Functional Predictors Discriminating Asthma–COPD Overlap (ACO) from Chronic Obstructive Pulmonary Disease (COPD)

Abstract

Background A significant proportion of patients with obstructive lung disease have clinical and functional features of both asthma and chronic obstructive pulmonary disease (COPD), referred to as the asthma–COPD overlap (ACO). The distinction of these phenotypes, however, is not yet well-established due to the lack of defining clinical and/or functional criteria. The aim of our investigations was to assess the discriminating power of various lung function parameters on the assessment of ACO. Methods From databases of 4 pulmonary centers, a total of 540 patients (231 males, 309 females), including 372 patients with asthma, 77 patients with ACO and 91 patients with COPD, were retrospectively collected, and gradients among combinations of explanatory variables of spirometric (FEV 1 , FEV 1 /FVC, FEF 25-75 ), plethysmographic (sR eff , sG eff , the aerodynamic work of breathing at rest; sWOB), static lung volumes, including trapped gases and measurements of the carbon monoxide transfer (DL CO , K CO ) were explored using multiple factor analysis (MFA). The discriminating power of lung function parameters with respect to ACO was assessed using linear discriminant analysis (LDA). Results LDA revealed that parameters of airway dynamics (sWOB, sR eff , sG eff ) combined with parameters of static lung volumes such as functional residual capacity (FRC pleth ) and trapped gas at FRC (V TG FRC ) are valuable and potentially important tools discriminating between asthma, ACO and COPD. Moreover, sWOB significantly contributes to the diagnosis of obstructive airway diseases, independent from the state of pulmonary hyperinflation, whilst the diffusion capacity for carbon monoxide (DL CO ) significantly differentiates between the 3 diagnostic classes. Conclusion The complexity of COPD with its components of interaction and their heterogeneity, especially in discrimination from ACO, may well be differentiated if patients are explored by a whole set of target parameters evaluating, interactionally, flow limitation, airway dynamics, pulmonary hyperinflation, small airways dysfunction and gas exchange disturbances assessing specific functional deficits.

Predicting parameters of airway dynamics generated from inspiratory and expiratory plethysmographic airway loops, differentiating subtypes of chronic obstructive diseases

“…Most importantly, this kind of modelling has been shown to be predictive for a large age range from childhood to adulthood 35. In fact, the healthy human body has a wide range of regulatory mechanisms during normal breathing and can serve as a model to understand what the interactions would look like in patients with respiratory disorders.…”

“…31 We have recently demonstrated that good discrimination between asthma, asthma-COPD overlap (ACO) [32][33][34] and COPD is possible based on parameters obtained from the plethysmographic sR aw -loop. 35 To visualise further information, not yet recognised in the sR aw -loop, figure 1 shows a plethysmographic shift volume (V pleth ) and tidal flow (V′) plot of a patient with COPD, from which the inspiratory and expiratory parts of the breathing cycle are separately calculated. This results in parameters such as the inspiratory and expiratory sWOB (sWOB in , sWOB ex ), as well as the inspiratory and expiratory sR eff (sR eff IN and sR eff…”

“…The most promising approach is based on the integral method, originally proposed by Matthys and Orth, which provides the integral of the ∮∆normalVnormalpnormallnormalenormaltnormalhnormaldnormalVnormalT -loop (the so-called sR aw -loop) as sWOB, from which the effective specific airway resistance (sR eff ) can be calculated 31. We have recently demonstrated that good discrimination between asthma, asthma–COPD overlap (ACO)32–34 and COPD is possible based on parameters obtained from the plethysmographic sR aw -loop 35. To visualise further information, not yet recognised in the sR aw -loop, figure 1 shows a plethysmographic shift volume (V pleth ) and tidal flow (V′) plot of a patient with COPD, from which the inspiratory and expiratory parts of the breathing cycle are separately calculated.…”

The value of bronchodilator response in FEV1 and FeNO for differentiating between chronic respiratory diseases: an observational study

“…It is very important to determine whether ΔFEV 1 ≥ 345 mL could distinguish ACO from COPD in patients with a positive BDT result. Another study revealed that lung function parameters are potentially important tools in discriminating between asthma, ACO, and COPD [ 41 ]. COPD and asthma are characterized by incompletely reversible and reversible airflow obstruction, respectively [ 22 , 42 ].…”

Assessment of functional diversities in patients with Asthma, COPD, Asthma-COPD overlap, and Cystic Fibrosis (CF)

“…Authors had no access to information that could identify individual participants during or after data collection. The anamnestic, clinical features, and the diagnosis for each patient was made by trained pediatric and adult pulmonologists based on history-taking, chest radiographs, high-resolution CT scans, spirometry, whole-body plethysmography, and measurement of the fraction of exhaled nitric oxide (FeNO); additional detail regarding how the clinical diagnoses have been established previously given [ 32 , 33 ].…”