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

The objectives of the present study were to evaluate the discriminating power of spirometric and plethysmographic lung function parameters to differenciate the diagnosis of asthma, ACO, COPD, and to define functional characteristics for more precise classification of obstructive lung diseases. From the databases of 4 centers, a total of 756 lung function tests (194 healthy subjects, 175 with asthma, 71 with ACO, 78 with COPD and 238 with CF) were collected, and gradients among combinations of target parameters from spirometry (forced expiratory volume one second: FEV1; FEV1/forced vital capacity: FEV1/FVC; forced expiratory flow between 25-75% FVC: FEF25-75), and plethysmography (effective, resistive airway resistance: sReff; aerodynamic work of breathing at rest: sWOB), separately for in- and expiration (sReffIN, sReffEX, sWOBin, sWOBex) as well as static lung volumes (total lung capacity: TLC; functional residual capacity: FRCpleth; residual volume: RV), the control of breathing (mouth occlusion pressure: P0.1; mean inspiratory flow: VT/TI; the inspiratory to total time ratio: TI/Ttot) and the inspiratory impedance (Zinpleth = P0.1/VT/TI) were explored. Linear discriminant analyses (LDA) were applied to identify discriminant functions and classification rules using recursive partitioning decision trees. LDA showed a high classification accuracy (sensitivity and specificity > 90%) for healthy subjects, COPD and CF. The accuracy dropped for asthma (~70%) and even more for ACO (~60%). The decision tree revealed that P0.1, sRtot, and VT/TI differentiate most between healthy and asthma (68.9%), COPD (82.1%), and CF (60.6%). Moreover, using sWOBex and Zinpleth ACO can be discriminated from asthma and COPD (60%). Thus, the functional complexity of obstructive lung diseases can be understood, if specific spirometric and plethysmographic parameters are used. Moreover, the newly described parameters of airway dynamics and the central control of breathing including Zinpleth may well serve as promising functional marker in the field of precision medicine.

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

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 (FEV1, FEV1/FVC, FEF25-75), plethysmographic (sReff, sGeff, the aerodynamic work of breathing at rest; sWOB), static lung volumes, including trapped gases and measurements of the carbon monoxide transfer (DLCO, KCO) 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, sReff, sGeff) combined with parameters of static lung volumes such as functional residual capacity (FRCpleth) and trapped gas at FRC (VTG 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 (DLCO) 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.

Bronchodilator Response in Patients with COPD, Asthma-COPD-Overlap (ACO) and Asthma, Evaluated by Plethysmographic and Spirometric z-Score Target Parameters.

BACKGROUND: Airflow reversibility criteria in COPD are still debated - especially in situations of co-existing COPD and asthma. Bronchodilator response (BDR) is usually assessed by spirometric parameters. Changes assessed by plethysmographic parameters such as the effective, specific airway conductance (sGeff), and changes in end-expiratory resting level at functional residual capacity (FRCpleth) are rarely appreciated. We aimed to assess BDR by spirometric and concomitantly measured plethysmographic parameters. Moreover, BDR on the specific aerodynamic work of breathing (sWOB) was evaluated. METHODS: From databases of 3 pulmonary centers, BDR to 200 g salbutamol was retrospectively evaluated by spirometric (∆FEV1 and ∆FEF25-75), and plethysmographic (∆sGeff, ∆FRCpleth, and ∆sWOB) parameters in a total of 843 patients diagnosed as COPD (478 = 57%), asthma-COPD-overlap (ACO) (139 = 17%), or asthma (226 = 27%), encountering 1686 BDR-measurement-sets (COPD n = 958; ACO n = 276; asthma n = 452). RESULTS: Evaluating z-score improvement taking into consideration the whole pre-test z-score range, highest BDR was achieved by combining ∆sGeff and ∆FRC detecting BDR in 62.2% (asthma: 71.4%; ACO: 56.7%; COPD: 59.8%), by ∆sGeff in 53.4% (asthma: 69.1%; ACO: 51.6%; COPD: 47.4%), whereas ∆FEV1 only distinguished in 10.6% (asthma: 21.8%; ACO: 18.6%; COPD: 4.2%). Remarkably, ∆sWOB detected BDR in 49.4% (asthma: 76.2%; ACO: 47.8%; COPD: 46.9%). CONCLUSION: BDR largely depends on the pre-test functional severity and, therefore, should be evaluated in relation to the pre-test conditions expressed as ∆z-scores, considering changes in airway dynamics, changes in static lung volumes and changes in small airway function. Plethysmographic parameters demonstrated BDR at a significant higher rate than spirometric parameters.