Resistance Measured by Airflow Perturbation Compared with Standard Pulmonary Function Measures

doi:10.4236/ojrd.2013.32010

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Open Journal of Respiratory Diseases, 2013, 3, 63-67

http://dx.doi.org/10.4236/ojrd.2013.32010 Published Online May 2013 (http://www.scirp.org/journal/ojrd)

Resistance Measured by Airflow Perturbation Compared

with Standard Pulmonary Function Measures*

Tania Haque1, Jafar Vossoughi2, Arthur T. Johnson3, Wanda Bell-Farrell1,

Thomas Fitzgerald1, Steven M. Scharf1#

1University of Maryland, Baltimore, USA

2Engineering and Scientific Research Associates, Olney, USA

3Fischell Department of Bioengineering University of Maryland, College Park, USA

Email: #[email protected]

Received March 5, 2013; revised April 5, 2013; accepted April 13, 2013

which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

ABSTRACT

Background: Routine lung function testing requires expensive equipment, or requires maximum expiratory effort. The

airflow perturbation device (APD) is a light handheld device, allowing for serial measures of respiratory resistance

noninvasively and effortlessly. Methods: In a convenience sample of 398 patients undergoing pulmonary function test-

ing, we compared routine spirometric indices (forced expired volume in 1 second (FEV1), peak expiratory flow (PEF)),

and airways resistance (Raw-272 patients), to measures of respiratory resistance measured with the APD including in-

spiratory (IR), expiratory (ER) and averaged (AR) resistance. Results: Measures of lung function were significantly

correlated (p < 0.001). On regression analysis, between 7% - 17% of the variance (R2) for FEV1, PEF, and Raw was

explained by APD measurements. Approximately 2/3 of the variance in FEV1 was explained by PEF measurements.

Conclusions: APD measurements of lung function correlate with conventional measures. Future studies should be di-

rected at exploring the use of the APD device in serial measures of lung function in patients with lung disease.

Keywords: Airflow Perturbation Device; Pulmonary Function; Forced Expired Volume in 1 Second; Peak Expiratory

Flow; Airway Resistance

1. Introduction

Airway resistance is a commonly used measurement of

lung function in a variety of respiratory disorders. Resis-

tance measurement is also useful in evaluating respira-

tory effects of exposure to bronchoconstrictive or bron-

chodilatory drugs as well as to airborne pollutants.

Whole-body plethysmography is commonly used to

measure airways resistance [1]. This technique requires

coordinated breathing maneuvers coached by a skilled

technician and a large non-portable and expensive appa-

ratus. Another technique for measurement of pulmonary

resistance (airways resistance and lung tissue resistance)

is the technique of von Niergard and Wirz [2]. However,

this technique necessitates the subject swallowing an

uncomfortable esophageal balloon. Finally, forced oscil-

lation, originally designed to measure respiratory imped-

ance during tidal breathing [3] has been shown to be sen-

sitive to changes in airways resistance [4]. For this tech-

nique, sinusoidal oscillations of pressure are superim-

posed on tidal breathing. From the ratio of pressure

changes to flow changes and the phase angles between

them, impedance is calculated [4]. However, forced os-

cillation requires expensive equipment and is only suit-

able in the pulmonary function laboratory. In the clinical

setting, total respiratory resistance is usually assessed

indirectly using spirometric indices such as forced ex-

pired volume in one second (FEV1) or peak expiratory

flow (PEF), the latter often used at home. However, spi-

rometric techniques require forced exhalation, require

some patient training, and may be difficult or stressful

for some patients to perform. Thus, most techniques

for measurement of pulmonary resistance require either

skilled cooperation on the part of the subject and/or spe-

cialized expensive equipment found in pulmonary func-

tion laboratories and are not suitable for home measure-

ment.

The airflow perturbation device (APD—see Figure 1)

is a variant of the forced oscillation technique suitable for

use in settings outside the pulmonary function laboratory

*Funding: NIH NHLBI: 44HL078055.

#Corresponding author.

T. HAQUE ET AL.

Figure 1. Schematic diagram of the APD showing the Pneu-

motach to measure flow rate, the pressure transducer to

measure mouth pressure, and the rotating wheel to perturb

airflow.

[5-7]. This lightweight, handheld, noninvasive, portable

and fast device measures total respiratory resistance dur-

ing quiet tidal breathing, without the need for special

breathing maneuvers. The APD has been shown to

measure total respiratory resistance from the mouth to

the surface of the chest wall [6,7]; it thus includes air-

ways, lung tissue, and chest wall resistance components.

A segmented wheel rotating in the air pathway from the

mouth causes changes at 10 Hz in both airflow and mouth

pressure. When airflow diminishes, mouth pressure in-

creases and vice versa. From the ratio of the amplitudes

of pressure and flow perturbations, total respiratory re-

sistance can be calculated. The APD separates respira-

tory resistance during inhalation from that during exhala-

tion. This feature can be of importance for diagnosis of

particular respiratory pathologies—e.g. exercise-induced

paradoxical vocal fold motion that primarily affects the

inspiratory phase. Additionally, the APD is small and

portable, thus making it suitable for use away from the

health care facility (Figure 2).

The APD device and the principles behind it have been

described in detail elsewhere [5-9]. Coursey et al. [8]

showed that APD derived measurements of respiratory

resistance reflected changes in added resistances at least

as well as classic measurements of pulmonary resistance

using the esophageal balloon [2]. APD measured respi-

ratory resistance was not significantly different from

pulmonary resistance measured using the esophageal

balloon. In fact, with added external resistance, the dif-

ferences between APD and pulmonary resistance de-

creased. These authors also demonstrated that expiratory

isovolume pressure-flow curves could reliably be ob-

Figure 2. Subject using the hand held APD. This device was

connected to a laptop computer for data recording. How-

ever, this is not required for use. All values are displayed on

a screen in the field of vision.

tained with the APD technique [9].

The APD offers a number of potential advantages for

the frequent following of lung function in patients with

pulmonary disease. First, it requires no cumbersome

equipment. Second, it requires no complicated maneu-

vers like panting or forced expiration. Finally, it does not

require a forced expiration like FEV1 or PEF. Thus APD

measurement would seem to be ideal to use as an out of

hospital assessment of lung function.

The current study is designed to compare measure-

ments of respiratory resistance using the APD with com-

monly used indices of lung function, based on spirometry

or body plethysmography, in adults referred to the pul-

monary function laboratory for evaluation of lung func-

tion. We hypothesized that APD measurements of resis-

tance would be significantly correlated with standard

laboratory measures of lung function.

2. Methods

The protocol was approved by the University of Mary-

land Institutional Review Board. Inclusion criteria in-

cluded: age ≥ 18, and willingness and ability to sign in-

formed consent in the English language. Patients were

excluded if they appeared to have an unstable pulmonary

condition requiring referral to urgent care. A conven-

ience sample of 398 patients, aged 18 to 88, with a vari-

ety of pulmonary complaints, referred to the pulmonary

function laboratory for routine pulmonary function test-

ing by their providers was studied. All subjects under-

went spirometric testing. In 272, body plethysmography

was also performed allowing for measurements of lung

volume and airways resistance [10], and in 23 spirmetry

and APD measures were repeated following bronchodi-

T. HAQUE ET AL. 65

lator. Since the laboratory performed only those tests

requested by the referring provider, we could not add to

these numbers. Following measurements of lung function

as ordered by their provider, subjects were asked to qui-

etly breathe through the airflow perturbation device for

one minute in the sitting position. A nose clip was used

to obstruct nasal breathing. In some cases, APD measure-

ments were performed twice on the same day: following

spirometry before bronchodilator and following spirome-

try after bronchodilator.

Spirometry and body plethysmography were per-

formed using a SensorMedics Viasys system according

to the standards set out by the American Thoracic Soci-

ety/European Respiratory Society [11,12]. Spirometry

yielded values for FEV1, forced vital capacity (FVC) and

PEF. Body plethysmography yielded values for lung

volumes including functional residual capacity (FRC),

airways resistance (Raw), and specific airways conduc-

tance (sGaw = 1/Raw/FRC). Predicted values for spi-

rometry and body plethysmograph measurements were

generated using standard published equations [13,14].

For APD measurements, we used a lightweight hand-

held APD device (see Figure 2). Patients breathed nor-

mally for 1 minute through the APD while their nostrils

were blocked with a nose clip. No special breathing ma-

neuvers were required. APD measurements yielded val-

ues for inspiratory (IR) and expiratory resistance (ER) as

well as respiratory resistance averaged over the entire

respiratory cycle (AR).

Data Analysis

Data were collected and collated. Central tendency was

estimated as the mean and variability as standard devia-

tion as all data were normally distributed (Shapiro-Wilk

test). Differences between multiple means were assessed

using one-way analysis of variance for repeated measures.

If significance was found, we used post-hoc testing

(Neuman-Keuls) to determine the source of the signifi-

cance. Associations between variables were assessed us-

ing the Least-Squares technique and Pearson coefficients

were calculated. For most analyses, linear regression

yielded the greatest correlation. SigmaPlot 12.2 (Systat

software, Inc.—Chicago, Ill) was used to perform all sta-

tistical analyses. The null hypothesis was rejected at the

5% level.

3. Results

The sample was composed of 46% males and included

52% Caucasian, 44% African American and 3% from

other ethnicities. One-hundred and nineteen were former

or current smokers (mean smoking history = 26.2 ± 22.6

pack-years). Table 1 shows anthropomorphic data as

well as average prebronchodilator lung function meas-

Table 1. Anthropometric data and prebronchodilator meas-

ures of lung function.

Mean Std Deviation

Age 55.5 14.7

BMI (kg/m2) 31.7 19.5

IR (cm H2O/L/sec) 2.9 1.0

ER (cm H2O/L/sec) 3.1 1.2

AR (cm H2O/L/sec) 3.0 1.0

FEV1 (L) 2.2 0.9

FEV1 (% predicted) 77.7 24.3

FVC (L) 3.0 1.1

FVC (% predicted) 79.2 20.5

FEV1/FVC% 71.9 14.2

Raw (cm H2O/L/sec) 3.3 2.8

sGaw (L/sec/cm H2O/L) 0.1 0.1

FEF25 (L/sec) 1.9 1.2

FEF25 (% predicted) 62.5 35.3

PEF (L/sec) 6.1 4.2

PEF (% predicted) 71.9 14.1

BMI = body mass index; IR = inspiratory resistance from the APD; ER =

expiratory resistance form the APD; AR = resistance averaged over inspira-

tion and expiration from the APD; FEV1 = forced expired volume in 1 sec-

tion; FVC = forced vital capacity; FEV1/FVC% = the ratio of FEV1 to FVC

expressed as a percent; Raw = airway resistance; sGaw = specific conduc-

tance; FEF25 = forced expiratory flow at 25% of the vital capacity; PEF =

peak expiratory flow.

urements. There were no significant differences between

mean Raw and AR, IR or ER. A total of 137/398 patients

had “obstructive” physiology, defined as FEV1/FVC less

than 70%. A total of 126/398 patients had “restrictive”

physiology, defined as FEV1/FVC > 70% and FVC <

80% predicted.

Table 2 shows correlations between the different vari-

able measured. All correlations were significant (p <

0.001). Also shown are the values for R2. This is the

proportion of the variance in the dependent variable ex-

plained by the independent variable. For correlations

between APD measurements and either FEV1 or PEF, R2

(percent of explained variance) was in the 7% - 12%

range. For the correlation between APD measurements

and Raw (plethysmograph) R2 was 15% - 17%. Also

shown in Table 2 are correlations between the APD

measurements AR, IR and ER. As expected, these indi-

cated a tight correlation between the various APD meas-

ures of respiratory resistance, with the variability in one

measure accounting for 68% - 92% of the variance in the

other. Figure 3 shows the regression of AR on FEV1.

When we compared FEV1 (an expiratory maneuver), to

ER a similar regression was found (Figure 4). Correla-

tions between FEV1 and APD measurements and PEF

and APD measurements were in the expected direction,

T. HAQUE ET AL.

Table 2. Correlation coefficients between different meas-

ures of lung function were calculated and shown below.

PEF

(L/sec)

Raw

(cm

H2O/L/s)

(cm

H2O/L/s)

(cm

H2O/L/s)

(cm

H2O/L/s)

FEV1 (L) 0.82

R2 = 0.68

−0.44

R2 = 0.19

−0.31

R2 = 0.10

−0.35

R2 = 0.12

−0.35

R2 = 0.12

PEF

(L/sec)

−0.42

R2 = 0.18

−0.20

R2 = 0.08

−0.31

R2 = 0.09

−0.31

R2 = 0.07

Raw

(cm H2O/L/s)

0.39

R2 = 0.15

0.39

R2 = 0.153

0.41

R2 = 0.17

(cm H2O/L/s)

0.83

R2 = 0.69

0.95

R2 = 0.90

(cm H2O/L/s)

0.96

R2 = 0.92

For abbreviations see previous table. All correlations were significant to the

p < 0.001 level.

Figure 3. Regression of AR on FEV1; AR = 3.883 − (0.412 ×

FEV1); R2 = 0.124; p < 0.001.

Figure 4. Regression of ER on FEV1; ER = 4.085 − (0.465 ×

FEV1); R2= 0.123; p < 0.001.

i.e. as FEV1 or PEF increased (improved function), APD

resistance decreased. Figure 5 shows the regression of

AR on Raw (all measured prebronchodilator). While the

correlation was significant with similar correlation coef-

ficients as in Figures 3 and 4, it was clear that there was

Figure 5. Regression of AR on Raw; AR 1 = 2.515 + (0.157 ×

Raw); R2 = 0.167; p < 0.001.

a great degree of leverage in points towards the extremes

of each. The correlation between 2 commonly used indi-

ces of lung function, FEV1 and PEF (Table 2) showed

that some 2/3 of the variance of one was explained by the

other.

Finally, we compared bronchodilator associated changes

in indices of lung function between FEV1 and APD

measurements. The mean change in FEV1 with bron-

chodilator in the 28 patients in whom data were obtained

pre and post bronchodilator was relatively small: 0.10 ±

0.23 L. The correlations between changes in APD meas-

urements and FEV1 were not significant: For ER: ΔER =

0.0486 − (0.264 × ΔFEV1), R = 0.103, NS; For AR: ΔAR

= 0.00279 − (0.140 × ΔFEV 1), R = 0.063; For IR: ΔIR =

0.0257 − (0.416 × ΔFEV1), R = 0.178.

4. Discussion

We compared measurements commonly used to assess

lung function in the pulmonary function laboratory with

those obtained using the APD. While significant correla-

tions were found, only 7% - 17% of the variance in APD

measurements was explained by FEV1, PEF or Raw.

Further, there was no correlation between the change in

FEV1 and APD measurements with bronchodilator. In

the ensuing discussion we review these findings in the

light of the current available literature.

To our knowledge this is the largest group of subjects

in which changes in APD and other assessments of lung

function were compared. Further, the other studies cited

included normal healthy subjects. The current study in-

cludes unselected patients referred to the pulmonary

function lab for a variety of indications as determined by

their attending providers.

As shown by the figures and Table 2, the correlations

with FEV1, PEF, and Raw, although going in the ex-

pected directions, and statistically significant, are not

tight, with only 7% - 17% of the variance of one being

explained by the other. By contrast, the correlation be-

T. HAQUE ET AL.

tween FEV1 and PEF, that are forced expiratory maneu-

vers, was excellent, with some 2/3 of the variance in one

explained by the other.

It is important to bear in mind that the various meas-

ures of pulmonary function actually measure different

aspects of respiratory mechanics. FEV1 and PEF are cer-

tainly responsive to changes in airways resistance; how-

ever, they are also very dependent on patient effort. Raw,

measured in the body plethysmograph, is sensitive to

changes in flow-resistance of the airways, but excludes

lung and chest wall tissue resistance. The APD measures

total respiratory resistance, and includes a large compo-

nent of upper airways resistance (see [8]). The most

practical use for the APD would likely be to follow pa-

tients with lung disease serially at home given the ease of

use and low cost of this device. We had hoped that the

measurement of serial function before and after bron-

chodilator would simulate serial measurements for stan-

dard spirometry compared with APD. Unfortunately, few

patients had bronchodilator studies ordered, and the

overall change in FEV1 with bronchodilator was small

(approximately 100 cc). Finally, in a recent study [15],

the intrasubject variability of APD measurements was

assessed. It was found that the largest portion of the

variability of measurements was in fact due to changes

within the subject and not to changes within the APD,

strengthening our argument that the device would be

most useful for serial measurements in patients with lung

disease.

In sum, there are significant correlations between APD

derived measures of respiratory resistance and measures

derived from standard pulmonary function testing. The

variance explained was less than that between commonly

used measures of pulmonary function. Studies should be

directed at the evaluation of efficacy of serial measure-

ments over time in patients with respiratory disease.

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