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Purpose: Despite increasing awareness, chronic obstructive pulmonary disease (COPD) exacerbations are often unrecognized, not reported or not treated. Assisting patients and caregivers to better identify deteriorations in COPD can help improve care. This study was designed to collect usage and inhalation parameters from albuterol Digihaler devices and its associated Digihaler dashboard, to identify potential inhalation parameters and alerts that might predict worsening COPD.
Patients And Methods: Real-time rescue albuterol Digihaler (albuterol sulfate) results for peak inspiratory flow (PIF), rescue inhaler usage and inhalation volume (InV) were assessed in 20 COPD patients over 6 months. Alert thresholds from device measurements were analyzed for 14 days prior to all COPD deteriorations defined by a COPD exacerbation or an acute worsening in COPD assessment test (CAT) score.
Results: Eleven subjects experienced 22 COPD exacerbations, and 16 subjects experienced 40 CAT score worsening over 6 months' time. No demographic or physiologic differences were identified comparing patients with or without exacerbations or CAT score worsening. Falls in PIF and increases in rescue inhaler usage were weak predictors of impending exacerbations, while a higher percentage (36%) of subjects had a fall in InV prior to an exacerbation. No notable changes in inhaler parameters were associated with deteriorating CAT scores, and no changes in lung function were observed over the study. A combination of 3 alert thresholds was present in 59% of patients within the 2 weeks prior to a COPD exacerbation.
Conclusion: Our study suggests that alert thresholds based on Digihaler device-measured physiologic parameters may have value in a predictive model for clinical deterioration in COPD.
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http://dx.doi.org/10.2147/COPD.S519963 | DOI Listing |
Int J Chron Obstruct Pulmon Dis
May 2025
Pulmonary Research Institute of Southeast Michigan, Farmington Hills, MI, USA.
Purpose: Despite increasing awareness, chronic obstructive pulmonary disease (COPD) exacerbations are often unrecognized, not reported or not treated. Assisting patients and caregivers to better identify deteriorations in COPD can help improve care. This study was designed to collect usage and inhalation parameters from albuterol Digihaler devices and its associated Digihaler dashboard, to identify potential inhalation parameters and alerts that might predict worsening COPD.
View Article and Find Full Text PDFBMJ Open Respir Res
May 2025
Teva Branded Pharmaceutical Products R&D Inc, Parsippany, New Jersey, USA.
Purpose: By using data obtained with digital inhalers, machine learning models have the potential to detect early signs of deterioration and predict impending exacerbations of chronic obstructive pulmonary disease (COPD) for individual patients. This analysis aimed to determine if a machine learning algorithm capable of predicting impending exacerbations could be developed using data from an integrated digital inhaler.
Patients And Methods: A 12-week, open-label clinical study enrolled patients (≥40 years old) with COPD to use ProAir Digihaler, a digital dry powder inhaler with integrated sensors, to deliver their reliever medication (albuterol, 90 µg/dose; 1-2 inhalations every 4 hours, as needed).
NPJ Prim Care Respir Med
August 2024
Inhalation Consultancy Ltd, Leeds, UK.
Electronic inhalers provide information about patterns of routine inhaler use. During a 12-week study, 360 asthma patients using albuterol Digihaler generated 53,083 inhaler events that were retrospectively analyzed. A total of 41,528 (78%) of the recorded inhalation events were suitable for flow analysis (having a PIF ≥ 18 L/min and <120 L/min).
View Article and Find Full Text PDFJ Allergy Clin Immunol Pract
February 2024
Division of Allergy/Immunology, Department of Medicine, National Jewish Health, Denver, Colo; University of Colorado Hospital, Aurora, Colo.
Background: Digital health tools have been shown to help address challenges in asthma control, including inhaler technique, treatment adherence, and short-acting β-agonist overuse. The maintenance and reliever Digihaler System (DS) comprises 2 Digihaler inhalers (fluticasone propionate/salmeterol and albuterol) with an associated patient App and web-based Dashboard. Clinicians can review patients' inhaler use and Digihaler inhalation parameter data to support clinical decision-making.
View Article and Find Full Text PDFJ Asthma Allergy
November 2022
Teva Pharmaceuticals Europe B.V, Amsterdam, the Netherlands.
Purpose: Machine learning models informed by sensor data inputs have the potential to provide individualized predictions of asthma deterioration. This study aimed to determine if data from an integrated digital inhaler could be used to develop a machine learning model capable of predicting impending exacerbations.
Patients And Methods: Adult patients with poorly controlled asthma were enrolled in a 12-week, open-label study using ProAir Digihaler, an electronic multi-dose dry powder inhaler (eMDPI) with integrated sensors, as reliever medication (albuterol, 90 µg/dose; 1-2 inhalations every 4 hours, as needed).