Search

Respiratory resistance (Rrs) was measured by the forced oscillation technique at 10, 20 and 30 Hz in 54 healthy subjects. The sinusoidal pressure oscillations were applied around the head, rather than at the mouth, so as to minimize transmural pressure across extrathoracic airway walls and the corresponding artefact (Peslin et al., J Appl Physiol, 1985, 59, 1790-1795). The flow (V') and volume (V) dependences of Rrs during the respiratory cycle were analysed by least square regression according to: Rrs = K1 + 2.K2.[V']#- K3.V, where K1 and K2 are Rohrer's constants, and where K3 expresses the (negative) volume dependence of Rrs. The analysis was made separately on the inspiratory and expiratory phases. A good fit was usually found between the data and the model, with a root-mean-square error averaging 15% of the mean Rrs at 10 Hz. At all frequencies K2 and K3 were substantially and significantly larger, and K1 slightly lower during expiration than during inspiration. Rrs, K1 and K3 were minimum at 20 Hz, while K2 exhibited a strong positive frequency dependence. The decrease of Rrs from 10 to 20 Hz was entirely explained by the variations of its linear component, and its increase from 20 to 30 Hz was largely due to its flow dependent component. Both the phasic variations and the frequency dependence of the coefficients suggest that the model is purely descriptive and that coefficients K2 and K3 reflect a number of phenomena, including the variations in glottic aperture during the respiratory cycle.

Total respiratory input (Zin) and transfer (Ztr) mechanical impedances were measured from 4-30 Hz in 9 patients with severe chronic obstructive pulmonary disease (COPD) and in 12 healthy subjects. Zin was obtained by applying a pressure input around the head to minimize transmural pressure across extrathoracic airway walls, and Ztr was obtained with a pressure input at the chest. In agreement with previous studies total respiratory compliance and inertance were decreased in patients, while effective input resistance was increased and exhibited a negative frequency dependence. Effective transfer resistance (Re(Ztr)) was also increased at all frequencies, and, in some patients, the Re(Ztr)-frequency curve was sigmoid in shape, which was never seen in normals. When Ztr was analysed with a six-coefficient monoalveolar model featuring tissue properties, alveolar gas compliance, and airways properties, the model fitted the data less closely in patients than in normals and, in the former, provided unrealistic coefficients. Such was also the case with a bialveolar model. A better fit with more realistic values for the coefficients was obtained in selected patients with a model where central and peripheral (Rp) airway resistance were separated by a shunt representing airway wall compliance (Cb): Cb was found to range from 0.029-0.062 l.kPa-1 and Rp represented 44-81% of total airway resistance.

Total respiratory input (Zrs,in) and transfer (Zrs,tr) impedances were obtained from 4 to 30 Hz in 10 healthy males by simultaneously measuring mouth and chest flow while applying pseudo-random pressure variations at the mouth. Compared with Zrs,in, the real part of Zrs,tr was larger up to 10 Hz but exhibited a much stronger negative frequency dependence. The imaginary part was larger at all frequencies, with a resonant frequency (fn) at 6.0 +/- 0.8 Hz compared with 8.2 +/- 2.9 Hz for Zrs,in. The two impedances were analyzed with a model featuring airway resistance and inertance, alveolar gas compressibility, and tissue resistance, inertance, and compliance. A good fit was generally obtained but, in most cases, with a different partitioning of resistance between airway and tissue for Zrs,in and Zrs,tr. The data were also used to compute separately airway and tissue (Zt) impedances. In most subjects Zt could not be properly fitted with a simple resistance-inertance-compliance unit and was consistent with a slow (fn = 7.4 +/- 2.3 Hz) overdamped compartment in parallel with a fast (fn = 37.1 +/- 5.6 Hz) underdamped one.

Total respiratory input (Zin) and transfer (Ztr) impedances were obtained from 4 to 30 Hz in 10 healthy subjects breathing air and He-O2. Zin was measured by applying pressure oscillations around the head to minimize the upper airway shunt and Ztr by applying pressure oscillations around the chest. Ztr was analyzed with a six-coefficient model featuring airways resistance (Raw) and inertance (Iaw), alveolar gas compressibility, and tissue resistance, inertance, and compliance. Breathing He-O2 significantly decreased Raw (1.35 +/- 0.32 vs. 1.74 +/- 0.49 cmH2O.l-1.s in air, P less than 0.01) and Iaw (0.59 +/- 0.33 vs. 1.90 +/- 0.44 x 10(-2) cmH2O.l-1.s2), but, as expected, it did not change the tissue coefficients significantly. Airways impedance was also separately computed by combining Zin and Ztr data. This approach demonstrated similar variations in Raw and Iaw with the lighter gas mixture. With both analyses, however, the changes in Iaw were more than what was expected from the change in density. This indicates that factors other than gas inertance are included in Iaw and reveals the short-comings of the six-coefficient model to interpret impedance data.

When the whole body is exposed to sinusoidal variations of ambient pressure (delta Pam) at very low frequencies (f), the resulting compression and expansion of alveolar gas is almost entirely achieved by gas flow through the airways (Vaw). As a consequence thoracic gas volume (TGV) may be computed from the imaginary part (Im) of the delta Pam/Vaw relationship: TGV = PB/[2 pi f X Im(delta Pam/Vaw)], where PB is barometric minus alveolar water vapor pressure. The method was tested in 35 normal subjects and compared with body plethysmography. The subjects sat in a chamber connected to a large-stroke-volume reciprocating pump that brought about pressure swings of 40 cmH2O at 0.05 Hz. delta Pam and Vaw were digitally processed by fast Fourier transform to extract the low-frequency component from the much larger respiratory flow. Total lung capacities (TLC) obtained by ambient pressure changes and by plethylsmography were highly correlated (r = 0.959, p less than 0.001) and not significantly different (6.96 +/- 1.38 l vs. 6.99 +/- 1.38). TLC obtained by ambient pressure changes were not influenced by lowering the frequency to 0.03 Hz, adding an external resistance at the mouth, or increasing abdominal gas volume. We conclude that the method is practical and in agreement with body plethysmography in normal subjects.

Thoracic gas volume (TGV) and specific airway resistance (sRaw) are commonly measured using pressure type and flow type body plethysmographs. Within-subject variability of the data, defined as the coefficient of variation of eight to ten measurements during the same session, was assessed with the two kinds of instruments and compared in fifteen normal subjects. The reproducibility of data obtained several days apart was also compared. All measurements were made in a 480-l body chamber, which could be used in both the pressure and the flow mode. The signals were processed digitally using three different algorithms: 1) simple linear regression (LR); 2) linear regression with drift correction achieved by adding to, or subtracting from the plethysmographic signal a term proportional to time (LRC); 3) Fourier analysis (FFT). Within-subject variability of TGV was much larger with flow than with pressure plethysmography when the signals were processed by LR (14.5 +/- 7.5 vs 6.3 +/- 3.0%; p less than 0.001), but almost the same using LRC (6.7 +/- 3.2 vs 5.4 +/- 2.7%) and FFT (6.1 +/- 2.4 vs 5.0 +/- 2.4%). For sRaw, variabilities were larger and less influenced by methodological factors. Adequate digital processing may therefore largely remedy the inherently greater variability of TGV measurements with flow plethysmographs.

A new method for measuring total respiratory input impedance (Zrs), which ensures minimal motion of extrathoracic airway walls, was tested over frequencies of 4–30 Hz in 14 normal subjects and 10 patients with airway obstruction. It consists of applying pressure variations around the head, rather than at the mouth, so that transmural pressure across upper airway walls is equal to the small pressure drop across the pneumotachograph. Compared with reference Zrs values obtained by directly measuring airway wall motion with a head plethysmograph and correcting the data for it, the investigated method provided similar values for respiratory resistance at all frequencies (30 Hz, 3.67 +/- 2.24 cmH2O X 1(-1) X s compared with 3.55 +/- 2.00) but slightly overestimated respiratory reactance at the largest frequencies (30 Hz, 2.82 +/- 1.28 cmH2O X 1(-1) X s compared with 2.52 +/- 1.22, P less than 0.01). In contrast, when the data were not corrected for airway wall motion, resistance was largely underestimated, especially in patients (-48% at 30 Hz, P less than 0.001), and the reactance-frequency curve was shifted to the right. The investigated method is almost as accurate as the reference method, provides equally reproducible data, and is much simpler.

We investigated two methods of decreasing the error on plethysmographic determinations of thoracic gas volume (TGV) related to cheeks movements during panting maneuvers: lowering gas density in the airways with an 80% He-20% O2 mixture and computing TGV from the in-phase component of the plethysmographic signal (TGVr). The methods were tested by measuring how TGV estimates varied when panting frequency was raised from 0.8 to 2.5 Hz during the same occlusion. The measurements were performed in 6 normal subjects and 12 patients with chronic bronchitis with and without cheeks support and when the airway was connected to an external device simulating an increased cheeks compliance. A small negative frequency dependence of TGV (delta TGV/delta f = -1.2 +/- 0.8%/Hz with cheeks support), most probably unrelated to upper airway walls, was found in normal subjects. Delta TGV/delta f was positive and algebraically larger in patients than in normals, reaching 2.2 +/- 3.4%/Hz without cheeks support and 11.8 +/- 8.0%/Hz with the additional cheeks. The latter value was only 20% smaller when computed on the basis of TGVr, demonstrating the limited usefulness of the phase-based correction. In contrast, breathing He-O2 decreased delta TGV/delta f to approximately 50% of its air value (P less than 0.01) and appears as an effective way to diminish the error in obstructive patients.

Total respiratory impedance was obtained from 4 to 30 Hz in 39 healthy males and in 140 iron miners by studying the relationship between transrespiratory pressure and mouth flow when forced oscillations were applied to the respiratory system in two different ways: by varying pressure at the mouth (input impedance, Zin); by varying pressure around the chest (transfer impedance, Ztr). Zin was characterized by the slope (S) and intercept (R0) of the resistance-frequency curve, by the resonant frequency (fn), and by total respiratory inertance (I) and compliance (C) obtained from the reactance. Transfer resistance and reactance curves were respectively analysed with a two-parameter (m1, m3) and a three-parameter (m0, m2, m4) equation. Significant correlations were found between impedance indices, particularly between m1 and both R0 (r = 0.931; p less than 0.001) and m2 (r = 0.739; p less than 0.001), and also between impedance indices and maximal expiratory flows. Nonsmoking miners (n = 40), compared to control nonsmokers (n = 16), had slightly lower maximal flows at high lung volumes (p less than 0.05) and higher values of m1 (p less than 0.001), R0, S, m3 (p less than 0.01) and m2 (p less than 0.05). In contrast, miners who smoked (n = 46) mainly differed from miners who did not smoke by lower flows at middle and low lung volumes (p less than 0.01) and larger m0 (p less than 0.01), m2 and m4 (p less than 0.05).(ABSTRACT TRUNCATED AT 250 WORDS)