Effect of weight and age on respiratory complexity in premature neonates

Multigenerational inheritance of breathing deficits following perinatal exposure to titanium dioxide nanoparticles in the offspring of mice

BACKGROUND

The utilization of titanium dioxide nanoparticles (TIO2NPs) has experienced a significant surge in recent decades, and these particles are now commonly found in various everyday consumer products. Due to their small size, TIO2NPs can penetrate biological barriers and elicit adverse interactions with biological tissues. Notably, exposure of pregnant females to TIO2NPs during the perinatal period has been shown to disrupt the growth of offspring. Furthermore, this exposure induces epigenetic modifications in the DNA of newborns, suggesting the possibility of multigenerational effects. Thus, perinatal exposure to TIO2NPs may induce immediate metabolic impairments in neonates, which could be transmitted to subsequent generations in the long term.

RESULTS

In this study, we utilized perinatal exposure of female mice to TIO2NPs through voluntary food intake and observed impaired metabolism in newborn male and female F1 offspring. The exposed newborn mice exhibited reduced body weight gain and a slower breathing rate compared to non-exposed animals. Additionally, a higher proportion of exposed F1 newborns experienced apneas. Similar observations were made when the exposure was limited to the postnatal period, highlighting lactation as a critical period for the adverse effects of TIO2NPs on postnatal metabolism. Importantly, the breathing deficits induced by TIO2NPs were transmitted from F1 females to the subsequent F2 generation. Moreover, re-exposure of adult F1 females to TIO2NPs exacerbated the breathing deficits in newborn F2 males.

CONCLUSIONS

Our findings demonstrate that perinatal exposure to TIO2NPs disrupts postnatal body weight gain and respiration in the offspring, and these deficits are transmissible to future generations.

Occupational exposure to airborne pollen and associated health risks among gardeners: a perception-based survey

Airborne pollen are considered a major trigger of respiratory diseases that causes morbidity and subsequently affects a person's quality of life (QOL). Outdoor workers, such as gardeners, florists, etc., are at greater risk of allergies due to continuous exposure to the high concentration of allergens. The current study aims to assess the associated health risks among gardeners due to occupational exposure to airborne pollen. A semi-structured questionnaire-based survey was conducted among gardeners (496) in Chandigarh, covering their socio-demographic status, occupational and environmental history, and respiratory and other health-related problems. Out of 496 respondents from 26 gardens in the city, 72.58% fall under the category of plantsman (mali), followed by 15.72% of grass cutters and 3.02% of headmali/supervisor. The majority of gardeners were males (95.76%) and a maximum number of respondents were in the age group of 29-38 years (27.41%). Among all, 4.2%, 3.6%, and 3.2% of respondents perceived the problem of shortness of breath and breathing problems. At the same time, 3.2% of respondents perceived that their breathing is never wholly satisfactory and surprisingly, all of them are plantsman (mali). Moreover, 18.9% of the respondents covered their faces with a cloth and only 0.5% of the respondents wore both spectacles and covered their faces with a cloth. Out of all respondents, 6.5% reported irritation in the eyes without wearing any personal protective device. The results show that a large proportion of gardeners are illiterate and unaware of occupational hazards and pollen allergies in their workplaces. Moreover, the regulatory authorities conduct no formal health awareness and training/education sessions to minimize the exposure and associate risk. The findings of the study will aid in a better understanding of the working conditions and health status of occupational gardeners, as well as the development of appropriate methods to improve their working conditions.

Temporal variations in the pattern of breathing: techniques, sources, and applications to translational sciences

The breathing process possesses a complex variability caused in part by the respiratory central pattern generator in the brainstem; however, it also arises from chemical and mechanical feedback control loops, network reorganization and network sharing with nonrespiratory motor acts, as well as inputs from cortical and subcortical systems. The notion that respiratory fluctuations contain hidden information has prompted scientists to decipher respiratory signals to better understand the fundamental mechanisms of respiratory pattern generation, interactions with emotion, influences on the cortical neuronal networks associated with cognition, and changes in variability in healthy and disease-carrying individuals. Respiration can be used to express and control emotion. Furthermore, respiration appears to organize brain-wide network oscillations via cross-frequency coupling, optimizing cognitive performance. With the aid of information theory-based techniques and machine learning, the hidden information can be translated into a form usable in clinical practice for diagnosis, emotion recognition, and mental conditioning.

Respiratory pattern complexity in newly-diagnosed asthmatic patients

BACKGROUND

The intensity of respiratory symptoms and expiratory airflow limitations in asthma fluctuate over time. Some studies have reported variable complexity of the respiratory patterns in asthmatic patients. Thus, we conducted a novel study to assess the correlation between asthma severity and breathing pattern dynamics in newly-diagnosed asthmatic patients.

METHODS

A total of 20 newly-diagnosed asthmatic patients (7 male, 13 female) and 20 healthy cases (11 male, 9 female) were included. The respiratory patterns of all participants and the asthma severity for asthmatic patients were measured using a spirometer (before and after a bronchodilator exposure) and airflow recorder, respectively. The peak-to-peak intervals and the amplitude of peaks were considered as the inter-breath interval (IBI) and lung volume (LV) series. The Detrended Fluctuation Analysis (DFA), Sample Entropy (SampEn), Multi-scale Entropy (MSE), short-term (SD1) and long-term (SD2) variability, and IBI and LV Cross-Sample Entropy of the respiratory pattern dynamics were calculated using MATLAB (Mathwork, USA).

RESULTS

Asthma patients showed notable increase in the average of sample entropy in both IBI and LV parameters (p = 0.025 and p = 0.018, respectively) and also decreased synchronization between IBI and LV (p = 0.042). The multi-scale sample entropy of both IBI and LV was significantly higher in asthmatic patients (p < 0.05). Furthermore, SD1 and SD2 were higher in the patients with asthma (p < 0.05). Significant correlations were detected between spirometric (forced expiratory flow (FEF) change, pre FEF, pre forced expiratory volume in one second (FEV1) / forced vital capacity (FVC), FVC change) and respiratory pattern (mean-IBI, mean-LV, mean-respiratory rate (RR), coefficient of variation (CV)-IBI, CV-LV, cross-sample entropy) parameters (p < 0.05). Furthermore, we identified a negative correlation between CV of IBI and asthma severity (r = -0.52, p = 0.021).

CONCLUSION

Here, we took a novel approach and observed increased irregularity (more complexity) in the breathing pattern of patients newly-diagnosed with asthma. Remarkable correlations were detected between breathing complexity markers and spirometric indices along with disease severity in asthmatic patients. Thus, our data suggests respiratory pattern indices could be utilized as an indicator of asthma and its severity. However, more clinical data are required to support this conclusion.

Predicting Apnoeic Events in Preterm Infants

Apnoea, a pause in respiration, is almost ubiquitous in preterm infants born before completing 30 weeks gestation. Apnoea often begets hypoxemia and/or bradycardia, and has the potential to result in adverse neurodevelopmental consequences. Our current inability to predict apnoeic events in preterm infants requires apnoea to first be detected by monitoring device/s in order to trigger an intervention by bedside (medical or nursing) staff. Such a reactive management approach is laborious, and makes the consequences of apnoeic events inevitable. Recent technological advances and improved signal processing have allowed the possibility of developing prediction models for apnoeic events in preterm infants. However, the development of such models has numerous challenges and is only starting to show potential. This paper identifies requisite components and current gaps in developing prediction models for apnoeic events, and reviews previous studies on predicting apnoeic events in preterm infants.

Entropy Analysis for the Evaluation of Respiratory Changes Due to Asbestos Exposure and Associated Smoking

Breathing is a complex rhythmic motor act, which is created by integrating different inputs to the respiratory centres. Analysing nonlinear fluctuations in breathing may provide clinically relevant information in patients with complex illnesses, such as asbestosis. We evaluated the effect of exposition to asbestos on the complexity of the respiratory system by investigating the respiratory impedance sample entropy (SampEnZrs) and recurrence period density entropy (RPDEnZrs). Similar analyses were performed by evaluating the airflow pattern sample entropy (SampEnV') and recurrence period density entropy (RPDEnV'). Groups of 34 controls and 34 asbestos-exposed patients were evaluated in the respiratory impedance entropy analysis, while groups of 34 controls and 30 asbestos-exposed patients were investigated in the analysis of airflow entropy. Asbestos exposition introduced a significant reduction of RPDEnV' in non-smoker patients (p < 0.0004), which suggests that the airflow pattern becomes less complex in these patients. Smoker patients also presented a reduction in RPDEnV' (p < 0.05). These finding are consistent with the reduction in respiratory system adaptability to daily life activities observed in these patients. It was observed a significant reduction in SampEnV' in smoker patients in comparison with non-smokers (p < 0.02). Diagnostic accuracy evaluations in the whole group of patients (including non-smokers and smokers) indicated that RPDEnV' might be useful in the diagnosis of respiratory abnormalities in asbestos-exposed patients, showing an accuracy of 72.0%. In specific groups of non-smokers, RPDEnV' also presented adequate accuracy (79.0%), while in smoker patients, SampEnV' and RPDEnV' presented adequate accuracy (70.7% and 70.2%, respectively). Taken together, these results suggest that entropy analysis may provide an early and sensitive functional indicator of interstitial asbestosis.

Trends in mechanical ventilation: are we ventilating our patients in the best possible way?

This review addresses how the combination of physiology, medicine and engineering principles contributed to the development and advancement of mechanical ventilation, emphasising the most urgent needs for improvement and the most promising directions of future development. Several aspects of mechanical ventilation are introduced, highlighting on one side the importance of interdisciplinary research for further development and, on the other, the importance of training physicians sufficiently on the technological aspects of modern devices to exploit properly the great complexity and potentials of this treatment.

EDUCATIONAL AIMS

To learn how mechanical ventilation developed in recent decades and to provide a better understanding of the actual technology and practice.To learn how and why interdisciplinary research and competences are necessary for providing the best ventilation treatment to patients.To understand which are the most relevant technical limitations in modern mechanical ventilators that can affect their performance in delivery of the treatment.To better understand and classify ventilation modes.To learn the classification, benefits, drawbacks and future perspectives of automatic ventilation tailoring algorithms.

Forbidden word entropy of cerebral oximetric values predicts postoperative neurocognitive decline in patients undergoing aortic arch surgery under deep hypothermic circulatory arrest

Purpose:

Up to 53% of cardiac surgery patients experience postoperative neurocognitive decline. Cerebral oximetry is designed to detect changes in cerebral tissue saturation and therefore may be useful to predict which patients are at risk of developing neurocognitive decline.

Methods:

This is a retrospective analysis of a prospective study originally designed to determine if treatment of cerebral oximetry desaturation is associated with improvement in postoperative cognitive dysfunction in patients undergoing aortic reconstruction under deep hypothermic circulatory arrest. Cognitive function was measured, preoperatively and 3 months postoperatively, with 15 neuropsychologic tests administered by a psychologist; the individual test scores were summed and normalized. Bilateral cerebral oximetry data were stored and analyzed using measures of entropy. Cognitive decline was defined as any decrease in the summed normalized score from baseline to 3 months.

Results:

Seven of 17 (41%) patients suffered cognitive decline. There was no association between baseline cerebral oximetry and postoperative cognitive dysfunction. Nor were changes in oximetry values associated with cognitive decline. However, cognitive decline was associated with loss of forbidden word entropy (FwEn) (correlation: Rho ρ = 0.51, P = 0.037 for left cerebral oximetry FwEn and ρ = 0.54, P = 0.025 for right cerebral oximetry FwEn).

Conclusion:

Postoperative cognitive decline was associated with loss of complexity of the time series as shown by a decrease in FwEn from beginning to end of the case. This suggests that regulation of cerebral oximetry is different between those who do and those who do not develop cognitive decline.

A retrospective analysis of the effect of blood transfusion on cerebral oximetry entropy and acute kidney injury

Purpose:

Acute anemia is associated with both cerebral dysfunction and acute kidney injury and is often treated with red blood cell transfusion. We sought to determine if blood transfusion changed the cerebral oximetry entropy, a measure of the complexity or irregularity of the oximetry values, and if this change was associated with subsequent acute kidney injury.

Methods:

This was a retrospective, case-control study of patients undergoing cardiac surgery with cardiopulmonary bypass at a tertiary care hospital, comparing those who received a red blood cell transfusion to those who did not. Acute kidney injury was defined as a perioperative increase in serum creatinine by ⩾26.4 μmol/L or by ⩾50% increase. Entropy was measured using approximate entropy, sample entropy, forbidden word entropy and basescale4 entropy in 500-point sets.

Results:

Forty-four transfused patients were matched to 88 randomly selected non-transfused patients. All measures of entropy had small changes in the transfused group, but increased in the non-transfused group (p<0.05, for all comparisons). Thirty-five of 132 patients (27%) suffered acute kidney injury. Based on preoperative factors, patients who suffered kidney injury were similar to those who did not, including baseline cerebral oximetry levels. After analysis with hierarchical logistic regression, the change in basescale4 entropy (odds ratio = 1.609, 95% confidence interval = 1.057–2.450, p = 0.027) and the interaction between basescale entropy and transfusion were significantly associated with subsequent development of acute kidney injury.

Conclusions:

The transfusion of red blood cells was associated with a smaller rise in entropy values compared to non-transfused patients, suggesting a change in the regulation of cerebral oxygenation, and these changes in cerebral oxygenation are also associated with acute kidney injury.

Sigh-induced changes of breathing pattern in preterm infants

Sighs are thought to play an important role in control of breathing. It is unclear how sighs are triggered, and whether preterm birth and lung disease influence breathing pattern prior to and after a sigh in infants. To assess whether frequency, morphology, size, and short-term variability in tidal volume (V_T) before, during, and after a sigh are influenced by gestational age at birth and lung disease (bronchopulmonary dysplasia, BPD) in former preterm infants and healthy term controls measured at equivalent postconceptional age (PCA). We performed tidal breathing measurements in 143 infants during quiet natural sleep at a mean (SD) PCA of 44.8 (1.3) weeks. A total of 233 sighs were analyzed using multilevel, multivariable regression. Sigh frequency in preterm infants increased with the degree of prematurity and severity of BPD, but was not different from that of term controls when normalized to respiratory rate. After a sigh, V_T decreased remarkably in all infants (paired t-test: P < 0.001). There was no major effect of prematurity or BPD on various indices of sigh morphology and changes in V_T prior to or after a sigh. Short-term variability in V_T modestly increased with maturity at birth and infants with BPD showed an earlier return to baseline variability in V_T following a sigh. In early infancy, sigh-induced changes in breathing pattern are moderately influenced by prematurity and BPD in preterm infants. The major determinants of sigh-related breathing pattern in these infants remain to be investigated, ideally using a longitudinal study design.

Factors affecting nasal intermittent positive pressure ventilation failure and impact on bronchopulmonary dysplasia in neonates

BACKGROUND

Nasal intermittent positive pressure ventilation (NIPPV) is becoming more important as a mode of ventilation in premature neonates predisposed to development of bronchopulmonary dysplasia (BPD). To the best of our knowledge, there have been no detailed studies characterizing neonates who fail NIPPV.

OBJECTIVE

To determine the differences between neonates who are successfully extubated to NIPPV and those who require re-intubation from NIPPV, and the impact of timing of NIPPV failure on BPD rates.

STUDY DESIGN

This was a retrospective cohort study in which we included infants with gestational age (GA) ⩽ 28 weeks and birth weight ⩽ 1000 g. χ²-test, analysis of variance and multivariate logistic regression models were used.

RESULTS

Two hundred and forty infants were studied; 180 failed NIPPV and of those, 33 (18%), 39 (22%) and 108 (60%) failed NIPPV within 0 to 6 h, ⩾ 6 to 24 h and ⩾ 24 h, respectively. Female sex and increased weight were protective against NIPPV failure (adjusted odds ratio (95% confidence interval): 0.28 (0.14 to 0.58), 0.04 (0.01 to 0.22)). Increased GA at extubation and female sex were both associated with increased time to failure (P=0.008, <0.001, respectively). Apnea was more likely the cause for failure ⩾ 24 h (P=0.015), whereas increased work of breathing/fraction of inspired oxygen requirements were more significant when NIPPV failure occurred earlier (P=0.001). Neonates who failed NIPPV within 24 h did not have any association with likelihood of developing BPD or severity of BPD, after adjusting for confounding variables.

CONCLUSION

Significant differences in neonatal characteristics may help identify which neonates are more likely to fail NIPPV, and their timing of failure.

Hyperglycemia, hypoglycemia, and glycemic complexity are associated with worse outcomes after surgery

PURPOSE

The purpose of this study was to determine if glycemic complexity, along with hypoglycemia and hyperglycemia, was associated with worse outcomes after cardiac surgery.

MATERIALS AND METHODS

We conducted a retrospective analysis of 970 patients who had insulin infusions designed to keep blood glucose levels between 80 and 110 mg/dL. Glycemic complexity was calculated using jackknifed approximate entropy. Logistic regression was used to adjust for confounders.

RESULTS

A total of 495 patients (51%) developed complications, and 32 patients (3.3%) died. Along with older age, comorbidities, and complicated surgeries, any hypoglycemia (glucose<71 mg/dL) and the number of glucose values greater than 140 mg/dL were independent predictors of complications. Increased risk of mortality, after adjusting for other risk factors, was associated with older age, longer perfusion time, receiving intraoperative transfusions, and greater jackknifed approximate entropy of the glucose time series.

CONCLUSION

We found that hypoglycemia (glucose<71 mg/dL) and hyperglycemia (glucose>140 mg/dL) were associated with increased risk of complications, whereas greater complexity of the glucose time series was associated with mortality.

Evaluating physiological dynamics via synchrosqueezing: prediction of ventilator weaning

Oscillatory phenomena abound in many types of signals. Identifying the individual oscillatory components that constitute an observed biological signal leads to profound understanding about the biological system. The instantaneous frequency (IF), the amplitude modulation (AM), and their temporal variability are widely used to describe these oscillatory phenomena. In addition, the shape of the oscillatory pattern, repeated in time for an oscillatory component, is also an important characteristic that can be parametrized appropriately. These parameters can be viewed as phenomenological surrogates for the hidden dynamics of the biological system. To estimate jointly the IF, AM, and shape, this paper applies a novel and robust time-frequency analysis tool, referred to as the synchrosqueezing transform (SST). The usefulness of the model and SST are shown directly in predicting the clinical outcome of ventilator weaning. Compared with traditional respiration parameters, the breath-to-breath variability has been reported to be a better predictor of the outcome of the weaning procedure. So far, however, all these indices normally require at least 20 min of data acquisition to ensure predictive power. Moreover, the robustness of these indices to the inevitable noise is rarely discussed. We find that based on the proposed model, SST and only 3 min of respiration data, the ROC area under curve of the prediction accuracy is 0.76. The high predictive power that is achieved in the weaning problem, despite a shorter evaluation period, and the stability to noise suggest that other similar kinds of signal may likewise benefit from the proposed model and SST.

Airflow pattern complexity during resting breathing in patients with COPD: effect of airway obstruction

We investigated the influence of airway obstruction in the complexity of the airflow pattern in COPD and its use as a marker of disease activity. The sample entropy (SampEnV') and the variability (SDV') of the airflow pattern were measured in a group of 88 subjects with various levels of airway obstruction. Airway obstruction resulted in a reduction in the SampEnV' (p<0.0001) that was significantly correlated with spirometric indices of airway obstruction (R=0.50, p<0.001). The early adverse effects in mild airway obstruction were detected by the SampEnV' with an accuracy of 84%. SDV' increased with airway obstruction (p<0.002). We conclude that (1) the airflow patterns in COPD exhibit reduced complexity compared with healthy subjects; (2) this reduction in complexity is proportional to airway obstruction; and (3) the evaluation of SampEnV' may provide novel respiratory biomarkers suitable to facilitate the diagnosis of respiratory abnormalities in COPD.

Complexity and emergent phenomena

Complex biological systems operate under non-equilibrium conditions and exhibit emergent properties associated with correlated spatial and temporal structures. These properties may be individually unpredictable, but tend to be governed by power-law probability distributions and/or correlation. This article reviews the concepts that are invoked in the treatment of complex systems through a wide range of respiratory-related examples. Following a brief historical overview, some of the tools to characterize structural variabilities and temporal fluctuations associated with complex systems are introduced. By invoking the concept of percolation, the notion of multiscale behavior and related modeling issues are discussed. Spatial complexity is then examined in the airway and parenchymal structures with implications for gas exchange followed by a short glimpse of complexity at the cellular and subcellular network levels. Variability and complexity in the time domain are then reviewed in relation to temporal fluctuations in airway function. Next, an attempt is given to link spatial and temporal complexities through examples of airway opening and lung tissue viscoelasticity. Specific examples of possible and more direct clinical implications are also offered through examples of optimal future treatment of fibrosis, exacerbation risk prediction in asthma, and a novel method in mechanical ventilation. Finally, the potential role of the science of complexity in the future of physiology, biology, and medicine is discussed.

Forecasting respiratory collapse: theory and practice for averting life-threatening infant apneas

Apnea of prematurity is a common disorder of respiratory control among preterm infants, with potentially serious adverse consequences on infant development. We review the capability for automatically assessing apnea risk and predicting apnea episodes from multimodal physiological measurements, and for using this knowledge to provide timely therapeutic intervention. We also review other, similar clinical domains of respiratory distress assessment and prediction in the hope of gaining useful insights. We propose an algorithmic framework for constructing discriminative feature vectors from physiological measurements, and for building robust and effective statistical models for apnea assessment and prediction.

Characterising non-linear dynamics in nocturnal breathing patterns of healthy infants using recurrence quantification analysis

Breathing dynamics vary between infant sleep states, and are likely to exhibit non-linear behaviour. This study applied the non-linear analytical tool recurrence quantification analysis (RQA) to 400 breath interval periods of REM and N-REM sleep, and then using an overlapping moving window. The RQA variables were different between sleep states, with REM radius 150% greater than N-REM radius, and REM laminarity 79% greater than N-REM laminarity. RQA allowed the observation of temporal variations in non-linear breathing dynamics across a night's sleep at 30s resolution, and provides a basis for quantifying changes in complex breathing dynamics with physiology and pathology.

The relationship between patterns of intermittent hypoxia and retinopathy of prematurity in preterm infants

BACKGROUND

We have previously shown an increased incidence of intermittent hypoxemia (IH) events in preterm infants with severe retinopathy of prematurity (ROP). Animal models suggest that patterns of IH events may play a role in ROP severity as well. We hypothesize that specific IH event patterns are associated with ROP in preterm infants.

METHODS

Variability in IH event duration, severity, and the time interval between IH events (≤80%, ≥10 s, and ≤3 min) along with the frequency spectrum of the oxygen saturation (SpO2) waveform were assessed.

RESULTS

Severe ROP was associated with (i) an increased mean and SD of the duration of IH event (P < 0.005), (ii) more variability (histogram entropy) of the time interval between IH events (P < 0.005), (iii) a higher IH nadir (P < 0.05), (iv) a time interval between IH events of 1-20 min (P < 0.05), and (v) increased spectral power in the range of 0.002-0.008 Hz (P < 0.05), corresponding to SpO2 waveform oscillations of 2-8 min in duration. Spectral differences were detected as early as 14 d of life.

CONCLUSION

Severe ROP was associated with more variable, longer, and less severe IH events. Identification of specific spectral components in the SpO2 waveform may assist in early identification of infants at risk for severe ROP.

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.

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.