Dynamic Hyperinflation During Daily Activities

Hannink, Jorien; Helvoort, H.A.C. van; Dekhuijzen, P.N.R.; Heijdra, Yvonne F.

doi:10.1378/chest.09-1847

Cited by 45 publications

(21 citation statements)

References 34 publications

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“…The amount of ADL-induced DH found in our study is similar to that in earlier findings [5,6]. Given the fact that the occurrence of DH is related to increased dyspnea, and decreased exercise capacity and level of physical activity, the fact that a large amount of DH does occur during regularly performed ADL is important [8,22].…”

Section: Discussionsupporting

confidence: 89%

“…This cut-off was based on the repeatability coefficient of measurements of IC [4]. A relative change in IC (ΔIC) was chosen over an absolute change, because absolute ΔIC is related to the IC value at rest, whereas relative ΔIC shows a more homoscedastic distribution [4,5,19,20]. …”

Section: Methodsmentioning

confidence: 99%

“…So far, it remains unknown whether the DH measured in laboratory settings, i.e. CPET and MPT, reflects the DH that occurs during activities in daily life (ADL) that cause dyspnea [5,6]. From a clinical point of view, it is interesting to know whether a patient with COPD is predisposed to develop DH during ADL.…”

Section: Introductionmentioning

confidence: 99%

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Can COPD Patients Who Hyperinflate During Daily Life Activities Be Identified by Laboratory Tests?

Lahaije

Helvoort

Dekhuijzen³

et al. 2013

Respiration

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Background: Identification of patients with chronic obstructive pulmonary disease (COPD) who develop dynamic hyperinflation (DH) during activities in daily life (ADL) is important, because of the association between DH and dyspnea and exercise limitation. Objective: We aimed to answer the question whether measurements of DH during metronome-paced tachypnea (MPT) or cardiopulmonary exercise testing (CPET) can be used to identify patients who develop DH during ADL. Methods: DH was measured by tracking changes in inspiratory capacity during CPET, MPT and ADL. Bland-Altman plots were used to evaluate agreement in DH between methods. With a receiver operating characteristic (ROC) analysis, the overall accuracy of MPT and CPET to identify patients who hyperinflate during ADL was assessed. Results: There are broad limits of agreement in DH between methods. ROC curve analyses showed good overall accuracy of both CPET and MPT to identify patients who hyperinflate during ADL. For CPET, area under the curve (AUC) = 0.956 (95% CI 0.903-1.009). For MPT, AUC = 0.840 (95% CI 0.699-0.981). Sensitivity and specificity to identify patients who hyperinflate during ADL with CPET were 96 and 83%, respectively, and with MPT, they were 89 and 77%, respectively. Conclusion: Both CPET and MPT can serve as screening tools to identify patients who are susceptible to developing DH during ADL. In practice, MPT is the most simple and inexpensive surrogate. However, the sensitivity of MPT is not optimal. When DH does not occur during CPET, it is unlikely to occur during ADL.

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Section: Discussionsupporting

confidence: 89%

Section: Methodsmentioning

confidence: 99%

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Can COPD Patients Who Hyperinflate During Daily Life Activities Be Identified by Laboratory Tests?

Lahaije

Helvoort

Dekhuijzen³

et al. 2013

Respiration

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“…A recent study showed that dynamic hyperinfl ation occurs in the daily life of patients with COPD of all GOLD stages. 34 Furthermore, dynamic hyperinfl ation has been shown to predict mortality. 35 with FEV 1 % predicted signifi cantly predicted 6MWD in any of the fi ve groups.…”

Section: Discussionmentioning

confidence: 99%

“…24,25 Several studies have shown that dynamic lung hyperinfl ation is associated with 6MWD and daily physical activity in COPD. 31,34,44,45 However, only a few studies examined the association of CT scan fi ndings with exercise tolerance. [14][15][16]18 Two reports studied only 20 subjects with COPD.…”

Section: Discussionmentioning

confidence: 99%

Six-Minute Walk Distance Predictors, Including CT Scan Measures, in the COPDGene Cohort

Rambod

Pórszász

Make

et al. 2012

Chest

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Background: Exercise tolerance in COPD is only moderately well predicted by airfl ow obstruction assessed by FEV 1 . We determined whether other phenotypic characteristics, including CT scan measures, are independent predictors of 6-min walk distance (6MWD) in the COPDGene cohort. Methods: COPDGene recruits non-Hispanic Caucasian and African American current and ex-smokers. Phenotyping measures include postbronchodilator FEV 1 % predicted and inspiratory and expiratory CT lung scans. We defi ned % emphysema as the percentage of lung voxels , 2 950 Hounsfi eld units on the inspiratory scan and % gas trapping as the percentage of lung voxels , 2 856 Hounsfi eld units on the expiratory scan. Results: Data of the fi rst 2,500 participants of the COPDGene cohort were analyzed. Participant age was 61 Ϯ 9 years; 51% were men; 76% were non-Hispanic Caucasians, and 24% were African Americans. Fifty-six percent had spirometrically defi ned COPD, with 9.3%, 23.4%, 15.0%, and 8.3% in GOLD (Global Initiative for Chronic Obstructive Lung Disease) stages I to IV, respectively. Higher % emphysema and % gas trapping predicted lower 6MWD ( P , .001). However, in a given spirometric group, after adjustment for age, sex, race, and BMI, neither % emphysema nor % gas trapping, or their interactions with FEV 1 % predicted, remained a signifi cant 6MWD predictor. In a given spirometric group, only 16% to 27% of the variance in 6MWD could be explained by age, male sex, Caucasian race, and lower BMI as signifi cant predictors of higher 6MWD. Conclusions:In this large cohort of smokers in a given spirometric stage, phenotypic characteristics were only modestly predictive of 6MWD. CT scan measures of emphysema and gas trapping were not predictive of 6MWD after adjustment for other phenotypic characteristics. CHEST 2012; 141(4):867 -875Abbreviations: 6MWD 5 6-min walk distance; 6MWT 5 6-min walk test; GOLD 5 Global Initiative for Chronic Obstructive Lung Disease; HU 5 Hounsfi eld unit; LOWESS 5 locally weighted scatterplot smoothing

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