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Physiological predictors Of peak inspiRatory flow using Observed lung function resultS (POROS): evaluation at discharge among patients hospitalized for a COPD exacerbation

BACKGROUND: Peak inspiratory flow (PIF) as generated through the resistance of a dry powder inhaler (DPI) device is a critical patient-dependent maneuver impacting the success of DPI medication delivery. Despite its importance, it is not routinely measured in clinical practice. Little is currently k...

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Detalles Bibliográficos
Autores principales: Price, David B, Yang, Sen, Ming, Simon Wan Yau, Hardjojo, Antony, Cabrera, Claudia, Papaioannou, Andriana I, Loukides, Stelios, Kritikos, Vicky, Bosnic-Anticevich, Sinthia Z, Carter, Victoria, Dorinsky, Paul M
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove Medical Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6296178/
https://www.ncbi.nlm.nih.gov/pubmed/30587952
http://dx.doi.org/10.2147/COPD.S174371
Descripción
Sumario:BACKGROUND: Peak inspiratory flow (PIF) as generated through the resistance of a dry powder inhaler (DPI) device is a critical patient-dependent maneuver impacting the success of DPI medication delivery. Despite its importance, it is not routinely measured in clinical practice. Little is currently known about the relationship, if any, between PIF through DPI devices, routine spirometry and disease outcomes. AIM: The aim of this study was to identify potential predictors of PIF for different DPIs from spirometric parameters and patient characteristics and explore the association between PIF and follow-up events. PATIENTS AND METHODS: A retrospective observational study at discharge among patients hospitalized for a COPD exacerbation at Attikon hospital, Athens, Greece. Spirometry was performed using an Easy on-PC™ spirometer. PIF was measured through four DPI resistances using the In-Check™ DIAL. Regression analyses were used to investigate the association between PIF through resistances and spirometric parameters obtained at discharge, comorbidities and demographic parameters. RESULTS: Forty-seven COPD patients (mean [±SD], age 71 [±9] years, 72% males, 51% current smokers) were included in this study. Overall, 85% and 15% were classified as GOLD (2017) groups D and C, respectively. Most prevalent comorbidities were hypertension (70%) and cardiovascular disease (53%). In the final regression model, higher PIF was significantly associated with the following: higher FEV(1) and % predicted peak expiratory flow (PEF) for Turbohaler(®) (R-squared value 0.374); higher FEV(1) and diagnosis of gastroesophageal reflux disease (GERD) for Aerolizer(®) (R-squared value 0.209) and higher FEV(1), younger age and diagnosis of ischemic heart disease (IHD) for Diskus(®) (R-squared value 0.350). However, R-squared values for all three devices were weak (<0.4). CONCLUSION: The study did not provide evidence to support the use of surrogate measurements for PIF through device resistance, which could assist in determining the appropriateness of inhaler device type. Although PIF measurement is feasible in patients at discharge and could be a valuable addition to the standard of care in COPD management, it needs to be measured directly.