Effect of exercise intensity on the changes in alveolar slopes of carbon dioxide and oxygen expiratory profiles in humans

Steinacker, Jürgen M.; Dehnert, Christoph; Whipp, Brian J.

doi:10.1007/s004210100422

Cited by 5 publications

(4 citation statements)

References 20 publications

(36 reference statements)

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“…In the absence of a true criterion test for exercise ventilatory inefficiency, we relied on a cluster of variables that are indirect markers of pulmonary gas-exchange disturbances. In this context, exercise induced elevations in PETCO 2 reflect either true carbon dioxide retention or delayed lung emptying in COPD [37,38]. Considering that PETCO 2 grossly underestimates alveolar carbon dioxide tension in these patients [36], our assumptions, which are increases in PETCO 2 indicate more severe gas exchange disturbances in COPD, still hold true.…”

Section: Figurementioning

confidence: 72%

Exercise ventilatory inefficiency in mild to end-stage COPD

et al. 2014

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Ventilatory inefficiency during exercise is a key pathophysiological feature of chronic obstructive pulmonary disease. Currently, it is unknown how this physiological marker relates to clinically relevant outcomes as resting ventilatory impairment progresses across disease stages.Slope and intercept of the linear region of the ventilation-carbon dioxide output relationship and the ratio between these variables, at the lowest point (nadir), were contrasted in 316 patients with Global Initiative for Chronic Obstructive Lung Disease (GOLD) stages 1-4 (forced expiratory volume in 1 s, ranging from 148% pred to 12% pred) and 69 aged-and gender-matched controls, Compared to controls, slope and intercept were higher in GOLD stages 1 and 2, leading to higher nadirs ( p<0.05). Despite even larger intercepts in GOLD stages 3 and 4, slopes diminished as disease evolved (from mean±SD 35±6 in GOLD stage 1 to 24±5 in GOLD stage 3, p<0.05). As a result, there were no significant differences in nadirs among patient groups. Higher intercepts, across all stages ( p<0.01), and to a lesser extent lower slopes in GOLD stages 2-4 ( p<0.05), were related to greater mechanical constraints, worsening pulmonary gas exchange, higher dyspnoea scores, and poorer exercise capacity.Increases in the ventilation intercept best indicate the progression of exercise ventilatory inefficiency across the whole spectrum of chronic obstructive pulmonary disease severity. @ERSpublications Exercise ventilatory inefficiency relates to dyspnoea and exercise intolerance across whole COPD severity spectrum

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Section: Figurementioning

confidence: 72%

Exercise ventilatory inefficiency in mild to end-stage COPD

et al. 2014

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“…Second, Whipp et al (43) pointed out that Grønlund's approach may provide a different breath duration under specific conditions, such as during the transition from rest to exercise, compared with that of the conventional flow-based approach. Since the slope of the alveolar partial pressure of expired O 2 (and CO 2 ) increase at the onset of exercise and during continued exercise (38), a particular intra-breath 𝐹 reference value at t1 might be reached earlier during the expiration phase at t2, which in turn would result in a shorter estimated breath duration, and differentially alter the durations of inspiratory and/or expiratory time (such as in t I /t E or t I/ t TOT ), than with the conventional approach (43). The same concern applies to the CF algorithm ( 16), although specific aspects of this algorithm may help mitigate this concern (see below) (39,41).…”

Section: Limitations Methodological Considerations and Future Directionsmentioning

confidence: 99%

“…Although unlikely, a given reference value at t1 may not be attained at t2 over a long series of breaths, which would result in losing the breath considered (Figure 4B) (see Capelli et al for further details) (10). This may occur during hyperventilation, where tachypnea increases the slope of the alveolar partial pressure of expired O 2 (and CO 2 ) (38) (see below for further details).…”

Section: *Figure 3 Near Here*mentioning

confidence: 99%

Current definitions of the breathing cycle in alveolar breath-by-breath gas exchange analysis

Girardi

Gattoni

Stringer

et al. 2023

American Journal of Physiology-Regulatory, Integrative and Comp

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Identification of the breathing cycle forms the basis of any breath-by-breath gas exchange analysis. Classically, the breathing cycle is defined as the time interval between the beginning of two consecutive inspiration phases. Based on this definition, several research groups have developed algorithms designed to estimate the volume and rate of gas transferred across the alveolar membrane ("alveolar gas exchange"); however, most algorithms require measurement of lung volume at the beginning of the ith breath ( VLi-1 - i.e., the end-expiratory lung volume of the preceding ith breath). The main limitation of these algorithms is that direct measurement of VLi-1 is challenging and often unavailable. Two solutions avoid the requirement to measure VLi-1 by redefining the breathing cycle. One method defines the breathing cycle as the time period between two equal fractional concentrations of lung expired oxygen ( FO2) (or carbon dioxide; FCO2), typically in the alveolar phase, whereas the other uses the time period between equal values of the FO2/FN2 (or FCO2/ FN2) ratios. Thus, these methods identify the breathing cycle by analyzing the gas fraction traces rather than the gas flow signal. In this review, we define the traditional approach and two alternative definitions of the human breathing cycle and present the rationale for redefining this term. We also explore the strengths and limitations of the available approaches and provide implications for future studies.

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“…The beta angle measures close to 90° (Smalhout andKalenda et al 1981, Bhavani-Shankar et al 1995). Many studies have shown phase III (alveolar plateau) to hold some discrimination ability for asthmatic and non-asthmatic patients (Gravenstein 2004), and to increase during exercise (Steinacker et al 2001). Yaron et al proposed a method to calculate the slope of the alveolar plateau, whose units are mmHg s −1 (Yaron et al 1996).…”

Section: Capnogram Shape As Physiological State Indicatorsmentioning

confidence: 99%

Segmentation and classification of capnograms: application in respiratory variability analysis

et al. 2014

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Variability analysis of respiratory waveforms has been shown to provide key insights into respiratory physiology and has been used successfully to predict clinical outcomes. The current standard for quality assessment of the capnogram signal relies on a visual analysis performed by an expert in order to identify waveform artifacts. Automated processing of capnograms is desirable in order to extract clinically useful features over extended periods of time in a patient monitoring environment. However, the proper interpretation of capnogram derived features depends upon the quality of the underlying waveform. In addition, the comparison of capnogram datasets across studies requires a more practical approach than a visual analysis and selection of high-quality breath data. This paper describes a system that automatically extracts breath-by-breath features from capnograms and estimates the quality of individual breaths derived from them. Segmented capnogram breaths were presented to expert annotators, who labeled the individual physiological breaths into normal and multiple abnormal breath types. All abnormal breath types were aggregated into the abnormal class for the purpose of this manuscript, with respiratory variability analysis as the end-application. A database of 11,526 breaths from over 300 patients was created, comprising around 35% abnormal breaths. Several simple classifiers were trained through a stratified repeated ten-fold cross-validation and tested on an unseen portion of the labeled breath database, using a subset of 15 features derived from each breath curve. Decision Tree, K-Nearest Neighbors (KNN) and Naive Bayes classifiers were close in terms of performance (AUC of 90%, 89% and 88% respectively), while using 7, 4 and 5 breath features, respectively. When compared to airflow derived timings, the 95% confidence interval on the mean difference in interbreath intervals was ± 0.18 s. This breath classification system provides a fast and robust pre-processing of continuous respiratory waveforms, thereby ensuring reliable variability analysis of breath-by-breath parameter time series.

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Effect of exercise intensity on the changes in alveolar slopes of carbon dioxide and oxygen expiratory profiles in humans

Abstract: The slope of the expired alveolar partial pressure of carbon dioxide pro®le increases during exercise.

Cited by 5 publications

References 20 publications

Exercise ventilatory inefficiency in mild to end-stage COPD

Exercise ventilatory inefficiency in mild to end-stage COPD

Current definitions of the breathing cycle in alveolar breath-by-breath gas exchange analysis

Segmentation and classification of capnograms: application in respiratory variability analysis

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