Flow Profiles Identify Sources of Poor Metered Dose Inhaler Technique
BACKGROUND: Inhaled medications are commonly used as therapy for obstructive lung disease (OLD); however, poor technique from pressurized metered dose inhalers (pMDIs) can severely limit drug delivery and therapeutic efficacy.A novel flow sensor has been developed to characterize inhalation flow profiles from pMDIs.RESEARCH QUESTION: Among patients with OLD, does recording flow profiles during pMDI inhalation maneuvers expose poor patterns of pMDI use, which can be used to remediate pMDI technique?STUDY DESIGN AND METHODS: A novel flow sensor was coupled with a placebo pMDI to characterize inhalation technique in 70 participants with OLD from a pulmonary clinic.pMDI inhalation flow profiles generated actuation timing, mean inspiratory airflow, and inspired volume before and after visualizing these features.McNemar test was used to characterize the impact of training on pMDI inhalation metrics.The postactuation inspired volume was normalized to inspiratory capacity.RESULTS: Among participants with a mean AE SD of 17.4 AE 17.9 years of pMDI use, flow profiles uncovered mistimed actuations in 47.1% and poor inspiratory flow rates in 30.0% of patients.After visualizing flow profiles, participants improved actuation timing (c 2 12.042;P < .001),mean inhaled volume (87.9% to 105.6% of inspiratory capacity; P < .001),and the combined inhalation metrics (c 2 8.45;P .003).INTERPRETATION: Flow profiles helped uncover and remediate specific defects in pMDI technique in most chronic users with OLD.Flow profiles from inhaled medications can be used to enhance drug delivery to the lung.
Authors
- Elizabeth C. Katz (ORCID: https://orcid.org/0000-0001-9539-082X)
- Hartmut Schneider (ORCID: https://orcid.org/0000-0001-7557-6280)
- Rohan D. Milak
- Stuart D. King
- Mudiaga Sowho (ORCID: https://orcid.org/0000-0003-3946-0605)
- Alan R. Schwartz (ORCID: https://orcid.org/0000-0001-9222-3751)
Publication Details
- Journal
- CHEST Pulmonary
- Published
- 2024-11-08
- DOI
- https://doi.org/10.1016/j.chpulm.2024.100116
- Citations
- 1
- Primary Topic
- Green IT and Sustainability
- Type
- article
- Field-Weighted Citation Impact
- 0.21