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Original Research: Asthma |

Increased Day-to-Day Variability of Forced Oscillatory Resistance in Poorly Controlled or Persistent Pediatric AsthmaRespiratory System Impedance Variability in Asthma FREE TO VIEW

Paul D. Robinson, MBChB, PhD; Nathan J. Brown, PhD; Martin Turner, PhD; Peter Van Asperen, MD; Hiran Selvadurai, PhD; Gregory G. King, MBChB, PhD
Author and Funding Information

From the Woolcock Institute of Medical Research (Drs Robinson, Brown, Turner, and King), Sydney; The University of Sydney (Drs Robinson, Brown, Turner, Van Asperen, Selvadurai, and King), Sydney; the Department of Respiratory Medicine (Drs Robinson, Van Asperen, and Selvadurai), The Children’s Hospital at Westmead, Westmead; the Cooperative Research Centre for Asthma and Airways (Drs Robinson, Brown, Turner, and King), Sydney; and the Department of Respiratory Medicine (Dr King), Royal North Shore Hospital, St. Leonards, NSW, Australia.

CORRESPONDENCE TO: Paul D. Robinson, MBChB, PhD, Department of Respiratory Medicine, The Children’s Hospital at Westmead, Locked Bag 4001, Westmead, NSW 2145, Australia; e-mail: dr.pdrobinson@gmail.com


FUNDING/SUPPORT: This study was supported by a National Health and Medical Research Council (NHMRC) Postgraduate Research Scholarship, an NHMRC Practitioner Fellowship, the Cooperative Research Centre for Asthma and Airways (Project 2.1), the Australian Research Council (UPTECH [Ultrafine Particles from Traffic Emissions and Children’s Health] study), and an NHMRC project grant [512387].

Reproduction of this article is prohibited without written permission from the American College of Chest Physicians. See online for more details.


Chest. 2014;146(4):974-981. doi:10.1378/chest.14-0288
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BACKGROUND:  Pediatric asthma lacks sensitive objective measures for asthma monitoring. The forced oscillation technique (FOT) offers strong feasibility across the pediatric age range, but relationships between FOT parameter day-to-day variability and pediatric asthma severity and control are unknown.

METHODS:  Day-to-day variability in FOT respiratory system resistance (Rrs) and respiratory system reactance (Xrs) compared with peak expiratory flow (PEF) were defined in 22 children with asthma (mean ± SD age, 10.4 ± 1.1 years) during a 5-day asthma camp. FOT was performed at 6 Hz in triplicate on each test occasion. Relationships between day-to-day FOT variability (expressed as within-subject SD [SDW] and asthma control and severity (defined according to GINA [Global Initiative for Asthma] recommendations) were explored. For comparison, normal baseline FOT values and variability, measured on two occasions, were defined in a separate cohort of 38 healthy children (age, 9.5 ± 1.0 years).

RESULTS:  Day-to-day Rrs variability was greater in persistent (n = 16) vs intermittent (n = 6) asthma (mean SDW, 0.69 cm H2O/L/s vs 0.39 cm H2O/L/s; P ≤ .01). Day-to-day Rrs variability was increased in uncontrolled (n = 13) vs partly controlled asthma (n = 9) (mean SDW, 0.75 cm H2O/L/s vs 0.42 cm H2O/L/s; P ≤ .05). PEF variability did not differentiate the groups. Day-to-day variability of Rrs and Xrs but not baseline values were increased in children with asthma vs control children (Rrs mean SDW, 0.61 cm H2O/L/s vs 0.33 cm H2O/L/s [P ≤ .05]; Xrs mean SDW, 0.24 cm H2O/L/s vs 0.15 cm H2O/L/s [P ≤ .05]).

CONCLUSIONS:  Increased day-to-day FOT variability exists in school-aged children with asthma. Day-to-day Rrs variability was associated with asthma severity and asthma control. FOT may be a useful objective monitoring tool in pediatric asthma and warrants further study.

TRIAL REGISTRY:  Australian and New Zealand Clinical Trials Registry; No.: ACTRN12614000885695; URL: www.anzctr.org.au

Figures in this Article

Asthma is the most common chronic respiratory condition among children in the developed world, and despite recent advances in treatment, it remains a significant cause of respiratory morbidity and mortality.1 Asthma is characterized by variable airflow obstruction. Increased day-to-day variability of lung function, measured by peak expiratory flow (PEF), is characteristic of asthma in adults and a marker of severity and risk of exacerbations,2 suggesting that monitoring of lung function should be an integral component of clinical management of asthma in adults. However, pediatric asthma management is primarily symptom based because there are no suitable objective measurements for monitoring lung function. Symptom-based management, although useful,3 is limited by poor perception and reporting by both patients and parents.4 Development of objective pediatric monitoring tools would improve existing clinical management strategies.

In children, conventional lung function tests such as FEV1 and PEF are not well suited to monitoring day-to-day lung function variability. Both FEV1 and PEF are effort dependent and require considerable patient cooperation. Reduced FEV1 is associated with an increased risk of future exacerbations,5 and increased variability in FEV1 occurs in children with chronic respiratory symptoms or asthma.6 However, FEV1 utility as a monitoring tool is limited because the majority of patients have normal FEV1, even during acute exacerbations.7 Although PEF variability predicts subsequent response to asthma treatment,8 written daily PEF diaries are unreliable in children.9 Even with electronic PEF meters, correlation between PEF variability and asthma severity is poor.10

The forced oscillation technique (FOT) measures respiratory system resistance (Rrs) and respiratory system reactance (Xrs) during tidal breathing. FOT, therefore, is an effort-independent measure of lung function and feasible across wide age ranges, including preschool age.11 Although diagnostic utility of FOT in children with asthma is limited,12,13 it may be suitable as a monitoring tool. In children, FOT parameters objectively measure bronchodilator response14,15 and airways hyperresponsiveness16,17 and have greater day-to-day variability than FEV1 in children with asthma18 or chronic respiratory symptoms.19 However, relationships between day-to-day variability of FOT parameters and clinical markers of asthma in children are unknown.

We hypothesized that day-to-day FOT variability in children would be increased in asthma and would relate to both asthma severity and asthma control. The aims of this study were to determine relationships between FOT variability and asthma severity and symptom control in a cohort of school-aged children with asthma and to compare measures of FOT variability to those in children without asthma.

Asthma Camp Cohort

Children with asthma were recruited for this study from those aged 8 to 12 years attending a 5-day holiday camp for children with asthma. The camp is run by the Asthma Foundation of New South Wales. Attendees had a physician diagnosis of asthma as reported by their parents, which was a prerequisite for camp attendance. Parents of all children completed questionnaires on past and current respiratory health, symptoms, and medication use.

Asthma severity and asthma symptom control were determined based on the questionnaire information and by daily recording of symptoms and medication use while at camp, as recorded by camp staff. Children were classified as having intermittent or persistent asthma.20 Asthma was also classified as being controlled, partly controlled, or uncontrolled3 based on GINA (Global Initiative for Asthma) guideline recommendations.

FOT was performed daily during asthma camp at the same time each day, at least 30 min after supervised medication administration, and with at least 10 min rest prior to measurement. Respiratory system impedance was measured at 6 Hz using an in-house-built FOT device, as described in detail previously,21 but modified to reduce total equipment dead space to comply with recent pediatric recommendations.22 Impedance repeatability checks and volume checks were performed at the start and end of each testing session. At each visit, following a practice test, three technically acceptable 1-min FOT measurements were performed with the child sitting upright while wearing a nose clip and with the cheeks and floor of mouth supported (by the child under instruction). Recordings were deemed acceptable by the technician if tidal volume and breathing frequency appeared stable, with no obvious leaks or glottic closures from visual inspection of the volume trace. Breath-by-breath data filtering was used to identify and reject entire breaths in which respiratory artifact occurred.23 Rrs and Xrs were recorded for each session as the mean of all three tests and expressed as raw values because of the lack of equipment-specific FOT normative data in this age-group.

Spirometry was also performed on one occasion during the camp after FOT measurement. Spirometry was performed using a SpiroCard (QRS Diagnostic) in accordance with American Thoracic Society recommendations24 and expressed as z scores using recently published normative data.25,26 An asthma camp volunteer experienced in the technique supervised bid PEF measurement for each child just prior to medication administration. The highest measurement of three acceptable PEF attempts was recorded for each test session.

Healthy Control Comparison Cohort

The healthy control cohort was recruited as part of a separate study, comprising a randomly selected cross-section of children aged 8 to 12 years attending two primary schools in Brisbane, Queensland, Australia. They had been recruited as part of a feasibility study of air pollution effects on respiratory health. Parents of these children completed detailed respiratory history questionnaires as part of the recruitment process and had no history of diagnosis of chronic respiratory disease and no chronic respiratory symptoms or medication use. As part of the protocol for the air pollution study, FOT was performed in a designated room within the school at the same time of day on two occasions 2 weeks apart. Spirometry was also performed at each visit after FOT.

Data Handling and Analysis

Data were analyzed using Analyze-it for Microsoft Excel software (Analyze-it Software Ltd). FOT variability was quantified using the SD, given that it was unrelated to mean across-the-cohort data sets (data not shown). Within-session test repeatability was calculated as within-subject SD (SDW) of three FOT measurements within a single testing session. Day-to-day repeatability of impedance (termed “day-to-day SDW”) was calculated for the asthma camp cohort as SDW of the means from all testing days (ie, a single mean value used for each day) and for the healthy cohort, as SDW of the means of the two testing sessions (ie, days 1 and 14). To adjust for differing test numbers in the SDW calculation (n = 5 asthma vs n = 2 healthy, respectively), additional SDW values for children with asthma were calculated from first and last testing sessions alone. Intraclass correlation coefficients (ICCs) were calculated as recommended by Bland and Altman.27 PEF variability was expressed as the lowest PEF value as a percentage of the best PEF value, as recommended by Brand et al,28 due to previous correlation with asthma symptoms. The t test was used to compare means between groups, and the χ2 test was used to compare categorical variables. Statistical significance was defined as P ≤ .05. Ethics committee approvals were obtained for the two studies contributing data to this article. Ethics approval for the air pollution study (healthy cohort testing) was obtained from the Queensland University of Technology (Institutional Review Board reference 1000000703), whereas approval for the asthma camp study was obtained from The Children’s Hospital at Westmead (Institutional Review Board reference 07/CHW/14). Written informed consent to participate was provided by a parent or guardian of each child.

Twenty-two children (100% of attendees) were recruited from the asthma camp, and 39 children were eligible for inclusion from the healthy cohort. All of the asthma camp cohort provided technically acceptable FOT data on all days of testing. Of the healthy cohort, two children failed to attend both testing sessions, and data from three children were subsequently excluded following FOT data analysis (one due to marked tachypnea and two due to presence of frequent upper airway artifact and variable leak). Thirty-four children, therefore, were included in the healthy cohort analysis. Characteristics and baseline lung function of the children according to asthma status are shown in Table 1. The asthma camp cohort had a higher proportion of boys (77% vs 47%, P = .03) and similar spirometry (% predicted and z scores) but lower Rrs than the healthy cohort. This finding likely is due to the difference in height between the cohorts, with lower Rrs values seen in the taller children with asthma. This relationship between Rrs and height is shown in e-Figure 1 and is consistent with published data.29

Table Graphic Jump Location
TABLE 1 ]  Baseline Characteristics and Lung Function of the Asthma Camp (According to Asthma Severity) and Healthy Control Cohorts

Data are presented as No. (%) and mean ± SD. Forced oscillation technique and spirometry data were taken from the first testing session for each cohort. Rrs = respiratory system resistance; Xrs = respiratory system reactance.

a 

P ≤ .05 compared with healthy.

Day-to-Day FOT Variability and Asthma Severity

Sixteen children with asthma (68%) were classified as having persistent asthma and six as having intermittent asthma. Baseline characteristics were similar for both asthma severity groups (Table 1). All children with persistent asthma were prescribed maintenance asthma preventer medications. Fourteen were managed with inhaled corticosteroids (ICSs) of which seven used ICS and a long-acting β2-agonist; four used ICS alone; and three used ICS, long-acting β2-agonist, and a leukotriene receptor antagonist. The remaining two children were managed with leukotriene receptor antagonist alone. Within-session SDW of Rrs and Xrs did not differ between the intermittent and persistent asthma groups. Day-to-day variability of Rrs, however, was greater in the persistent than in the intermittent asthma group (Fig 1, Table 2). Day-to-day variability of Xrs did not differ between the two groups (P = .12).

Figure Jump LinkFigure 1 –  Day-to-day variability, expressed as SDW, for children in the asthma camp cohort classified according to asthma severity as having either intermittent (○) or persistent (●) asthma. Horizontal bars indicate mean SDW values for each group. Rrs6 = respiratory system resistance at 6 Hz; SDW = within-subject SD.Grahic Jump Location
Table Graphic Jump Location
TABLE 2 ]  Repeatability and Day-to-Day Variability of Rrs and Xrs in Children With Intermittent and Persistent Asthma Compared With Healthy Control Children

SDW = within-subject SD. See Table 1 legend for expansion of other abbreviations.

a 

P ≤ .01 compared with healthy.

b 

P ≤ .05 compared with intermittent asthma.

c 

P ≤ .05 compared with healthy.

Day-to-Day FOT Variability and Asthma Control

Thirteen children with asthma (59%) were classified as having uncontrolled asthma and nine as having partly controlled asthma. Within-session repeatability of Rrs in the uncontrolled asthma group was slightly worse than in the partly controlled asthma group (P ≤ .05). Day-to-day variability of Rrs was greater in the uncontrolled than in the partly controlled asthma group (P ≤ .05) (Fig 2, Table 3) and greater than the within-session repeatability seen. Repeatability of Xrs in the children with uncontrolled asthma was worse than in the healthy children (P ≤ .05) but did not differ from the children with partly controlled asthma (P = .21). Day-to-day variability of Xrs did not differ between the two groups (P = .11). PEF day-to-day variability did not differ between the uncontrolled and partly controlled asthma groups (Fig 3).

Figure Jump LinkFigure 2 –  Day-to-day variability, expressed as SDW, for children in the asthma camp cohort classified according to asthma symptom control as having either partly controlled (○) or uncontrolled (●) asthma. Horizontal bars indicate mean SDW values for each group. See Figure 1 legend for expansion of abbreviations.Grahic Jump Location
Table Graphic Jump Location
TABLE 3 ]  Repeatability and Day-to-Day Variability of Rrs and Xrs in Children With Partly Controlled or Uncontrolled Asthma Compared With Healthy Control Children

See Table 1 and 2 legends for expansion of abbreviations.

a 

P ≤ .05 compared with partly controlled.

b 

P ≤ .05 compared with healthy.

c 

P ≤ .01 compared with healthy.

Figure Jump LinkFigure 3 –  Relationship between asthma control and day-to-day PEF variability, expressed as the lowest PEF value as a percentage of the best PEF value, for children with asthma classified as having either partly controlled (○) or uncontrolled (●) asthma. Horizontal bars indicate mean values for each group. PEF = peak expiratory flow.Grahic Jump Location
Comparison Between the Asthma Camp and Healthy Control Cohorts

Within-session repeatability for Rrs and Xrs were similar between the asthma camp and healthy cohorts. In healthy children, Rrs and Xrs remained highly repeatable between testing sessions, with between-session ICCs of 0.89 and 0.88, respectively. Corresponding ICCs in the children with asthma, however, were lower at 0.64 and 0.71, respectively (based on the first and last testing session for comparison). Day-to-day variability of Rrs and Xrs were significantly greater than the corresponding within-session repeatability in children with asthma (P ≤ .05) (Table 2). This was also found for Rrs among healthy children (P ≤ .05) but not for Xrs. Day-to-day variability of Rrs and Xrs in children with asthma was increased compared with healthy children (P ≤ .05) (Table 2). Increased day-to-day variability compared with healthy children remained similar in magnitude and statistical significance, using SDW calculated from the first and last testing sessions in the children with asthma (data not shown).

In this study, we showed for the first time in our knowledge that day-to-day Rrs variability is related to both asthma severity and asthma control, whereas PEF variability did not differentiate. Day-to-day variability in Xrs did not differentiate. Rrs and Xrs are highly repeatable measurements in both healthy children and children with asthma. Day-to-day Rrs variability was greater in children with asthma compared with healthy children and was greater than the variability of the measurement itself. These novel findings provide evidence that FOT Rrs may be a suitable objective monitoring tool in pediatric asthma because increased variability in children with asthma is likely due to the effects of disease.

Potential clinical utility of serial Rrs measurements both in terms of asthma severity and control are novel findings. This is reinforced by the single FOT measurements at baseline being poorly discriminative between children with asthma and healthy children (e-Fig 1, Table 1). Past attempts to investigate the utility of FOT variability have focused on FOT fluctuations within single recordings or across tests within single testing sessions.23,3032 Increased within-recording variability (or reduced test repeatability) has been reported for both adult and pediatric patients with asthma compared with healthy control subjects. Increased variability of impedance over a 15-min recording period was originally reported in adults with asthma.23 In children, where prolonged recording is more technically difficult, increased Rrs variability was described across three 1-min recordings joined together31 or across successive Rrs values at points of zero flow within a single recording of 40 to 45 breaths.32 However, clinical utility of within-session variability has not been consistently found in adult asthma studies.30 Diba et al,30 using a shortened 1-min recording window, compared with Que et al,23 found no difference in impedance variability between adults with asthma and healthy control subjects and no relationships between this measured variability and either diurnal variability or airways hyperresponsiveness. In the current study, within-recording variability was not examined, and within-session repeatability of Rrs and Xrs was expressed as the variability across the mean Rrs and Xrs values from technically acceptable recordings. Within-session repeatability was similar in the healthy and asthma camp cohorts but was worse in children with uncontrolled vs partly controlled asthma. However, considerable overlap existed between these groups, which would be expected to limit utility of this approach.

Day-to-day variability of both Rrs and Xrs was greater than inherent test variability (within-session SDW), suggesting that increased day-to-day variability in children with asthma compared with healthy children is due to asthma-related differences in lung physiology. Previously, Goldman et al18 performed daily impulse oscillometry and spirometry measurements over 3 days in an asthma camp setting and showed that Rrs day-to-day variability was greater than that of spirometry. Timonen et al19 measured FOT in children with chronic respiratory disease and showed increased Rrs day-to-day and week-to-week variability compared with both FEV1 and FEF, midexpiratory phase. The findings of the current study are consistent with these previous pediatric studies. In adults with asthma, Timmins et al33 also reported increased day-to-day variability in Rrs but not Xrs compared with healthy control subjects. Relationships to asthma control and severity were not examined in their study. It is unclear why Rrs is more variable in poorly controlled and persistent asthma, whereas Xrs is not. Rrs and Xrs may confer different information in relation to the dynamic behavior of asthmatic airways. However, the basis of these differences is unknown, but nevertheless, Rrs may be more informative than Xrs in children and adults with asthma. Several possible explanations can be speculated. There may be different contributions of airway narrowing and airway closure in asthma to Rrs and Xrs. Interestingly, the volume dependence of Xrs, reflecting airway closure, relates to asthma control.34 However, the simple measure of Xrs at functional residual capacity may not capture the same clinically important information. Rrs and Xrs may reflect abnormalities in various airway compartments, although the nature of the differences are again uncertain.

The current study extends these findings in two important ways. First, inclusion of a control group confirms the increased variability present in children with asthma by defining normal variability of FOT parameters in school-aged children. Second, FOT variability was related to test repeatability and measures of asthma control and severity. The similar relationship with both symptom control and severity is not surprising given that both are predominantly symptom based, with preventer treatment being considered in the severity score. Despite the small numbers, a statistically significant difference with relatively small overlap was observed (Figs 1, 2) and suggests that repeated measurements could be clinically useful as an assessment for asthma control. However, larger longitudinal studies are required to confirm this finding and determine whether increased Rrs variability predicts future loss of control in children, as shown by PEF in adults.35 Difficulties with PEF in children have already been discussed, and in the present cohort, PEF variability did not relate to asthma control.

In measuring between-session repeatability in healthy children and comparing with an asthma cohort, we assumed that variability of two measurements performed 14 days apart were representative of test variability over a few days. We believe that this was a reasonable assumption for two reasons. First, the healthy children studied were stable, without evidence of acute illness, over the period of measurement. Second, in the asthma camp cohort, there were no effects from the environment, particularly in relation to supervised medication administration. Such effects are unlikely because no significant changes in either Rrs or Xrs occurred from the start to the end of the camp. In addition, supervised medication administration might have actually decreased observed FOT variability; therefore, finding increased variability under these circumstances may underestimate the actual increased variability present. Finally, although there was a sex difference between cohorts (more boys in the asthma cohort), we do not believe that this influenced the findings reported because most pediatric FOT studies conducted to date have not reported a sex effect on FOT results.22

Although asthma camps provide a unique opportunity to conduct well-supervised studies of this nature in children,18,31 future studies will need to establish feasibility, as already demonstrated in adults,36,37 of FOT monitoring in children in the unsupervised home setting. The clinical relevance of the current findings is that Rrs variability differs in relation to asthma control and severity, giving support for future studies on home monitoring provided that technological advances will lead to small, practical FOT devices for this purpose in children and adults.

In conclusion, day-to-day variability of Rrs in school-aged children with asthma is related to both disease severity and symptom control and is greater than that observed in healthy children. These findings, combined with low variability of Rrs in healthy, school-aged children, suggest potential utility of daily FOT measurement in pediatric asthma management. Future studies are needed to confirm these relationships in the home setting and the ability of FOT monitoring to predict future asthma exacerbations and response to treatment.

Author contributions: P. D. R. had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. P. D. R., N. J. B., M. T., P. V. A., H. S., and G. G. K. contributed to the study concept and design, data analysis and interpretation, drafting of the manuscript, review of the manuscript for important intellectual content, and final approval of the manuscript; and P. D. R. and M. T. contributed to the data acquisition.

Financial/nonfinancial disclosures: The authors have reported to CHEST the following conflicts of interest: Dr King has received various sponsorships from Boehringer Ingelheim GmbH; Novartis AG; Pfizer, Inc; AstraZeneca plc; and GlaxoSmithKline plc for travel and accommodation to attend international, local, and interstate meetings that include pharmaceutical industry-sponsored meetings and independent society scientific meetings. A proportion of Dr King’s research is conducted at the Woolcock Institute of Medical Research, which receives or has received unrestricted grants from AstraZeneca plc, Boehringer Ingelheim GmbH, GlaxoSmithKline plc, and Pharmaxis Ltd and which also has current and past consultancy agreements with AstraZeneca plc; Boehringer Ingelheim GmbH; GlaxoSmithKline plc; and Pfizer, Inc. His research group receives a proportion of the grants and monies that arise from those companies as part of a general allocation of funds for research purposes across all research groups of the Woolcock Institute of Medical Research. Dr King provides consultancy services related to asthma and COPD, which include sitting on advisory boards and providing talks at local and national meetings for AstraZeneca plc, Boehringer-Ingelheim GmbH, GlaxoSmithKline plc, Mundipharma International, and Novartis AG, for which his institution and research group receive payments. His research group receives support from competitive grants arising from local research foundations, the National Health and Medical Research Council of Australia, Cooperative Research Centre for Asthma and Airways, and Lung Foundation Australia. Dr King’s research group is also supported by grants from Boehringer Ingelheim GmbH, GlaxoSmithKline plc, and Mundipharma International. Drs Robinson, Brown, Turner, Van Asperen, and Selvadurai have reported that no potential conflicts of interest exist with any companies/organizations whose products or services may be discussed in this article.

Role of sponsors: The sponsors had no role in the design of the study, the collection and analysis of the data, or the preparation of the manuscript.

Other contributions: The authors thank Asthma Foundation New South Wales for its support in facilitating the FOT measurements at its annual asthma camp held in conjunction with the New South Wales Department of Sport and Recreation. They also thank the members of the UPTECH (Ultrafine Particles from Traffic Emissions and Children’s Health) project, including Guy Marks, Lidia Morawska, Kerrie Mengersen, Zoran Ristovski, Godwin Ayoko, Mandana Mazaheri, Sama Low Choy, Jaime Mejia, Wafaa Ezz, Gail Williams, Diane Keogh, Adriana Cortes, and Brett Toelle for their contribution to this work. The authors further thank Matthew Falk for his assistance in the classification of the epidemiologic studies and his contribution to the discussion of epidemiologic study design, Folasade Fatokun (formerly from International Laboratory for Air Quality and Health, Queensland University of Technology, and currently from the Department of Employment, Economic Development and Innovation) for the initial collection of the literature, and Rachael Appleby for administrative assistance.

Additional information: The e-Figure can be found in the Supplemental Materials section of the online article.

FOT

forced oscillation technique

ICC

intraclass correlation coefficient

ICS

inhaled corticosteroid

PEF

peak expiratory flow

Rrs

respiratory system resistance

SDW

within-subject SD

Xrs

respiratory system reactance

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Bland JM, Altman DG. Measuring agreement in method comparison studies. Stat Methods Med Res. 1999;8(2):135-160. [CrossRef] [PubMed]
 
Brand PL, Duiverman EJ, Postma DS, Waalkens HJ, Kerrebijn KF, van Essen-Zandvliet EE; Dutch CNSLD Study Group. Peak flow variation in childhood asthma: relationship to symptoms, atopy, airways obstruction and hyperresponsiveness. Eur Respir J. 1997;10(6):1242-1247. [CrossRef] [PubMed]
 
Marchal F, Hall GL. Forced oscillation technique.. In:Frey U, Merkus PJFM., eds. European Respiratory Monograph 47: Paediatric Lung Function. Sheffield, England: European Respiratory Society; 2010:121-136.
 
Diba C, Salome CM, Reddel HK, Thorpe CW, Toelle B, King GG. Short-term variability of airway caliber-a marker of asthma? J Appl Physiol (1985). 2007;103(1):296-304. [CrossRef] [PubMed]
 
Lall CA, Cheng N, Hernandez P, et al. Airway resistance variability and response to bronchodilator in children with asthma. Eur Respir J. 2007;30(2):260-268. [CrossRef] [PubMed]
 
Trübel H, Banikol WK. Variability analysis of oscillatory airway resistance in children. Eur J Appl Physiol. 2005;94(4):364-370. [CrossRef] [PubMed]
 
Timmins SC, Coatsworth N, Palnitkar G, et al. Day-to-day variability of oscillatory impedance and spirometry in asthma and COPD. Respir Physiol Neurobiol. 2013;185(2):416-424. [CrossRef] [PubMed]
 
Kelly VJ, Sands SA, Harris RS, et al. Respiratory system reactance is an independent determinant of asthma control. J Appl Physiol (1985). 2013;115(9):1360-1369. [CrossRef] [PubMed]
 
Thamrin C, Taylor DR, Jones SL, Suki B, Frey U. Variability of lung function predicts loss of asthma control following withdrawal of inhaled corticosteroid treatment. Thorax. 2010;65(5):403-408. [CrossRef] [PubMed]
 
Dellacà RL, Gobbi A, Pastena M, Pedotti A, Celli B. Home monitoring of within-breath respiratory mechanics by a simple and automatic forced oscillation technique device. Physiol Meas. 2010;31(4):N11-N24. [CrossRef] [PubMed]
 
Rigau J, Burgos F, Hernández C, Roca J, Navajas D, Farré R. Unsupervised self-testing of airway obstruction by forced oscillation at the patient’s home. Eur Respir J. 2003;22(4):668-671. [CrossRef] [PubMed]
 

Figures

Figure Jump LinkFigure 1 –  Day-to-day variability, expressed as SDW, for children in the asthma camp cohort classified according to asthma severity as having either intermittent (○) or persistent (●) asthma. Horizontal bars indicate mean SDW values for each group. Rrs6 = respiratory system resistance at 6 Hz; SDW = within-subject SD.Grahic Jump Location
Figure Jump LinkFigure 2 –  Day-to-day variability, expressed as SDW, for children in the asthma camp cohort classified according to asthma symptom control as having either partly controlled (○) or uncontrolled (●) asthma. Horizontal bars indicate mean SDW values for each group. See Figure 1 legend for expansion of abbreviations.Grahic Jump Location
Figure Jump LinkFigure 3 –  Relationship between asthma control and day-to-day PEF variability, expressed as the lowest PEF value as a percentage of the best PEF value, for children with asthma classified as having either partly controlled (○) or uncontrolled (●) asthma. Horizontal bars indicate mean values for each group. PEF = peak expiratory flow.Grahic Jump Location

Tables

Table Graphic Jump Location
TABLE 1 ]  Baseline Characteristics and Lung Function of the Asthma Camp (According to Asthma Severity) and Healthy Control Cohorts

Data are presented as No. (%) and mean ± SD. Forced oscillation technique and spirometry data were taken from the first testing session for each cohort. Rrs = respiratory system resistance; Xrs = respiratory system reactance.

a 

P ≤ .05 compared with healthy.

Table Graphic Jump Location
TABLE 2 ]  Repeatability and Day-to-Day Variability of Rrs and Xrs in Children With Intermittent and Persistent Asthma Compared With Healthy Control Children

SDW = within-subject SD. See Table 1 legend for expansion of other abbreviations.

a 

P ≤ .01 compared with healthy.

b 

P ≤ .05 compared with intermittent asthma.

c 

P ≤ .05 compared with healthy.

Table Graphic Jump Location
TABLE 3 ]  Repeatability and Day-to-Day Variability of Rrs and Xrs in Children With Partly Controlled or Uncontrolled Asthma Compared With Healthy Control Children

See Table 1 and 2 legends for expansion of abbreviations.

a 

P ≤ .05 compared with partly controlled.

b 

P ≤ .05 compared with healthy.

c 

P ≤ .01 compared with healthy.

References

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Miller MR, Hankinson J, Brusasco V, et al; ATS/ERS Task Force. Standardisation of spirometry. Eur Respir J. 2005;26(2):319-338. [CrossRef] [PubMed]
 
Pan H, Cole TJ. LMSgrowth, a Microsoft Excel add-in to access growth references based on the LMS method. Version 2.69. Harlow Healthcare website. http://www.healthforallchildren.co.uk. Published 2010. Accessed November 30, 2013.
 
Stanojevic S, Wade A, Stocks J, et al. Reference ranges for spirometry across all ages: a new approach. Am J Respir Crit Care Med. 2008;177(3):253-260. [CrossRef] [PubMed]
 
Bland JM, Altman DG. Measuring agreement in method comparison studies. Stat Methods Med Res. 1999;8(2):135-160. [CrossRef] [PubMed]
 
Brand PL, Duiverman EJ, Postma DS, Waalkens HJ, Kerrebijn KF, van Essen-Zandvliet EE; Dutch CNSLD Study Group. Peak flow variation in childhood asthma: relationship to symptoms, atopy, airways obstruction and hyperresponsiveness. Eur Respir J. 1997;10(6):1242-1247. [CrossRef] [PubMed]
 
Marchal F, Hall GL. Forced oscillation technique.. In:Frey U, Merkus PJFM., eds. European Respiratory Monograph 47: Paediatric Lung Function. Sheffield, England: European Respiratory Society; 2010:121-136.
 
Diba C, Salome CM, Reddel HK, Thorpe CW, Toelle B, King GG. Short-term variability of airway caliber-a marker of asthma? J Appl Physiol (1985). 2007;103(1):296-304. [CrossRef] [PubMed]
 
Lall CA, Cheng N, Hernandez P, et al. Airway resistance variability and response to bronchodilator in children with asthma. Eur Respir J. 2007;30(2):260-268. [CrossRef] [PubMed]
 
Trübel H, Banikol WK. Variability analysis of oscillatory airway resistance in children. Eur J Appl Physiol. 2005;94(4):364-370. [CrossRef] [PubMed]
 
Timmins SC, Coatsworth N, Palnitkar G, et al. Day-to-day variability of oscillatory impedance and spirometry in asthma and COPD. Respir Physiol Neurobiol. 2013;185(2):416-424. [CrossRef] [PubMed]
 
Kelly VJ, Sands SA, Harris RS, et al. Respiratory system reactance is an independent determinant of asthma control. J Appl Physiol (1985). 2013;115(9):1360-1369. [CrossRef] [PubMed]
 
Thamrin C, Taylor DR, Jones SL, Suki B, Frey U. Variability of lung function predicts loss of asthma control following withdrawal of inhaled corticosteroid treatment. Thorax. 2010;65(5):403-408. [CrossRef] [PubMed]
 
Dellacà RL, Gobbi A, Pastena M, Pedotti A, Celli B. Home monitoring of within-breath respiratory mechanics by a simple and automatic forced oscillation technique device. Physiol Meas. 2010;31(4):N11-N24. [CrossRef] [PubMed]
 
Rigau J, Burgos F, Hernández C, Roca J, Navajas D, Farré R. Unsupervised self-testing of airway obstruction by forced oscillation at the patient’s home. Eur Respir J. 2003;22(4):668-671. [CrossRef] [PubMed]
 
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