Developing Fractional Exhaled Nitric Oxide Predicted and Upper Limit of Normal Values for a Disadvantaged Population

Fractional exhaled nitric oxide in a respiratory healthy general population through the lifespan

INTRODUCTION AND OBJECTIVES

The fractional exhaled fraction of nitric oxide (FeNO) is used in clinical practice for asthma diagnosis, phenotyping, and therapeutic management. Therefore, accurate thresholds are crucial. The normal FeNO values over lifespan in a respiratory healthy population and the factors related to them remain unclear.

MATERIALS AND METHODS

We determined FeNO levels in 2,251 respiratory healthy, non-atopic, and non-smoking participants from the Lung, hEart, sociAl, boDy (LEAD) cohort, a general population, observational cohort study of participants aged 6-82 years in Austria.

RESULTS

The median FeNO value in the total study population was 13.0 [interquartile range: 9.0, 20.0] ppb, increases with age, and, except in young participants (<18 years: 9.0 [7.0, 12.0], ≥18 years: 15.0 [11.0, 22.0]), it was significantly lower in females versus males. Multiple regression analyses showed that body height and blood eosinophil counts were associated with higher FeNO levels, both in children/adolescents and adults. In children/adolescents, FeNO values were positively associated with total IgE levels, FEV1/FVC ratio, and urban living. In adults, FeNO was positively associated with age and negatively associated with the presence of cardiovascular and ischaemic vascular disease.

CONCLUSIONS

We identified the normal FeNO ranges within a respiratory healthy population at different age ranges and associated factors. Collectively, they serve as a reference to frame FeNO values in clinical practice.

Detection of Breath Nitric Oxide at Ppb Level Based on Multiperiodic Spectral Reconstruction Neural Network

As breath nitric oxide (NO) is a biomarker of respiratory inflammation, reliable techniques for the online detection of ppb-level NO in exhaled breath are essential for the noninvasive diagnosis of respiratory inflammation. Here, we report a breath NO sensor based on the multiperiodic spectral reconstruction neural network. First, a spectral reconstruction method that transforms a spectrum from the wavelength domain to the intensity domain is proposed to remove noise and interference signals from the spectrum. Different from the traditional spectral processing method based on the wavelength domain, the method enhances the absorption characteristics of a target gas in the intensity domain, while discretizing noise and interference signals. This facilitates the extraction of the target gas spectrum. Then, a neural network is built to detect the concentration of breath NO. Laboratory-based results show that the sensor enables online detection of NO (1.63-846.68 ppb) with mean absolute error (MAE), mean absolute percentage error (MAPE), and detection accuracy of 0.31 ppb, 0.96% and 0.63%, respectively. Furthermore, an actual exhalation experiment proved that the sensor is capable of distinguishing breath NO of healthy people from that of simulated patients, which provides a reliable way to realize exhaled breath detection based on optical methods in the medical field.

Chronic respiratory disease in Indigenous peoples: a framework to address inequity and strengthen respiratory health and health care globally

Indigenous peoples around the world bear a disproportionate burden of chronic respiratory diseases, which are associated with increased risks of morbidity and mortality. Despite the imperative to address global inequity, research focused on strengthening respiratory health in Indigenous peoples is lacking, particularly in low-income and middle-income countries. Drivers of the increased rates and severity of chronic respiratory diseases in Indigenous peoples include a high prevalence of risk factors (eg, prematurity, low birthweight, poor nutrition, air pollution, high burden of infections, and poverty) and poor access to appropriate diagnosis and care, which might be linked to colonisation and historical and current systemic racism. Efforts to tackle this disproportionate burden of chronic respiratory diseases must include both global approaches to address contributing factors, including decolonisation of health care and research, and local approaches, co-designed with Indigenous people, to ensure the provision of culturally strengthened care with more equitable prioritisation of resources. Here, we review evidence on the burden of chronic respiratory diseases in Indigenous peoples globally, summarise factors that underlie health disparities between Indigenous and non-Indigenous people, propose a framework of approaches to improve the respiratory health of Indigenous peoples, and outline future directions for clinical care and research.

ERS technical standard: Global Lung Function Initiative reference values for exhaled nitric oxide fraction (F ENO50 )

BACKGROUND

Elevated exhaled nitric oxide fraction at a flow rate of 50 mL·s-1 (F ENO50 ) is an important indicator of T-helper 2-driven airway inflammation and may aid clinicians in the diagnosis and monitoring of asthma. This study aimed to derive Global Lung Function Initiative reference equations and the upper limit of normal for F ENO50 .

METHODS

Available individual F ENO50 data were collated and harmonised using consensus-derived variables and definitions. Data collected from individuals who met the harmonised definition of "healthy" were analysed using the generalised additive models of location, scale and shape (GAMLSS) technique.

RESULTS

Data were retrospectively collated from 34 782 individuals from 34 sites in 15 countries, of whom 8022 met the definition of healthy (19 sites, 11 countries). Overall, height, age and sex only explained 12% of the between-subject variability of F ENO50 (R2=0.12). F ENO device was neccessary as a predictor of F ENO50 , such that the healthy range of values and the upper limit of normal varied depending on which device was used. The range of F ENO50 values observed in healthy individuals was also very wide, and the heterogeneity was partially explained by the device used. When analysing a subset of data in which F ENO50 was measured using the same device and a stricter definition of health (n=1027), between-site heterogeneity remained.

CONCLUSION

Available F ENO50 data collected from different sites using different protocols and devices were too variable to develop a single all-age reference equation. Further standardisation of F ENO devices and measurement are required before population reference values might be derived.