Physiological predictors Of peak inspiRatory flow using Observed lung function resultS (POROS): evaluation at discharge among patients hospitalized for a COPD exacerbation
Received 16 May 2018
Accepted for publication 25 October 2018
Published 13 December 2018 Volume 2018:13 Pages 3937—3946
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 3
Editor who approved publication: Dr Richard Russell
David B Price,1,2 Sen Yang,1 Simon Wan Yau Ming,1 Antony Hardjojo,1 Claudia Cabrera,3,4 Andriana I Papaioannou,5 Stelios Loukides,5 Vicky Kritikos,6 Sinthia Z Bosnic-Anticevich,6 Victoria Carter,7 Paul M Dorinsky8
1Observational and Pragmatic Research Institute, Singapore, Singapore; 2Centre of Academic Primary Care, Division of Applied Health Sciences, University of Aberdeen, Aberdeen, UK; 3Global Medical Affairs, AstraZeneca R and D, Mölndal, Sweden; 4Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden; 52nd Respiratory Medicine Department, Medical School, National and Kapodistrian University of Athens, Attikon General Hospital, Athens, Greece; 6Woolcock Institute of Medical Research, Quality Use of Respiratory Medicines Group, School of Medical Sciences, University of Sydney, Glebe, Australia; 7Optimum Patient Care, Cambridge, UK; 8Pearl – a member of the AstraZeneca Group, Durham, NC, USA
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 FEV1 and % predicted peak expiratory flow (PEF) for Turbohaler® (R-squared value 0.374); higher FEV1 and diagnosis of gastroesophageal reflux disease (GERD) for Aerolizer® (R-squared value 0.209) and higher FEV1, 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.
Keywords: hospital admission, COPD, dry powder inhaler devices, inhaler technique, resistance, spirometry
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