways with any level of methacholine stimulation had greater variability than those at baseline. The airway variability was greatest at the lowest dose of methacholine administered but was elevated at all the doses. In conclusion, there was substantial day-to-day variability in baseline airway size. Most importantly, the same dose of methacholine to the same individual airway showed even greater variability than that at baseline. If we consider that increased heterogeneity may potentiate clinical symptoms, then airway response variability may play an important role in the manifestation of airway disease.

Predicting asthma control and exacerbations: chronic asthma as a complex dynamic model

PURPOSE OF REVIEW

Predicting asthma episodes is notoriously difficult but has potentially significant consequences for the individual, as well as for healthcare services. The purpose of this review is to describe recent insights into the prediction of acute asthma episodes in relation to classical clinical, functional or inflammatory variables, as well as present a new concept for evaluating asthma as a dynamically regulated homeokinetic system.

RECENT FINDINGS

Risk prediction for asthma episodes or relapse has been attempted using clinical scoring systems, considerations of environmental factors and lung function, as well as inflammatory and immunological markers in induced sputum or exhaled air, and these are summarized here. We have recently proposed that newer mathematical methods derived from statistical physics may be used to understand the complexity of asthma as a homeokinetic, dynamic system consisting of a network comprising multiple components, and also to assess the risk for future asthma episodes based on fluctuation analysis of long time series of lung function.

SUMMARY

Apart from the classical analysis of risk factor and functional parameters, this new approach may be used to assess asthma control and treatment effects in the individual as well as in future research trials.

Variability in asthma: symptom perception, care, and outcomes

Asthma remains a global respiratory health concern. Substantial variations in asthma outcomes persist in Canada despite the dissemination of national management guidelines. Many factors and their interactions presumably contribute to variations in outcomes, including asthma prevalence, severity, symptom recognition, self-management behaviour, access to care, and management. This article reviews the physiology of symptom perception in asthma, specifically the role of dynamic lung hyperinflation (DH) on the perception of the intensity and quality of dyspnea in asthma, and the link between blunted perception and life-threatening asthma. Additionally, the magnitude and correlates of regional variation in emergency department visit rates and hospitalizations for asthma in Ontario are reviewed.

The mechanisms, diagnosis, and management of severe asthma in adults

There has been a recent increase in the prevalence of asthma worldwide; however, the 5-10% of patients with severe disease account for a substantial proportion of the health costs. Although most asthma cases can be satisfactorily managed with a combination of anti-inflammatory drugs and bronchodilators, patients who remain symptomatic despite maximum combination treatment represent a heterogeneous group consisting of those who are under-treated or non-adherent with their prescribed medication. After excluding under-treatment and poor compliance, corticosteroid refractory asthma can be identified as a subphenotype characterised by a heightened neutrophilic airway inflammatory response in the presence or absence of eosinophils, with evidence of increased tissue injury and remodelling. Although a wide range of environmental factors such as allergens, smoking, air pollution, infection, hormones, and specific drugs can contribute to this phenotype, other features associated with changes in the airway inflammatory response should be taken into account. Aberrant communication between an injured airway epithelium and underlying mesenchyme contributes to disease chronicity and refractoriness to corticosteroids. The importance of identifying underlying causative factors and the recent introduction of novel therapeutic approaches, including the targeting of immunoglobulin E and tumour necrosis factor alpha with biological agents, emphasise the need for careful phenotyping of patients with severe disease to target improved management of the individual patient's needs.

Childhood asthma: breakthroughs and challenges

As we move forward, our goal is to control and eliminate asthma and other allergic disorders. This may come through broadly applied manipulation of environmental, dietary, and infectious risk factors, possibly during the perinatal period. Or we may learn to identify genetically susceptible children and to intervene with individualized genotype-specific treatment before the onset of disease. Maybe we'll learn how to block the mechanisms that give rise to chronic inflammation, or how to subdue Th2 activation. However, as the Swedish proverb says--Don't throw away the old bucket until you know whether the new one holds water. To continue using the old bucket, we have to fix the leaks. One approach to reducing asthma disparities is through traditional disease prevention stages. Primary prevention targets asthma incidence; secondary prevention mitigates established disease and involves disease detection, management, and control; and tertiary prevention is the reduction of complications caused by severe disease. Once causative factors at each level of disease prevention are understood, this knowledge can be translated into clinical practice and public health policy. We need reliable diagnostic criteria to provide correct treatment for infants and toddlers. This will require longitudinal cohort studies supported by assessment of pulmonary function and inflammatory markers. We must find ways to convince more physicians to embrace controller therapy for more severe disease, and to identify the patients with less severe disease who also require ongoing controller therapy. We need to close the gap between what we know and what we do in practice. We need to link basic research to healthcare delivery, and to gain acceptance and support from the intended recipients of new interventions. We need better strategies for improving adherence. We need accountability, foresight, and imagination.