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Abstract 


Physiological dead space volume (VD) and dynamic hyperinflation (DH) are two different types of abnormal pulmonary physiology. Although they both involve lung volume, their combination has never been advocated, and thus their effect and implication are unclear. This study aimed (1) to combine VD and DH, and (2) investigate their relationship and clinical significance during exercise, as well as (3) identify a noninvasive variable to represent the VD fraction of tidal volume (VD/VT). Forty-six male subjects with chronic obstructive pulmonary disease (COPD) and 34 healthy male subjects matched for age and height were enrolled. Demographic data, lung function, and maximal exercise were investigated. End-expiratory lung volume (EELV) was measured for the control group and estimated for the study group using the formulae reported in our previous study. The VD/VT ratio was measured for the study group, and reference values of VD/VT were used for the control group. In the COPD group, the DHpeak/total lung capacity (TLC, DHpeak%) was 7% and the EELVpeak% was 70%. After adding the VDpeak% (8%), the VDDHpeak% was 15% and the VDEELVpeak% was 78%. Both were higher than those of the healthy controls. In the COPD group, the VDDHpeak% and VDEELVpeak% were more correlated with dyspnea score and exercise capacity than that of the DHpeak% and EELV%, and had a similar strength of correlation with minute ventilation. The VTpeak/TLC (VTpeak%), an inverse marker of DH, was inversely correlated with VD/VT (R2 ≈ 0.50). Therefore, we recommend that VD should be added to DH and EELV, as they are physiologically meaningful and VTpeak% represents not only DH but also dead space ventilation. To obtain VD, the VD/VT must be measured. Because obtaining VD/VT requires invasive arterial blood gases, further studies on noninvasive predicting VD/VT is warranted.

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Logo of jclinmedLink to Publisher's site
J Clin Med. 2020 Apr; 9(4): 1127.
Published online 2020 Apr 15. https://doi.org/10.3390/jcm9041127
PMCID: PMC7231163
PMID: 32326507

Combining Dynamic Hyperinflation with Dead Space Volume during Maximal Exercise in Patients with Chronic Obstructive Pulmonary Disease

Abstract

Physiological dead space volume (VD) and dynamic hyperinflation (DH) are two different types of abnormal pulmonary physiology. Although they both involve lung volume, their combination has never been advocated, and thus their effect and implication are unclear. This study aimed (1) to combine VD and DH, and (2) investigate their relationship and clinical significance during exercise, as well as (3) identify a noninvasive variable to represent the VD fraction of tidal volume (VD/VT). Forty-six male subjects with chronic obstructive pulmonary disease (COPD) and 34 healthy male subjects matched for age and height were enrolled. Demographic data, lung function, and maximal exercise were investigated. End-expiratory lung volume (EELV) was measured for the control group and estimated for the study group using the formulae reported in our previous study. The VD/VT ratio was measured for the study group, and reference values of VD/VT were used for the control group. In the COPD group, the DHpeak/total lung capacity (TLC, DHpeak%) was 7% and the EELVpeak% was 70%. After adding the VDpeak% (8%), the VDDHpeak% was 15% and the VDEELVpeak% was 78%. Both were higher than those of the healthy controls. In the COPD group, the VDDHpeak% and VDEELVpeak% were more correlated with dyspnea score and exercise capacity than that of the DHpeak% and EELV%, and had a similar strength of correlation with minute ventilation. The VTpeak/TLC (VTpeak%), an inverse marker of DH, was inversely correlated with VD/VT (R2 ≈ 0.50). Therefore, we recommend that VD should be added to DH and EELV, as they are physiologically meaningful and VTpeak% represents not only DH but also dead space ventilation. To obtain VD, the VD/VT must be measured. Because obtaining VD/VT requires invasive arterial blood gases, further studies on noninvasive predicting VD/VT is warranted.

Keywords: incremental exercise test, plethysmography, diffusing capacity, air trapping, tidal volume and total lung capacity ratio, end-expiratory lung volume

1. Introduction

In the alveolar dead space (VD) of the three component (Riley) model [1], if alveolar VD exists, residual volume is expected to increase, potentially causing air trapping and hyperinflation of the lung. However, the physiological VD refers to ventilation not involved in gas exchange and involved in unperfused or underperfused alveoli [2] and includes anatomical and alveolar VDs [1]. Acute dynamic hyperinflation (DH) refers to a temporary increase in operating lung volume above the resting value, i.e., end-expiratory lung volume at peak exercise (EELVpeak) [3,4,5,6] minus resting EELV (EELVrest) [7]. Because the definitions of alveolar VD and DH are different, physiological VD would not cause DH, and thus their relationship is unclear.

The physiological VD/tidal volume ratio (VD/VT) can be calculated using the Bohr-Enghoff equation [2]. Therefore, VD can be considered to be a part of VT, and anatomical VD can be assumed to occur at the beginning of VT. Accordingly, as EELV is immediately followed by tidal breathing, beginning VD not included in EELV should be added.

In patients with chronic obstructive pulmonary disease (COPD), the VD/VT is often highly increased at rest and usually mildly decreased during exercise as compared with normal subjects. This phenomenon has been hypothesized to be due to a small increase in VD and a small expansion in VT, as VT is constrained by DH. VT “floats” above DH and is concomitantly limited by the ceiling of total lung capacity (TLC) and causes reductions in inspiratory reserve volume and O’Donnell threshold [8]. This is in contrast to healthy subjects, in whom a small change in VD and a large increase in VT are usually noted.

Although the definition and mechanism of VD and DH are quite different, both are volumes; DH, i.e., EELVpeak minus EELVrest has been reported to be correlated with the VD/VT ratio [3,9,10] (see the Appendix A Table A1), and EELVpeak has been shown to be inversely related to VTpeak/TLC (VTpeak%) [11]. Hence, the aims of this study were as follows: (1) to combine VD with DH; (2) to investigate the relationship between DH and VD; (3) to investigate the relationship between VDDH and dyspnea, exercise capacity, and ventilation capability; and (4) to investigate the relationship between VD/VTpeak and VTpeak% during maximal exercise in order to find a surrogate for VD/VTpeak, which is an invasive variable. This study could help clinicians better understand the relative positions of EELV, DH, VD, and VT in TLC, and show that VD and DH together are unfavorable lung volumes during exercise [9,10]. Using the easily calculated VTpeak% during exercise, testing could possibly reflect the invasively measured VD/VTpeak, and thus clinicians could use the VTpeak% as an indicator of DH and also VD/VTpeak. To the best of our knowledge, this is the first study to integrate the concept of dead space ventilation and DH during exercise.

2. Methods

2.1. Study Design

In this observational cross-sectional study, we analyzed lung function data and cardiopulmonary exercise with inspiratory capacity maneuver data from subjects with COPD and healthy controls at the Chung Shan Medical university hospital. The relationships between VTpeak% and VD/VT were investigated in the subjects with COPD. VD, VT, and EELV as % of TLC were illustrated using percentages. Signed informed consent was obtained from each participant. The local Institutional Review Board of the institution (CS16174) approved this study, which was conducted in compliance with the Declaration of Helsinki.

2.2. Subjects

Subjects aged ≥40 years without any chronic diseases including uncontrolled diabetes mellitus, uncontrolled hypertension, anemia (hemoglobin <13 g/dL), and no acute illnesses in the recent period of 1 month were enrolled. Anthropometric measurements, leisure/sports activities, and cigarette smoking were recorded. Subjects with a body mass index ≤18 kg/m2 or ≥32 kg/m2 or with laboratory findings of cardiovascular, hematological, metabolic, or neuromuscular diseases were excluded. All of the participants performed lung function and cardiopulmonary exercise tests (CPET). Subjects who did not have sufficient motivation to perform CPET were also excluded.

2.2.1. Study Group

Male adult subjects who underwent spirometry, plethysmography, and diffusing capacity were enrolled if their forced expired volume in one second (FEV1)/forced expired capacity (FVC) was <0.7 [12]. The diagnosis of COPD was made according to the global initiative for chronic obstructive lung disease (GOLD) criteria [12]. As few female subjects met the criteria of COPD, they were not included in this study.

2.2.2. Control Group

A group of healthy subjects was recruited among the hospital staff and from the local community through personal contacts. Healthy male subjects reported no chronic diseases.

2.3. Measurements

2.3.1. Functional Daily Activity

The oxygen cost diagram (OCD) was used to evaluate the participants’ functional activity. The participants were asked to indicate a point on an OCD, a 100 mm long vertical line with everyday activities listed alongside the line, above which breathlessness limited them [13]. The distance from zero was measured and scored.

2.3.2. Pulmonary Function Testing

Cigarette smoking, drinking coffee, tea, or alcohol, and taking medications were not permitted 24 h before any test. Bronchodilators were not administered within 3 h for short-acting beta agonists and 12 h for long-acting beta agonists before the tests [14,15]. FEV1, TLC, residual volume (RV), and diffusing capacity for carbon monoxide (DLCO) were measured using spirometry, body plethysmography, and the single-breath technique, respectively, in accordance with the currently recommended standards [16,17,18]. All of the spirometry data were obtained before and after inhaling a standard dose of fenoterol HCl. Post-dose measurements were performed 15 min after inhalation. Static lung volume data and DLCO data were obtained before inhaling fenoterol. Simple volume calibration was conducted and accuracy checks for body plethysmograph mouth flow and pressure and box pressure were performed as reported previously [14,15].

2.3.3. Cardiopulmonary Exercise Testing (CPET)

Each subject completed an incremental exercise test using a cycle ergometer to the limit of the symptom. Work rate was selected at a rate of 5–20 W/min based on a derived protocol formula according to the oxygen-cost diagram scores [19]. Oxygen uptake (VO2) (mL/min), CO2 output (VCO2) (mL/min), and minute ventilation (VE) were continuously measured. VO2peak was symptom-limited peak VO2, because VO2max, which was the plateau of VO2, was likely not attained in the participants with COPD. The ratio of compartment of TLC and TLC was remarked as the % of TLC such as EELV%, DH%, VD%, and VT%. A dyspnea score was obtained using the Borg scale by asking the patients about their dyspnea levels while they were performing the ramp-pattern exercise at the end of each minute and at peak exercise.

2.3.4. Dynamic Inspiratory Capacity (IC) Measurement

The techniques used for performing and accepting IC measurements of our previous study [11] were modified from a previous report [7]. Dynamic IC was measured at the end of a steady-state resting baseline, near the middle of loaded exercise (supposed to be near anaerobic threshold, AT), and near peak exercise. Dynamic IC near AT was measured approximately 5–6 min after the start of loaded exercise. EELV was calculated as TLC minus dynamic IC [5,6,20,21]. DH referred to end-expiratory lung volume at AT or peak exercise (EELVAT or peak) minus resting EELV (EELVrest). In this study, EELV was estimated for subjects with COPD using the formulae from the data of our previous report [11]. EELVrest% = 0.7235 − 1.0053 × VTrest%; EELVAT% = 0.9877 − 2.0132 × VT AT%; EELVpeak% = 0.9491 − 1.35178 × VTpeak%; O’Donnell threshold (OT) = TLC – EELV − VTpeak (see O’Donnell threshold in Reference [22]).

2.3.5. VD/VT Calculation

Brachial artery blood samples were drawn via an arterial catheter connected to a pressure transducer within the last 15 s of each minute after the start of exercise to the peak of exercise [23]. At rest, near the anaerobic threshold, and at the peak of exercise, the physiological VD/VT was calculated using a standard formula as follows [24]: VD/VT = (PaCO2 − PĒCO2)/PaCO2 − VDm/(VT − VDm), where PĒCO2 = VCO2/VE × (PB − 47 mmHg) and PB is barometric pressure measured daily and VDm is breathing valve dead space. Hemoglobin and biochemistry data were provided. In normal subjects, mean values of VD/VT are 0.30 ± 0.08 at rest, 0.20 ± 0.07 at AT, and 0.19 ± 0.07 at peak [2].

2.4. Statistical Analysis

Data were summarized as mean ± standard deviation. The sample size was estimated to be at least 17 for each group when the population mean difference in VD/VT was 0.1 with a standard deviation for the normal and COPD groups of 0.1 and with a significance level of 0.05 and a power of 0.8. The unpaired t-test was used to compare the means between two groups. The paired t-test was used to compare two related means between two different time points with Bonferroni correction. Pearson’s correlation coefficients were further used when appropriate for quantifying the pairwise relationships among the interested variables. All statistical analyses were performed using SAS statistical software 9.4 (SAS Institute Inc., Cary, NC, USA). Statistical significance was set at p < 0.05 and p < 0.017 for Bonferroni correction.

3. Results

A total of 81 male subjects were enrolled, including 46 subjects (mean age 65.2 ± 5.8 years) with COPD after excluding one subject due to poor motivation, and 34 healthy subjects matched for age and height (mean age 62.2 ± 9.2 years) (Table 1 and Figure 1). Most of the COPD subjects had GOLD stages II and III with hyperinflation and air trapping, normocapnia, and borderline hypoxemia at rest and could perform daily brisk walking on the level. Compared to the healthy controls during exercise, most of the COPD subjects had mildly impaired exercise capacity due to ventilatory limitation with poor lung expansion, significant oxyhemoglobin desaturation, and exercise hyperventilation (Table 2).

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Flow diagram. A total of 81 participants with chronic obstructive pulmonary disease and healthy controls were screened.

Table 1

Demographics and lung function in 80 male subjects with 46 subjects of chronic obstructive pulmonary disease (COPD) and 34 healthy subjects.

COPDNormal Controls
MeanSDMeanSD p
Age, years65.25.862.29.20.10
Height, cm165.06.4167.05.30.14
Weight, kg60.411.269.28.90.0002
Body mass index, kg/m222.13.524.82.70.0003
Cigarette smoke, pack[center dot]year42.319.24.717.4<0.0001
Oxygen cost diagram, cm7.01.48.31.0<0.0001
TLC% predicted, %135219711<0.0001
RV% predicted, %2005510117<0.0001
RV/TLC0.580.090.390.06<0.0001
IC% predicted, %922799170.15
DLCO% predicted, %692210616<0.0001
FVC% predicted, %812110113<0.0001
FEV1% predicted, %501910313<0.0001
GOLD, I, II, III, IV, n3, 18, 19, 6 NA NA
FEV1/FVC0.490.130.930.28<0.0001
Hemoglobin, g/dL14.81.514.61.20.78
Creatinine, mg/dL1.10.21.00.30.25
Na+, meq/L140.52.4138.42.20.73
K+, meq/L4.30.54.10.40.52
Albumin, mg/dL4.20.4NANANA
pH7.400.03NANANA
PaCO2, mmHg40.66.4NANANA
PaO2, mmHg79.310.1NANANA
SPO2, %95.32.697.21.2<0.0001

TLC: total lung capacity, RV: residual volume, IC: inspiratory capacity, DLCO: diffusing capacity for carbon monoxide, FVC: forced vital capacity, FEV1: forced expired volume in one second., GOLD: global initiative for chronic obstructive lung disease, SPO2: oxyhemoglobin saturation measured with pulse oximetry. NA: not available or not applicable.

Table 2

Cardiopulmonary exercise test at peak exercise in male subjects with chronic obstructive pulmonary disease (COPD) (n = 46) and male healthy subjects (n = 34).

COPDNormal Controls p
MeanSDMeanSD
Work rate, watts91.842.9146.634.7<0.0001
% predicted6930115.922.9<0.0001
Oxygen uptake (VO2), mL/min10733551708402<0.0001
% predicted69.320.990.719.4<0.0001
Anaerobic threshold, mL/min4891371018302<0.0001
%VO2max predicted, %31.18.053.011.8<0.0001
Respiratory exchange ratio1.050.101.160.140.0003
Cardiac frequency, b/min13320149170.0002
% predicted max, %81.312.094.79.6<0.0001
Oxygen pulse, mL/min8.12.411.52.5<0.0001
% predicted85.323.596.722.90.03
Minute ventilation VE/VO2nadir36.98.028.23.9<0.0001
SPO2,%91.05.896.81.2<0.0001
VE, L/min38.612.370.418.0<0.0001
VE/MVV1.160.360.630.15<0.0001
Breathing frequency, breath/min32.65.936.69.30.03
Tidal volume (VT), L1.190.351.960.42<0.0001
VT/total lung capacity (TLC)0.190.050.320.05<0.0001
Dead space volume (VD)/VT0.430.100.19 *0.07NA
pH7.320.04NA NA
PaCO2, mmHg46.17.8NA NA
PaO2, mmHg71.016.7NA NA

Oxygen pulse = VO2/cardiac frequency; oxyhemoglobin saturation measured with pulse oximetry—SPO2; maximum voluntary ventilation—MVV; * from Reference [2]. NA: not applicable or not available.

3.1. The % of TLC: EELV%, DH%, VD%, VT%, VDDH%, VDEELV%, and VTEELV% (or End-Inspiratory Lung Volume, EILV)

In the COPD group, EELVrest% was 63% ± 2% and EELVpeak was 70% ± 7% as compared with 48% ± 13% and 46% ± 13% in the healthy group (Figure 2, group comparisons, both p < 0.0001). Hence, DHpeak% was 7% ± 7% as compared with 1% ± 10% in the healthy group (p = 0.03). In the COPD group, VDrest% was 5% ± 1% and VDpeak% was 8% ± 2% as compared with 4% ± 2% and 6% ± 1% in the healthy group (Figure 2, group comparisons: p < 0.01 and p < 0.0001). In the COPD group, DHpeak% was similar to VDpeak% at peak exercise (7% ± 7% vs. 8% ± 2%, p = 0.61).

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The % of total lung capacity (TLC, upward triangles) at rest, anaerobic threshold (AT) and peak exercise. Left panel COPD group and right panel normal controls. Open circles, end-expiratory lung volume (EELV); solid circles, dead space volume (VD) plus EELV; down triangles, tidal volume (VT) plus EELV (i.e., end-inspiratory lung volume, EILV); vertical bars, standard error of estimate; OT, O’Donnell threshold; DH, dynamic hyperinflation indicating EELV at AT or peak exercise minus EELV at rest; dashed line, EELV at rest. Comparisons of each compartment between COPD patients and normal controls at rest, AT and peak exercise, respectively, all p < 0.0001 except VTEELV at rest, p < 0.01 and VTEELV at peak exercise, p < 0.001. In COPD patients, comparisons of each compartments of TLC between two time points, all p < 0.0001 except EELV at AT versus EELV at peak exercise, p < 0.001 and VDEELV at AT versus VDEELV at peak exercise, p = 0.046, which was insignificant.

After combining VD with DH (VDDH%), VDDHrest% was 5% ± 1% and VDDHpeak% was 15% ± 5% in the COPD group as compared with 4% ± 2% and 7% ± 10% in the healthy group (group comparisons, both p < 0.01). After combining VD with EELV (VDEELV%), VDEELVrest% was 68% ± 1% and VDEELVpeak% was 78% ± 6% in the COPD group as compared with 52% ± 13% and 52% ± 13% in the healthy group (group comparisons, both p < 0.0001). After combining VT with EELV (VTEELV% or EILV%), VTEELVrest% was 72% ± 0% and VTEELVpeak% was 88% ± 2% in the COPD group as compared with 62% ± 13% and 78% ± 14% in the healthy group (group comparisons, p < 0.01 and p < 0.001, respectively).

3.2. Relationships among the Compartments of TLC

VDpeak% was moderately positively correlated with VTpeak% (Table 3, r = 0.66, p <0.0001) and moderately negatively correlated with the other compartments at peak exercise (r = −0.47 to −0.68, p <0.01 to <0.0001).

Table 3

Relationships among the compartments of total lung capacity (TLC) and correlations of seven components of total lung capacity (TLC) with oxygen uptake (VO2), minute ventilation (VE), and dyspnea at peak exercise in 46 patients with COPD.

PeakVD%VO2VEΔBorg/ΔVO2
EELV%−0.67 −0.62 −0.75 0.66
DH%−0.61 −0.69 −0.78 0.72
VD%10.26 *0.46 **−0.19
VT%0.66 0.62 0.76 −0.67
VDDH%−0.68 −0.74 −0.74 0.78
VDEELV%−0.47 **−0.74 −0.74 0.78
VTEELV%−0.68 −0.60 −0.71 0.63

%: variable divided by TLC, EELV: end-expiratory lung volume, DH: dynamic hyperinflation indicating EELV at peak exercise subtracting resting EELV, VDDH: combing dead space (VD) and DH, VT: tidal volume, Δ: change. * 0.05 > p ≤ 0.1, ** p ≤ 0.01, p ≤ 0.0001.

3.3. Relationships between the % of TLC and Oxygen Uptake, Minute Ventilation, and Dyspnea

In the % of TLC, VDEELVpeak% and VDDHpeak% showed the best correlations with ΔBorg/ΔVCO2 and, and a similar strength of correlation with VEpeak (Table 3). The higher the VDDHpeak% and VDEELVpeak%, the higher the dyspnea score and the lower the VO2peak% and VEpeak.

3.4. VTpeak% versus VD/VTpeak

In the COPD group, VTrest% was 9% ± 2% and VTpeak% was 18% ± 5% as compared with 13% ± 7% and 32% ± 54% in the healthy group (Figure 2, group comparisons p < 0.01 and p < 0.0001). In the COPD group, there was a negatively significant relationship between VT% and VD/VT at rest, anaerobic threshold, and peak exercise, and this was stronger as the exercise intensity increased (see the Appendix A Table A2, r = −0.34 to −0.64, p = 0.02 to p < 0.0001). When pooling the data of these two variables at the three time points together, the relationship was much closer (r = −0.72, p < 0.0001).

4. Discussion

There are four main findings in this study. First, VD and DH (VDDH) and VD and EELV (VDEELV) could be combined. Secondly, we found that in the patients with COPD, VD and DH were similar in size, and that VDEELVrest accounted for 68% of the TLC and VDEELVpeak accounted for up to 78%. Third, compared to DHpeak% and EELVpeak%, VDDHpeak% and VDEELVpeak% were more closely related to dyspnea and exercise capacity and had a similar power in relation to ventilation capability. Lastly, VTpeak%, a recently reported marker of DHpeak [11], was moderately negatively correlated with VD/VTpeak. To the best of our knowledge, these findings have not previously been published.

4.1. The % of TLC

The importance of EELVpeak% has been reported when the EELVpeak is ≥75% of TLC, a threshold value which can maximize the sensitivity and specificity of detecting ≤5.5 mL/heartbeat change in oxygen pulse (ΔO2P) and ≤10,000 oxygen uptake efficiency slope (OUES) during exercise [25], where ΔO2P and OUES are markers of cardiovascular function. In addition to EELVpeak% >75% [25], the reciprocal ICpeak/TLC <25% [26] has also been associated with lower O2P and exercise capacity in patients with severe COPD. ICpeak/TLC <23% has also been associated with lower O2P and exercise capacity in patients with severe COPD [27]. Although OUES was not measured in this study, our previous study reported that ICpeak/TLC was significantly correlated with O2P and ΔO2P (r = 0.35–0.36, both p < 0.05) [28]. These results support an interaction between hyperinflation and decreased cardiac function that can contribute to exercise limitation in these patients. A greater amount of trapped gas in the lung increases the intrinsic positive end-expiratory pressure, and this compresses the heart and impedes venous return causing further heart impairment [25,26]. It has recently been reported that this compression can occur even at rest [29].

DH has been shown to increase with exercise in patients with COPD [3,4,5,6,9,10,20,21,22], and thus EELV caused failure of VT to expand, as in the healthy subjects in this study (0.6 ± 0.31 L versus 1.12 ± 0.57 L, p < 0.0001). A high level of VDEELV “buoyed” the expandable basic lung volume above its position, meaning that VT had limited room to expand downwards so that it could not help but invade upwards to the OT or near its limit (Figure 2). In COPD, decreased OT [3,22] and increased DH have been reported to be possible causes of exercise limitation [30], although some studies have questioned whether DH occurs in all COPD patients [31,32,33]. These previous studies have measured DHpeak but not included VDpeak. In this study, VDDHpeak% and VDEELVpeak% were slightly better than DHpeak% and EELVpeak% with regards to the correlation with ΔBorg/ΔVO2 and VO2peak% and had a similar power with regards to the correlation with VEpeak (Table 3). Therefore, it could be reasonable to combine VDpeak with DHpeak and to combine VDpeak with EELVpeak. In this study, VDEELVpeak%, an unfavorable lung volume, was elevated to as high as 78% ± 6% of TLC.

In the patients with COPD in this study, although VDpeak% was small as compared with EELVpeak% but similar to DH peak% in size, VDDH peak% accounted for 15% of TLC. The majority of the increase in physiological VD must have come from alveolar VD, as the increase in anatomical VD was estimated to be only 12 mL and 20 mL in the COPD and control groups, respectively, based on the estimation that anatomical VD would increase 20 mL per liter increase in EELV [1]. Hence, the remaining increase in physiological VD must have come from alveolar VD, which is strongly influenced by lung pathology but less influenced by other factors such as age, sex, body size (1 mL of physiological dead space per pound of weight reported by Radford), posture, low cardiac output, pulmonary emboli, and posture [1].

VD% and EELV% were moderately negatively correlated (Table 3). This is because VD% and VT% were moderately positively correlated and VT% and EELV% were highly negatively correlated (r = −0.83, p < 0.0001) [11]. VD% was positively correlated with VT% because VD is calculated by VD/VT multiplied by VT. Hence, the larger the VT, the larger the VD, and the smaller the EELV. It is clear that VD is different from EELV and DH in the direction of correlation, that these volumes can be combined, and that the combinations are more related to exercise capacity and exertional dyspnea sensation, although VD is small. Interestingly, VD% alone was poorly related to exercise tolerance and dyspnea. However, the relationships between DH% and EELV% versus exercise tolerance and dyspnea were slightly improved after adding VD% (Table 3).

4.2. VT% versus VD/VT

VD/VT has been reported to be the most consistent gas exchange abnormality in smokers with only mild abnormalities in spirometry [3]. However, invasive methods to obtain arterial blood gases are needed to measure VD/VT. In this study, VT%, an inverse marker of DH [11], was inversely correlated with VD/VT (R2 ≈ 0.50) (see the Appendix A Table A2). However, Mahut et al. reported that VD/VTpeak was only mildly correlated to DH (r = −0.45, p = 0.004) [10], where DH was represented by ICpeak% predicted [10]. This difference in correlation between DH and VD/VT in these two studies could be due to the different criteria used for DH, i.e., ICpeak% predicted versus VT%. Predicted IC data were obtained from the general population, whereas VT% was directly measured in the participants. In addition, Mahut et al. reported that the alveolar volume (VA)/TLC ratio was significantly correlated with VD/VTrest but much less significantly correlated with VD/VTpeak (see the Appendix A Table A1) [10]. VA is usually measured using the single breath helium dilution method at rest and is equal to TLC − VD [34]. Therefore, VA would underestimate TLC in subjects with poorly communicating airways or disequilibrium of ventilation. VA/TLC measured at rest cannot reflect DHpeak, so that it was poorly correlated with VD/VTpeak. Moreover, in this study, the relationship between VT% and VD/VT was strongest when data at rest, anaerobic threshold, and peak exercise were pooled (see the Appendix A Table A2, r = −0.72, p < 0.0001). The mechanism underpinning the stronger relationship between VTpeak% and VD/VTpeak with increasing exercise intensity could be due to the common factor VTpeak being highly constrained at peak exercise. The stronger relationship between VT% and VD/VT after pooling different stages of exercise is comparable to a previous study in which VE/VCO2 was used instead of VT% in healthy subjects and patients with COPD [3].

Nevertheless, Paoletti et al. reported that VTpeak/FEV1 > 1 (or VTpeak/IC = 0.96 ± 0.05), emphysema, the slope of VE/VCO2, and PETCO2peak values were colinear [35] (Figure 3). In their study, the patients with COPD had high RV% predicted and high emphysema score measured with high resolution computed tomography (HRCT). They hypothesized that VTpeak/FEV1 > 1 or elevated VTpeak/IC was due to DH occurring at peak exercise in patients with severe emphysema, which is comparable with our study and another study using VTpeak/SVC to assess the severity of emphysema evaluated with HRCT [36] (Figure 3). However, it has been reported that the change in VD/VT from rest to peak exercise was not related to the severity of emphysema [35]. In the current study, VTpeak/FEV1 > 1 and VTpeak/SVC were correlated with VTpeak%, respectively (Figure 3, r = −0.36 and 0.66, p = 0.001, p < 0.0001), however neither were correlated with VD/VTpeak. Nevertheless, VTpeak% was correlated with VD/VTpeak (r = −0.64, p < 0.0001), suggesting that VTpeak% could be more powerful than VTpeak/FEV1 and VTpeak/SVC (Figure 3).

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Relationships among dynamic hyperinflation (DH) variables and relationships between DH variables and dead space fraction (VD/VT) in patients with chronic obstructive pulmonary disease. Black bolded boxes, from this study; blue boxes, from References [35,36]. Solid lines, significantly correlated; dashed lines, not significantly correlated. Black lines, from this study; blue lines, from reference [35]; green line, from reference [36]. VT%, tidal volume and total lung capacity (TLC) ratio; EELV%, end-expiratory lung volume and TLC ratio; VT/SVC, VT and slow vital capacity ratio; VT/FEV1, VT and forced expired volume in one second ratio; HRCT, high resolution computed tomography; RV%, residual volume predicted %; Δ VE/Δ VCO2, slope of minute ventilation and CO2 output; PETCO2, end-tidal CO2 pressure.

4.3. Clinical Implications of VDDHpeak% and VDEELVpeak%, and VTpeak%

Since DH may not occur in all COPD patients [31,32,33], as VDDHpeak% and VDEELVpeak% are substantially larger and slightly more related to dyspnea [31] and exercise capacity than DH% and EELV%, and as VTpeak% can be obtained easily and noninvasively, these three markers could potentially be used to evaluate the effect of bronchodilator or lung volume reduction surgery on dyspnea and exercise tolerance.

5. Study Limitations

Airflow obstruction should be defined as a FEV1/VC ratio below the fifth percentile (z-score −1.645) of the distribution of a reference population [17] according to the 2019 ATS-ERS technical statement [16]. In the present study, the use of GOLD criteria to define COPD could have introduced age, sex, and height selection bias. However, the severity of most of the subjects with COPD in this study had GOLD stages II–IV (93.5%), and thus the likelihood of underdiagnosing COPD was small. Although OCD is not a commonly used tool to evaluate physical activity for patients with COPD, previous studies have suggested that the OCD and the COPD assessment test should be used simultaneously when undertaking clinical evaluations of patients with COPD, and that the OCD in ramp-slope selection should be used for dyspneic patients when undertaking CPET [13,19]. However, the International Physical Activity Questionnaire and accelerometry could also be helpful in this case [37,38]. A novel analytical method reported calculating shunt VD by subtracting respiratory VD (i.e., anatomical VD and alveolar VD) from physiological VD [39]. We did not calculate shunt VD, as this method is sophisticated and the shunt VD level was expected to be small. Tidal flow limitation measured with negative expiratory pressure has been shown to play a role in reducing the IC at rest, during which tidal flow limitation constrains VT expansion during exercise thereby causing an elevation in VD/VT at peak exercise [40]. Although tidal flow limitation was not measured in this study, it can be anticipated to occur in the subjects with more severe airflow obstruction and higher air trapping with a lower IC [41]. In the COPD group in this study, EELV was estimated using the formulae reported in our previous study [11], and thus the estimated DH% and EELV% values may not be exactly the same as the measured data. In the healthy controls, data on VD/VT at rest, AT, and peak exercise were retrieved from reference subjects, as it was difficult to obtain permission from our Institutional Review Boards to perform arterial catheterization for exercise testing. The emphysematous phenotype could be related to VDDH. However, as there were relatively few subjects and emphysema was not evaluated using HRCT in this study, further studies are warranted to address these issues. Lastly, VD cannot be obtained without using invasive method in patients with COPD, and thus its clinical implication could be limited. Studies to investigate the development of a novel noninvasive method to obtain VD or VD/VT are warranted. Finally, using Jones’ and Bohr’s equations to estimate VD/VT in subjects with COPD is not suitable, as PETCO2 used in the equations cannot be used as a surrogate for PaCO2 or alveolar PCO2 [42,43].

6. Conclusions

Although the definitions of VD and DH are quite different, this study shows the utility of their combination, and that it could play a role in physiology with regards to the evaluation of exertional dyspnea and exercise capacity in subjects with COPD. In addition, VT% was significantly correlated with VD/VT, suggesting that VT% is not only a convenient marker for DH as reported previously, but also a potential noninvasive marker for VD/VT.

Abbreviations

VDDead space
DHdynamic hyperinflation
EELVend-expiratory lung volume
VD/VTdead space/tidal volume ratio
COPDchronic obstructive pulmonary disease
OTO’Donnell’s threshold
TLCtotal lung capacity
CPETcardiopulmonary exercise tests
ICinspiratory capacity
FEV1forced expired volume in one second
FVCforced expired capacity
GOLDglobal initiative for chronic obstructive lung disease
OCDoxygen cost diagram
RVresidual volume
DLCOdiffusing capacity for carbon monoxide
VO2oxygen uptake
VCO2CO2 output
VEminute ventilation
PĒCO2mixed expired CO2 pressure
PBbarometric pressure
VDmbreathing valve dead space
ΔΒοργ/Δ ςO2slope of Borg score and oxygen uptake
ΔOoxygen pulse
VAalveolar volume
VE/VCO2ventilatory equivalent for CO2 output
PETCO2end-tidal CO2 pressure
HRCThigh resolution computed tomography
SVCslow vital capacity

Appendix A

Table A1

Summary of the correlation coefficient (r) between the dead space fraction (VD/VT) and some physiological variables reported by Mahut et al. [10] and Elbehairy et al. [3].

rVD/VT
RestPeak
VA/TLC [10]−0.6−0.2
VE peak/MVC% [10]NA0.32
IC peak% predicted [10]NA−0.45
VE/VCO2 [3]0.78 **NA
KCO [10]−0.52−0.43
DLCO% predicted [10]NA*NA*
PaO2peak [10]NA−0.66
Borgpeak/%VO2peak [10]NA0.33

VA, alveolar volume measured during diffusing capacity for carbon monoxide (DLCO) measurement; TLC, total lung capacity; IC, inspiratory capacity; VE, minute ventilation; CO2, CO2 output; KCO, the diffusing constant of Krogh, i.e., DLCO/VA without considering barometric pressure, where VA is alveolar volume in BTPS equal to TLC measured by single breath helium dilution method after subtracting anatomic dead space [34]; Borg, Borg score. * p < 0.05 reported in reference [10], but r values are not reported, ** data involving rest and submaximal exercise in healthy subjects and mild COPD subjects. NA: not available.

Table A2

Pearson correlations (r) pairwise deletion between dead space and tidal volume ratio (VD/VT) and tidal volume and total lung capacity ratio (VT%) at different phases of exercise test in participants with chronic obstructive pulmonary disease.

VT%VD/VT
RestATPeakAll
Rest−0.34 *---
AT-−0.47 **--
Peak--−0.64 -
All-- −0.72

AT: anaerobic threshold, * p < 0.05, ** p < 0.01, p < 0.0001, All: VT% at rest, AT, and peak and VD/VT at rest, AT, and peak were pooled together.

Author Contributions

M.-L.C. initiated and designed the study, analyzed and interpreted the data, wrote the manuscript. All authors have read and agreed to the published version of the manuscript

Funding

The study was supported in part by the Minister of Science and Technology, Taiwan (MOST 106-2314-B-040-025). The funding body had no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.

Conflicts of Interest

The author declares no competing financial interests.

References

1. Lumb A.B., Nunn J.F. Distribution of pulmonary ventilation and perfusion. In: Lumb A.B., editor. Nunn’s Applied Respiratory Physiology. 5th ed. Butterworth Heinemann; Edinburgh, UK: 2000. pp. 163–199. [Google Scholar]
2. Wasserman K., Hansen J.E., Sue D.Y., Stringer W.W., Whipp B.J. Physiology of exercise. In: Wasserman K., editor. Principles of Exercise Testing and Interpretation. 4th ed. Lippicott Williams & Wilkins; Philadelphia, PA, USA: 2005. pp. 10–65. [Google Scholar]
3. Elbehairy A.F., Ciavaglia C.E., Webb K.A., Guenette J.A., Jensen D., Mourad S.M., Neder J.A., O’Donnell D.E. Pulmonary Gas Exchange Abnormalities in Mild Chronic Obstructive Pulmonary Disease. Implications for Dyspnea and Exercise Intolerance. Am. J. Respir. Crit. Care Med. 2015;191:1384–1394. 10.1164/rccm.201501-0157OC. [Abstract] [CrossRef] [Google Scholar]
4. O’Donnell D.E. Hyperinflation, dyspnea, and exercise inteolerance in in chronic obstructive pulmonary disease. Am. J. Respir. Crit. Care Med. 2006;3:180–184. [Abstract] [Google Scholar]
5. O’Donnell D.E., Revill S.M., Webb K.A. Dynamic hyperinflation and exercise intolerance in chronic obstructive pulmonary disease. Am. J. Respir. Crit. Care Med. 2001;164:770–777. 10.1164/ajrccm.164.5.2012122. [Abstract] [CrossRef] [Google Scholar]
6. O’Donnell D.E., Webb K.A. Exertional breathlessness in patients with chronic airflow limitation. The role of lung hyperinflation. Am. Rev. Respir. Dis. 1993;148:1351–1357. 10.1164/ajrccm/148.5.1351. [Abstract] [CrossRef] [Google Scholar]
7. Guenette J.A., Chin R.C., Cory J.M., Webb K.A., O’Donnell D.E. Inspiratory Capacity during Exercise: Measurement, Analysis, and Interpretation. Pulm. Med. 2013;2013:956081. 10.1155/2013/956081. [Europe PMC free article] [Abstract] [CrossRef] [Google Scholar]
8. Casanova C., Cote C., De Torres J.P., Aguirre-Jaime A., Marin J.M., Pinto-Plata V., Celli B.R. Inspiratory-to-total lung capacity ratio predicts mortality in patients with chronic obstructive pulmonary disease. Am. J. Respir. Crit. Care Med. 2005;171:591–597. 10.1164/rccm.200407-867OC. [Abstract] [CrossRef] [Google Scholar]
9. Chuang M.L., Huang S.F., Su C.H. Cardiovascular and respiratory dysfunction in chronic obstructive pulmonary disease complicated by impaired peripheral oxygenation. Int. J. Chron. Obstruct. Pulm. Dis. 2015;10:329–337. 10.2147/COPD.S76209. [Europe PMC free article] [Abstract] [CrossRef] [Google Scholar]
10. Mahut B., Chevalier-Bidaud B., Plantier L., Essalhi M., Callens E., Graba S., Gillet-Juvin K., Valcke-Brossollet J., Delclaux C. Diffusing capacity for carbon monoxide is linked to ventilatory demand in patients with chronic obstructive pulmonary disease. COPD. 2012;9:16–21. 10.3109/15412555.2011.630700. [Abstract] [CrossRef] [Google Scholar]
11. Chuang M.L., Hsieh M.J., Lin I.F. Developing a New Marker of Dynamic Hyperinflation in Patients with Obstructive Airway Disease—An observational study. Sci. Rep. 2019;9:7514. 10.1038/s41598-019-43893-1. [Europe PMC free article] [Abstract] [CrossRef] [Google Scholar]
12. GOLD Committees Global Strategy for the Diagnosis, Management, and Prevention of Chronic Obstructive Pulmonary Disease (revised 2015) [(accessed on 31 July 2015)];Disclosure Forms for GOLD Committees Are Posted on the GOLD Website. Available online: www.goldcopdorg.
13. Chuang M.L., Lin I.F., Lee C.Y. Clinical assessment tests in evaluating patients with chronic obstructive pulmonary disease—A cross-sectional study. Medicine. 2016;95:e5471. 10.1097/MD.0000000000005471. [Europe PMC free article] [Abstract] [CrossRef] [Google Scholar]
14. Chuang M.L., Lin I.F. Investigating the relationships among lung function variables in chronic obstructive pulmonary disease in men. PeerJ. 2019;7:e7829. 10.7717/peerj.7829. [Europe PMC free article] [Abstract] [CrossRef] [Google Scholar]
15. Chuang M.L., Lin I.F., Wasserman K. The body weight-walking distance product as related to lung function, anaerobic threshold and peak VO2 in COPD patients. Respir. Med. 2001;95:618–626. 10.1053/rmed.2001.1115. [Abstract] [CrossRef] [Google Scholar]
16. Graham B.L., Steenbruggen I., Miller M.R., Barjaktarevic I.Z., Cooper B.G., Hall G.L., Hallstrand T.S., Kaminsky D.A., McCarthy K., McCormack M.C., et al. Standardization of Spirometry 2019 Update. An Official American Thoracic Society and European Respiratory Society Technical Statement. Am. J. Respir. Crit. Care Med. 2019;200:e70–e88. 10.1164/rccm.201908-1590ST. [Europe PMC free article] [Abstract] [CrossRef] [Google Scholar]
17. Quanjer P.H., Stanojevic S., Cole T.J., Baur X., Hall G.L., Culver B.H., Enright P.L., Hankinson J.L., Ip M.S., Zheng J., et al. Multi-ethnic reference values for spirometry for the 3-95-yr age range: The global lung function 2012 equations. Eur. Respir. J. 2012;40:1324–1343. 10.1183/09031936.00080312. [Europe PMC free article] [Abstract] [CrossRef] [Google Scholar]
18. Stanojevic S., Graham B.L., Cooper B.G., Thompson B.R., Carter K.W., Francis R.W., Hall G.L. Official ERS technical standards: Global Lung Function Initiative reference values for the carbon monoxide transfer factor for Caucasians. Eur. Respir. J. 2017;50:1700010. 10.1183/13993003.00010-2017. [Abstract] [CrossRef] [Google Scholar]
19. Chuang M.L., Lee C.H., Lin I.F. Using the oxygen-cost diagram in ramp-slope selection for dyspneic patients. Intern. Med. 2010;49:1325–1332. 10.2169/internalmedicine.49.3094. [Abstract] [CrossRef] [Google Scholar]
20. Faisal A., Alghamdi B.J., Ciavaglia C.E., Elbehairy A.F., Webb K.A., Ora J., Neder J.A., O’Donnell D.E. Common Mechanisms of Dyspnea in Chronic Interstitial and Obstructive Lung Disorders. Am. J. Respir. Crit. Care Med. 2016;193:299–309. 10.1164/rccm.201504-0841OC. [Abstract] [CrossRef] [Google Scholar]
21. O’Donnell D.E., Chau L.K., Webb K.A. Qualitative aspects of exertional dyspnea in patients with interstitial lung disease. J. Appl. Physiol. 1998;84:2000–2009. 10.1152/jappl.1998.84.6.2000. [Abstract] [CrossRef] [Google Scholar]
22. Casaburi R., Rennard S.I. Exercise limitation in chronic obstructive pulmonary disease. The O’Donnell threshold. Am. J. Respir. Crit. Care Med. 2015;191:873–875. 10.1164/rccm.201501-0084ED. [Abstract] [CrossRef] [Google Scholar]
23. Chuang M.L., Lin I.F., Vintch J.R.E., Ho B.J., Chao S.W., Ker J.J.W. Significant exercise-induced hypoxaemia with equivocal desaturation in patients with chronic obstructive pulmonary disease. Intern. Med. J. 2006;36:294–301. 10.1111/j.1445-5994.2006.01069.x. [Abstract] [CrossRef] [Google Scholar]
24. Wasserman K., Hansen J.E., Sue D.Y., Stringer W.W., Whipp B.J. Calculations, formulas, and examples. In: Wasserman K., editor. Principles of Exercise Testing and Interpretation. 4th ed. Lippincot Williams & Wilkins; Philadelphia, PA, USA: 2005. pp. 556–565. [Google Scholar]
25. Tzani P., Aiello M., Elia D., Boracchia L., Marangio E., Olivieri D., Clini E., Chetta A. Dynamic hyperinflation is associated with a poor cardiovascular response to exercise in COPD patients. Respir. Res. 2011;12:150. 10.1186/1465-9921-12-150. [Europe PMC free article] [Abstract] [CrossRef] [Google Scholar]
26. Vassaux C., Torre-Bouscoulet L., Zeineldine S., Cortopassi F., Paz-Díaz H., Celli B.R., Pinto-Plata V.M. Effects of hyperinflation on the oxygen pulse as a marker of cardiac performance in COPD. Eur. Respir. J. 2008;32:1275–1282. 10.1183/09031936.00151707. [Abstract] [CrossRef] [Google Scholar]
27. Zhang Y., Sun X.G., Yang W.L., Tan X.Y., Liu J.M. Inspiratory fraction correlates with exercise capacity in patients with stable moderate to severe COPD. Respir. Care. 2013;58:1923–1930. 10.4187/respcare.01927. [Abstract] [CrossRef] [Google Scholar]
28. Chuang M.L., Lin I.F., Huang S.F., Hsieh M.J. Patterns of Oxygen Pulse Curve in Response to Incremental Exercise in Patients with Chronic Obstructive Pulmonary Disease—An Observational Study. Sci. Rep. 2017;7:10929. 10.1038/s41598-017-11189-x. [Europe PMC free article] [Abstract] [CrossRef] [Google Scholar]
29. Xu Y., Yamashiro T., Moriya H., Tsubakimoto M., Tsuchiya N., Nagatani Y., Matsuoka S., Murayama S. Hyperinflated lungs compress the heart during expiration in COPD patients: A new finding on dynamic-ventilation computed tomography. Int. J. Chron. Obstruct. Pulm. Dis. 2017;12:3123–3131. 10.2147/COPD.S145599. [Europe PMC free article] [Abstract] [CrossRef] [Google Scholar]
30. O’Donnell D.E., Webb K.A. The major limitation to exercise performance in COPD is dynamic hyperinflation. J. Appl. Physiol. 2008;105:753–755. 10.1152/japplphysiol.90336.2008b. discussion 755–757. [Abstract] [CrossRef] [Google Scholar]
31. Guenette J.A., Webb K.A., O’Donnell D.E. Does dynamic hyperinflation contribute to dyspnoea during exercise in patients with COPD? Eur. Respir. J. 2012;40:322–329. 10.1183/09031936.00157711. [Abstract] [CrossRef] [Google Scholar]
32. O’Donnell D.E., Elbehairy A.F., Berton D.C., Domnik N.J., Neder J.A. Advances in the Evaluation of Respiratory Pathophysiology during Exercise in Chronic Lung Diseases. Front. Physiol. 2017;8:82. 10.3389/fphys.2017.00082. [Europe PMC free article] [Abstract] [CrossRef] [Google Scholar]
33. Vogiatzis I., Georgiadou O., Golemati S., Aliverti A., Kosmas E., Kastanakis E., Geladas N., Koutsoukou A., Nanas S., Zakynthinos S., et al. Patterns of dynamic hyperinflation during exercise and recovery in patients with severe chronic obstructive pulmonary disease. Thorax. 2005;60:723–729. 10.1136/thx.2004.039115. [Europe PMC free article] [Abstract] [CrossRef] [Google Scholar]
34. Miller A. Diffusing capacity for CO. In: Miller A., editor. Pulmonary Function Tests in Clinical & Occupational. 4th ed. Grune & Stratton, Inc.; Orlando, FL, USA: 1986. pp. 133–159. [Google Scholar]
35. Paoletti P., De Filippis F., Fraioli F., Cinquanta A., Valli G., Laveneziana P., Vaccaro F., Martolini D., Palange P. Cardiopulmonary exercise testing (CPET) in pulmonary emphysema. Respir. Physiol. Neurobiol. 2011;179:167–173. 10.1016/j.resp.2011.07.013. [Abstract] [CrossRef] [Google Scholar]
36. Miniati M., Catapano G.A., Monti S., Mannucci F., Bottai M. Effects of emphysema on oxygen uptake during maximal exercise in COPD. Intern. Emerg. Med. 2013;8:41–47. 10.1007/s11739-011-0575-x. [Abstract] [CrossRef] [Google Scholar]
37. Andersson M., Stridsman C., Rönmark E., Lindberg A., Emtner M. Regional blood flow during periodic acceleration. Respir. Med. 2015;109:1048–1057. 10.1016/j.rmed.2015.05.007. [Abstract] [CrossRef] [Google Scholar]
38. Gore S., Blackwood J., Guyette M., Alsalaheen B. Validity and Reliability of Accelerometers in Patients with COPD: A Systematic Review. J. Cardiopulm. Rehabil. Prev. 2018;38:147–158. 10.1097/HCR.0000000000000284. [Abstract] [CrossRef] [Google Scholar]
39. Hirabayashi G., Ogihara Y., Tsukakoshi S., Daimatsu K., Inoue M., Kurahashi K., Maruyama K., Andoh T. Effect of pressure-controlled inverse ratio ventilation on dead space during robot-assisted laparoscopic radical prostatectomy: A randomised crossover study of three different ventilator modes. Eur. J. Anaesthesiol. 2018;35:307–314. 10.1097/EJA.0000000000000732. [Abstract] [CrossRef] [Google Scholar]
40. Diaz O., Villafranca C., Ghezzo H., Borzone G., Leiva A., Milic-Emili J., Lisboa C. Breathing pattern and gas exchange at peak exercise in COPD patients with and without tidal flow limitation at rest. Eur. Respir. J. 2001;17:1120–1127. 10.1183/09031936.01.00057801. [Abstract] [CrossRef] [Google Scholar]
41. Diaz O., Villafranca C., Ghezzo H., Borzone G., Leiva A., Milic-Emil J., Lisboa C. Role of inspiratory capacity on exercise tolerance in COPD patients with and without tidal expiratory flow limitation at rest. Eur. Respir. J. 2000;16:269–275. 10.1034/j.1399-3003.2000.16b14.x. [Abstract] [CrossRef] [Google Scholar]
42. Lewis D.A., Sietsema K.E., Casaburi R., Sue D.Y. Inaccuracy of noninvasive estimates of VD/VT in clinical exercise testing. Chest. 1994;106:1476–1480. 10.1378/chest.106.5.1476. [Abstract] [CrossRef] [Google Scholar]
43. Zimmerman M.I., Miller A., Brown L.K., Bhuptani A., Sloane M.F., Teirstein A.S. Estimated vs actual values for dead space/tidal volume ratios during incremental exercise in patients evaluated for dyspnea. Chest. 1997;106:131–136. 10.1378/chest.106.1.131. [Abstract] [CrossRef] [Google Scholar]

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