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ORIGINAL ARTICLE
Year : 2020  |  Volume : 37  |  Issue : 1  |  Page : 30-36  

Regression equations of respiratory impedance of Indian adults measured by forced oscillation technique


Department of Pulmonary Medicine, National Institute for Research in Environmental Health, Bhopal, Madhya Pradesh, India

Date of Submission02-Jun-2019
Date of Acceptance18-Oct-2019
Date of Web Publication31-Dec-2019

Correspondence Address:
Dr. Sajal De
Department of Pulmonary Medicine, National Institute for Research in Environmental Health, Kamla Nehru Hospital Building, Gandhi Medical College Campus, Bhopal - 462 001, Madhya Pradesh
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/lungindia.lungindia_260_19

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   Abstract 


Background: Forced oscillation technique (FOT) is a technique to measure the mechanical properties of the lung. The present study was aimed to develop regression equations of within- and whole-breath respiratory impedance (Zrs) of healthy Indian adults. Methods: Total 323 adults were sequentially screened. Smokers, individuals with respiratory symptoms or diseases, and unable to perform acceptable FOT were excluded. Within- and whole-breath resistance (Rrs) and reactance (Xrs) were measured at 5, 11, and 19 Hz by Resmon Pro® Full device. The regression equations of within- and whole-breath Rrs and Xrs were generated separately for men and women by multiple linear regression models. Results: The FOT data of 253 individuals (122 men) aged 18–81 years were included in the analysis. The magnitudes of whole-breath Rrs at 5 Hz (4.53 ± 1.05 cmH2O/L/s in women vs. 3.26 ± 1.05 cmH2O/L/s in men; P = 0.000) and whole-breath Xrs at 5 Hz (−1.23 ± 0.66 cmH2O/L/s in women vs. −1.00 ± 0.54 cmH2O/L/s in men; P = 0.003) of women were significantly of higher magnitude as compared to men. The standing height was the best determinant of Zrs, followed by body weight; the effect of age was negligible and was observed in men only. The magnitudes of both Rrs and Xrs decrease with an increase in standing height of both men and women. Conclusions: The present study provides regression equations of within- and whole-breath respiratory impedance of Indian adults.

Keywords: Forced oscillation technique, Indian adults, respiratory impedance, regression equation, within-breath analysis


How to cite this article:
De S, Banerjee N, Kushwah GD, Dharwey D. Regression equations of respiratory impedance of Indian adults measured by forced oscillation technique. Lung India 2020;37:30-6

How to cite this URL:
De S, Banerjee N, Kushwah GD, Dharwey D. Regression equations of respiratory impedance of Indian adults measured by forced oscillation technique. Lung India [serial online] 2020 [cited 2020 Jan 21];37:30-6. Available from: http://www.lungindia.com/text.asp?2020/37/1/30/274417




   Introduction Top


Forced oscillation technique (FOT) is a noninvasive tool to measure mechanical properties of the respiratory system, i.e., respiratory impedance (Zrs) by superimposing multiple sinusoidal pressure waves on tidal breaths. Zrs is calculated by analyzing the resulting changes in pressure and flow relationships. Zrs is comprised of respiratory system resistance (Rrs) and respiratory system reactance (Xrs). Technically, Rrs measures frictional forces opposing airflow and Xrs measures both elastic and inertial properties of the respiratory system. Physiologically, Rrs at lower frequency, for example, Rrs at 5 Hz (R5) is considered as a representation of total airway resistance, and Xrs at 5 Hz (X5) mostly relates to the functionality of small airways.[1] The advantages of FOT as compared to other lung function tests are easier to perform, require minimal cooperation of individual and no special breathing maneuvers during measurements.

The utility of FOT in adults is gaining clinical importance and its use is also expanding. The sensitivity of FOT to detect airway obstruction is similar or superior to that of spirometry.[2] Studies have shown the potential utility of separate measurement of inspiratory and expiratory Zrs, using an approach known as within-breath analysis.[2],[3] Within-breath analysis helps to calculate inspiratory and expiratory Rrs and Xrs separately.

For clinical interpretation, observed Rrs and Xrs values are to be compared with reference values generated from a healthy local population. The predicted values of Rrs and Xrs depend on ethnicity, gender, standing height, body weight, and age of the individual.[4] Most of the presently available regression equations of Zrs are derived from Caucasian and Chinese populations.[4] To the best of our knowledge, the reference value for Zrs in healthy Indian adults had never been explored. The present study aimed to develop regression equations of within- and whole-breath respiratory impedance for healthy Indian adults using the forced oscillation technique.


   Methods Top


Subjects

A prospective cross-sectional study of lung function measurements by FOT and spirometry was carried out in Bhopal, a city located in central India. The study protocol was approved by the Institutional Ethics Committee of the National Institute for Research in Environmental Health, and written informed consent was obtained from each individual.

Study procedure

The study questionnaire was designed by incorporating Hindi Translation of INSEARCH (Indian study on epidemiology of asthma, respiratory symptoms, and chronic bronchitis) questionnaire to identify individuals with respiratory symptoms or disease.[5] In the questionnaire, individuals were asked about history of whistling sound from their chest during the past 12 months, tightness in the chest or breathlessness in the morning; shortness of breath after finishing exercises or at rest; nocturnal awakening due to cough or breathlessness; coughing or expectoration in the morning; past history of ever asthma or asthma attack; and use of any medication for breathlessness. The information on demographic profile, current and past history of smoking, and other diseases including pulmonary tuberculosis were collected. The exclusion criteria were the presence of bronchial asthma; chronic obstructive pulmonary disease (COPD); chronic bronchitis; having any above-mentioned respiratory symptoms; recent respiratory tract infection (<2 weeks); the history of pulmonary tuberculosis; ever-smoker; the history of cardiovascular disease (except hypertension), and unable to perform acceptable FOT. Ever-smoker was defined as those who had smoked more than 1 cigarette or bidi per day.

The age in completed years, gender, and standing height with erect head and without footwear to the nearest centimeter were recorded. Body weight was measured to the nearest 1.0 kg using an electronic scale wearing light clothing and no footwear. Resmon Pro Full device ® (Restech Srl, Milan, Italy) was used for FOT. This FOT device is capable to measure both within- and whole-breath Rrs and Xrs at each frequency. Resmon Pro uses a stringent patented breath-reject algorithm to exclude breath with artifacts and nonphysiological breaths.[6] The inspiratory, expiratory, and whole-breath Rrs and Xrs were measured breath-by-breath at 5 Hz, 11 Hz, and 19 Hz, and the results were presented in cmH2O/L/s as mean (±standard deviation) of all the accepted breaths. The device calibrated daily before use by a reference impedance supplied by the manufacturer. The test procedure was explained to each participant in simple language. The tests were carried out during the morning and early afternoon. The tests were performed in an upright sitting position with the neck slightly flexed and legs uncrossed as per European Respiratory Society recommendation.[1] Participants were asked to breathe normally through a tightly sealed mouthpiece of an antibacterial filter and wearing a nose clip. During the procedure, cheeks were supported by the participant themselves and reinforced by the technician. The impedance of the antibacterial filter was measured before each test by the device and that impedance was adjusted during reporting results. The participants were first allowed to familiarize themselves with the technique by performing a few sham breaths. A minimum of three tests was performed per individual, and each test was continued until 15 accepted breaths were recorded by the device. A test was retained for subsequent analysis only if more than 50% of the breaths were accepted by the device, and within-test coefficient of variation (×100 standard deviation/mean, expressed in percentage) of whole-breath resistance at 5 Hz (R5) was smaller than 30%.[7] Additional spirometry was carried out in agreed individuals as per ATS-ERS recommendation using PowerCube Diffusion+ (GANSHORN Medizin Electronic, Germany).[8]

Statistical analysis

The statistical analyses were performed by IBM SPSS statistics for Window (Version 25.0, Armonk, NY:IBM crop), and data were summarized as a mean ± standard deviation. The study population was further subdivided into four age groups, i.e., 18–30, 31–45 years, 46–60 years, and more than 60 years. One-way ANOVA was used to find significant differences between age groups. The Student's t-test was used to compare the sample means of men and women. For all analyses, a two-tailed P < 0.05 was considered statistically significant. The relationships of both Rrs and Xrs with independent anthropometric variables were analyzed by Pearson's correlation coefficients. The regression equations for Rrs and Xrs were carried out using a multivariate linear regression model for men and women separately by including independent anthropometric variables (e.g., standing height, body weight, and age) to obtain the best model based on the highest coefficients of determination. Reference equations were presented with coefficients of determination (R2) and standard errors of estimate.


   Results Top


Study population

From April 2018 to March 2019, 323 adults of age 18 years and more were screened. Out of them, total 253 adults of age 41.8 ± 13.7 years (range: 18–81 years) were included in the present analysis, and causes of rejections are mentioned in [Figure 1]. Men accounted for 48% (n = 122) of study population. The standing height, body weights, and body mass index of the study population were 161.2 ± 9.9 cm, 65.5 ± 13.3 kg, and 25.1 ± 3.9 kg/m 2, respectively. Men were taller (168.1 ± 8.2 cm) as compared to women (154.8 ± 6.5 cm, P = 0.00). However, body mass index of men (25.3 ± 3.6 kg/m 2) and women was comparable (24.9 ± 4.1 kg/m 2, P = 0.47).
Figure 1: Flowchart of study participant inclusion process

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Forced oscillation technique parameters

The inspiratory, expiratory, and whole-breath (R5) Rrs at 5 Hz of the study population were 3.73 ± 1.17 cmH2O/L/s, 4.09 ± 1.37 cmH2O/L/s, and 3.91 ± 1.22 cmH2O/L/s, respectively. Similarly, inspiratory, expiratory, and whole-breath (X5) Xrs at 5 Hz of the study population were −1.13 ± 0.69 cmH2O/Ls, −1.15 ± 0.63 cmH2O/L/s, and −1.12 ± 0.61 cmH2O/L/s, respectively. Both within-breath and whole-breath Rrs at 5 Hz of women <60 years of old were significantly higher as compared to men [Table 1]. The magnitude of within-breath and whole-breath Xrs at 5 Hz of women <60 years old were significantly more negative as compared to men (P < 0.001). In general, more than 60 years older adults had a higher magnitude of Zrs as compared to the corresponding gender and age <60 years, though the difference was statistically nonsignificant. The difference between inspiratory and expiratory Rrs at 5 Hz (ΔR5) of the study population was −0.36 ± 0.75 cmH2O/L/s, and it was statistically not different between men and women (−0.32 ± 0.65 cm H2O/L/s in men vs. −0.40 ± 0.84 cmH2O/L/s in women; P = 0.39). The difference between inspiratory and expiratory Xrs at 5 Hz (ΔX5) of the study population was −0.02 ± 0.64 cmH2O/L/s, and it was also statistically not different between men and women (−0.07 ± 0.61 cm H2O/L/s in men vs. 0.03 ± 0.67 cmH2O/L/s in women; P = 0.19). The difference of Rrs between 5 Hz and 19 Hz (R5–19), i.e., small airway resistance of the study population was 0.53 ± 0.50 cmH2O/L/s. Women had significantly higher R5–19 values as compared to men (0.65 ± 0.53 cmH2O/L/s in women vs. 0.39 ± 0.43 cmH2O/L/s in men; P = 0.000).
Table 1: The comparison of anthropometric parameters and respiratory impedance of study population according to gender in each age group

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Regression equations of respiratory impedance

The standing height and body weight of the study population showed a significant relationship with R5 and X5. Standing height had a significant negative association with Rrs and a positive association with Xrs. Pearson's correlation coefficient of standing height with Rrs and Xrs was − 0.46 (P = 0.000) and 0.26 (P = 0.000), respectively [Figure 2]. With an increase in body weight, Rrs at both 5 Hz and 19 Hz increases in both men and women. The magnitude of X5 in men increases with an increase in body weight, though X5 of women demonstrated no relationship with body weight. The contribution of aging on predicted Zrs values was negligible and observed in men only. The regression equations of Rrs and Xrs for men and women are presented in [Table 2].
Figure 2: The relationship of standing height with respiratory impedance. (a) Relationship of standing height with whole-breath Rrs at 5 Hz (R5). (b) Relationship of standing height and whole-breath Xrs at 5 Hz (X5)

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Table 2: Regression equations of within- and whole-breath respiratory impedance for men and women

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The predicted R5 and X5 using the present study regression equations for men and women were compared with predicted equations of Newbury et al. and Schulz et al. [Figure 3].[9],[10] The predicted Zrs were constructed for three different ages (25 years, 45 years, and 60 years) with different standing heights and body weight fixed at 65 kg. The predictive R5 of the Indian population was higher for all age groups, irrespective of gender. The predicted X5 by the present regression equations was also of higher magnitude as compared to the above studies for both the genders and in all ages.
Figure 3: Comparison of whole breath resistance (R5) and reactance (X5) predicted values at 5 Hz for men and women as a function of standing height at different ages and body weight fixed at 65 kg. The values are calculated by the present study equation (continuous line), median values by the equation of Schulz et al.[10] (dotted line), and equation by Newbury et al.[9] (dashed line). (a) Age 25 years: R5 and X5 for men in upper panel and for women in lower panel; (b) Age 45 years: R5 and X5 for men in upper panel and for women in lower panel; (c) Age 60 years: R5 and X5 for men in upper panel and for women in lower panel

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   Discussion Top


In the present study, the regression equations of within- and whole-breath respiratory impedance were derived from never-smoked healthy Indian adults. This study is first in publishing regression equations of respiratory impedance for Indian adults.

As compared to children, fewer studies attempted to develop the regression equations of Zrs for adults, especially within-breath. The within- and whole-breath Rrs and Xrs at 5 Hz of the present study population were very similar to observations by Paredi et al.[11] The mean whole-breath R5 and X5 values of Indian adults irrespective of gender were also matched with the values of ECLIPSE study population.[12]

The effect of gender on Zrs of adults had been reported in other ethnicities.[9],[10],[11],[12],[13] Australian women had significantly higher values of R5 and lower values of X5 as compared to men.[9] Schulz et al. observed significantly higher Rrs and lower Xrs in German women as compared to men in a population of age 45 years and more.[10] Higher Rrs at 4 Hz and lower Xrs at 4 Hz in Brazilian women were also reported by Ribeiro et al.[13] In agreement with all these studies, Indian women also had significantly higher magnitudes of R5 and lower magnitudes of X5 as compared to men. It is postulated that smaller lung volumes and smaller airway diameter are responsible for higher Rrs and lower Xrs in women.

The anthropometric parameters of adults influence the regression equations of Zrs, and the relative contribution of each parameter is variable across different ethnicities.[4] Complex regression models of Zrs with anthropometric parameters were attempted by Schulz et al., and they found that liner model was best fitted.[10] Newbury et al. found both age and standing height of adults were significant predictors of Zrs. Standing height negatively correlate with Rrs and positively correlate with Xrs, irrespective of genders.[9] Schulz et al. observed that both standing height and body weight of individuals were the main predictors of Zrs and body weight had more significant relevance in women than men.[10] However, the effect of age and weight on Rrs and Xrs of their population was variable across genders. Rrs of heathy Caucasians greater dependent on standing height in men and dependent on the body weight of both men and women.[14] In a population of 65 years and older, Guo et al. observed that the standing height of an individual was the best predictor of Zrs and the effect of both weight and age was negligible.[15] Therefore, except for standing height, other anthropometric parameters have a considerable variable contribution to regression equations of Zrs across populations. In close agreement with all earlier studies, standing height was the strongest independent predictor of Zrs in Indian adults, followed by body weight. Tramont et al. noticed that Xrs decreases with aging due to increased inhomogeneity of ventilation and aging had a negligible effect on Rrs.[16] In the present study, the effect of aging was observed on both Rrs and Xrs values of men only, though the effect was negligible.

Traditionally, the difference between Rrs at lower frequency, for example, R5 and higher frequency, for example, 20 Hz (R5–20) is known as frequency dependence of Rrs, i.e., fall in resistance with increase in oscillating frequency. The presence of a higher magnitude of frequency dependency of Rrs is an indicator of heterogeneous airflow obstruction. Different researchers adopted the difference between different frequencies to demonstrate the frequency dependence of Rrs. Guo et al. used the difference of Rrs between 4 and 16 Hz and 4 and 30 Hz.[15] On the other hand, to reduce the effect of harmonic distortion and frequency cross-talk, Resmon Pro employs the difference between Rrs at 5 Hz and 19 Hz (R5–19) to demonstrate frequency dependence of Rrs.[17] In concordance with other studies, the frequency dependence of Rrs was also observed in Indian adults. However, the magnitude of R5–19 in Indian adults was less as compared to R5–20 values observed by Crim et al.[12] Schulz et al. observed that R5–20 had a significant age dependency in their study population.[10] Whereas, age dependency of R5–19 in Indian adults was observed in men only. Both standing heights and body weight of Indian adults are significant predictors of R5–19, irrespective of gender.

The importance of within-breath analysis of respiratory impedance was highlighted by several investigators.[11],[18] The difference between inspiratory and expiratory X5 is known as Δ X5. The magnitude of Δ X5 is considered a marker of tidal expiratory flow limitation, i.e., collapsing of airways during the expiration of spontaneous breathing. The Δ X5 values in COPD are higher as compared to both healthy and bronchial asthma patients, and high Δ X5 is considered a hallmark of COPD.[11] The normal value of Δ X5 in the adult population has not studied much. In concordance with observations by Paredi et al., ΔX5 of Indian adults was also negligible.

The magnitude of difference between inspiratory and expiratory R5, i.e., ΔR5 in a healthy population has not been much investigated. Paredi et al. observed Δ R5 of healthy adults as −0.2 ± 0.1 cmH2O/L/s and higher Δ R5 in both bronchial asthma and COPD patients.[11] The Δ R5 of the present study population was of little higher magnitude as compared to healthy adults of the above-mentioned study.

Different researchers used different technologies such as impulse oscillometry system (IOS) and FOT to develop regression equations for respiratory impedance. It has been observed that IOS tends to provide bigger values as compared to FOT.[4] Zimmermann et al. compared the impedance measured by three commercial FOT devices, and observed measurements of Rrs were similar, but Xrs varies across the devices.[19] Kalchiem-Dekel et al. also observed that Zrs values at lower frequencies were independent of measuring device.[4] Therefore, there are possibilities that predictive values generated by different technologies may not be comparable with each other. Both Schulz et al. and Newbury et al. used IOS in their study. In general, predicted R5 and X5 values by the current study equations are higher magnitudes than those calculated using the equation of Newbury et al. and Schultz et al.[9],[10] The observed difference is either due to ethnicity or due to the use of different technology, i.e., IOS.

The limitation of the present study was that few individuals performed simultaneous spirometry to demonstrate normal spirometry. The numbers of adults more than 60 years were less, and thus, regression equations for more than 60 years must be interpreted cautiously. The signal of 5-11-19 Hz was used in the present study; therefore, two commonly used parameters of FOT, i.e., resonant frequency (Fres) and reactance area (AX) were not measured.


   Conclusions Top


The regression equations of respiratory impedance for Indian adults were developed for the first time. Indian women had a higher magnitude of both resistance and reactance as compared to men. The standing heights, followed by body weight of Indian adults, are significant determinants of Zrs. The regression equations developed by the present study will be worthwhile for clinical interpretation of FOT results of Indian adults and will encourage the clinicians to use of FOT in their clinical practice.

Acknowledgments

The authors like to thank to Dr. R R Tiwari, Director ICMR-NIREH, for his cooperation and constant encouragement.

Financial support and sponsorship

This project is supported by the intramural Research Grant from the Indian Council of Medical Research (New Delhi).

Conflicts of interest

There are no conflicts of interest.



 
   References Top

1.
Oostveen E, MacLeod D, Lorino H, Farré R, Hantos Z, Desager K, et al. The forced oscillation technique in clinical practice: Methodology, recommendations and future developments. Eur Respir J 2003;22:1026-41.  Back to cited text no. 1
    
2.
Dellacà RL, Duffy N, Pompilio PP, Aliverti A, Koulouris NG, Pedotti A, et al. Expiratory flow limitation detected by forced oscillation and negative expiratory pressure. Eur Respir J 2007;29:363-74.  Back to cited text no. 2
    
3.
Silva KK, Faria AC, Lopes AJ, Melo PL. Within-breath respiratory impedance and airway obstruction in patients with chronic obstructive pulmonary disease. Clinics (Sao Paulo) 2015;70:461-9.  Back to cited text no. 3
    
4.
Kalchiem-Dekel O, Hines SE. Forty years of reference values for respiratory system impedance in adults: 1977-2017. Respir Med 2018;136:37-47.  Back to cited text no. 4
    
5.
Jindal SK, Aggarwal AN, Gupta D, Agarwal R, Kumar R, Kaur T, et al. Indian study on epidemiology of asthma, respiratory symptoms and chronic bronchitis in adults (INSEARCH). Int J Tuberc Lung Dis 2012;16:1270-7.  Back to cited text no. 5
    
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Gobbi A, Milesi I, Govoni L, Pedotti A, Dellacà RL. A new telemedicine system for the home monitoring of lung function in patients with obstructive respiratory diseases. Int Conf eHealth Telemedicine Soc Med 2009:117-22. DOI: 10.1109/eTELEMED.2009.18.  Back to cited text no. 6
    
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Miller MR, Hankinson J, Brusasco V, Burgos F, Casaburi R, Coates A, et al. Standardisation of spirometry. Eur Respir J 2005;26:319-38.  Back to cited text no. 8
    
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Newbury W, Crockett A, Newbury J. A pilot study to evaluate Australian predictive equations for the impulse oscillometry system. Respirology 2008;13:1070-5.  Back to cited text no. 9
    
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Schulz H, Flexeder C, Behr J, Heier M, Holle R, Huber RM, et al. Reference values of impulse oscillometric lung function indices in adults of advanced age. PLoS One 2013;8:e63366.  Back to cited text no. 10
    
11.
Paredi P, Goldman M, Alamen A, Ausin P, Usmani OS, Pride NB, et al. Comparison of inspiratory and expiratory resistance and reactance in patients with asthma and chronic obstructive pulmonary disease. Thorax 2010;65:263-7.  Back to cited text no. 11
    
12.
Crim C, Celli B, Edwards LD, Wouters E, Coxson HO, Tal-Singer R, et al. Respiratory system impedance with impulse oscillometry in healthy and COPD subjects: ECLIPSE baseline results. Respir Med 2011;105:1069-78.  Back to cited text no. 12
    
13.
Ribeiro FCV, Lopes AJ, Melo PL. Reference values for respiratory impedance measured by the forced oscillation technique in adult men and women. Clin Respir J 2018;12:2126-35.  Back to cited text no. 13
    
14.
Oostveen E, Boda K, van der Grinten CP, James AL, Young S, Nieland H, et al. Respiratory impedance in healthy subjects: Baseline values and bronchodilator response. Eur Respir J 2013;42:1513-23.  Back to cited text no. 14
    
15.
Guo YF, Herrmann F, Michel JP, Janssens JP. Normal values for respiratory resistance using forced oscillation in subjects >:65 years old. Eur Respir J 2005;26:602-8.  Back to cited text no. 15
    
16.
Tramont CV, Faria AC, Lopes AJ, Jansen JM, Melo PL. Influence of the ageing process on the resistive and reactive properties of the respiratory system. Clinics (Sao Paulo) 2009;64:1065-73.  Back to cited text no. 16
    
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Suki B, Lutchen KR. Pseudorandom signals to estimate apparent transfer and coherence functions of nonlinear systems: Applications to respiratory mechanics. IEEE Trans Biomed Eng 1992;39:1142-51.  Back to cited text no. 17
    
18.
Ohishi J, Kurosawa H, Ogawa H, Irokawa T, Hida W, Kohzuki M. Application of impulse oscillometry for within-breath analysis in patients with chronic obstructive pulmonary disease: Pilot study. BMJ Open 2011;1:e000184.  Back to cited text no. 18
    
19.
Zimmermann SC, Watts JC, Bertolin A, Jetmalani K, King GG, Thamrin C. Discrepancy between in vivo and in vitro comparisons of forced oscillation devices. J Clin Monit Comput 2018;32:509-12.  Back to cited text no. 19
    


    Figures

  [Figure 1], [Figure 2], [Figure 3]
 
 
    Tables

  [Table 1], [Table 2]



 

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