A Predictive Model for Clinical Asthma Exacerbations Using Albuterol eMDPI (ProAir Digihaler): A Twelve-Week, Open-Label Study

Background The ability to identify an impending clinical asthma exacerbation (CAE) would improve asthma action plans and provide opportunities for pre-emptive treatment. Increased use of inhaled rescue medications, such as albuterol, has been observed in the days prior to a CAE, but other potential predictive factors are poorly understood. Approved by the US Food and Drug Administration (FDA) in late 2018, ProAir Digihaler with built-in sensors registers when patients use the inhaler and has been shown previously to accurately measure both peak inspiratory flow and inhalation volume, confirming the device’s ability to reliably record objective information on inhaler usage and technique. Objective Data collected from the ProAir Digihaler provides, for the first time, a more complete picture of patients’ use of inhaled medication, and thereby offers an opportunity to develop a predictive model of an impending CAE, and the potential to better implement asthma action plans and facilitate early treatment. Methods Patients (≥18 years old) with exacerbation-prone asthma were recruited to a 12-week, open-label study. Patients used the ProAir Digihaler (albuterol 90 µg 1–2 inhalations q4 hours) as needed. The electronic component of Digihaler recorded each use and inhalation variables (peak inspiratory flow, volume inhaled, time to peak flow, and inhalation duration). Data were downloaded from the inhalers and, together with clinical data, subjected to a machine-learning algorithm to develop models predictive of an impending CAE as defined by the need for oral corticosteroids. The generated model was evaluated by receiver operating characteristic (ROC) curve analysis. Results Three hundred and sixty patients made ≥1 valid inhalation from the Digihaler and were included in the analysis. Of these, 64 patients experienced a total of 78 CAEs. The strongest predictive factor during the 5 days before a CAE was the average number of albuterol inhalations per day. The predictive model was strengthened by supplementing these data with other inhalation features collected by Digihaler, including peak inhalation flow, inhalation volume, night-time usage, and trends of these parameters over time. This model predicted an impending exacerbation over the 5 days with a ROC AUC value of 0.75. Conclusions This study represents, to our knowledge, the first successful attempt to develop a model to predict CAE derived from the use of a rescue medication inhaler device equipped with an integrated sensor and capable of measuring inhalation parameters. The predictive power of the model would benefit from further development with larger populations of asthma patients.

The Effect of Inhalation Volume and Breath-Hold Duration on the Retention of Nicotine and Solanesol in the Human Respiratory Tract and on Subsequent Plasma Nicotine Concentrations During Cigarette Smoking

The influence of inhalation depth and breath-hold duration on the retention of nicotine and solanesol in the human respiratory tract and on nicotine uptake was studied in ten cigarette smokers. In a first series of experiments, the subjects took seven puffs from a 10 mg ‘tar’ yield, test cigarette and a fixed volume of air (0, 75, 250, 500 or 1000 mL, as required by the protocol) was inhaled after each puff in order to give a controlled ‘depth’ of inhalation. The inhalation was drawn from a bag containing the required volume of air. Following a 2 s breath-hold, subjects exhaled normally, with the first exhalation after each puff passing through a single acidified filter pad for collection of the non-retained nicotine and solanesol. Blood samples were taken before and at intervals during and after smoking for the sessions with 0, 75 and 500 mL inhalation volumes for determination of plasma nicotine and carboxyhaemoglobin levels. Another series of experiments was conducted with a fixed inhalation volume (500 mL) and two further breath-hold durations (0 and 10 s) in addition to 2 s from above. Nicotine and solanesol retentions were measured for each breath-hold condition. The amounts of nicotine retained within the respiratory system, expressed as a percentage of the amount taken into the mouth, were consistently higher than the corresponding values for solanesol in all five inhalation conditions (0-1000 mL, 2 s breath-hold). Nicotine retention increased from 46.5% at zero inhalation to 99.5% at 1000 mL inhalation (2 s breath-hold) and from 98.0% at zero breath-hold to 99.9% at 10 s breath-hold (500 mL inhalation). Solanesol retention increased from 34.2% at zero inhalation volume to 71.9% at 1000 mL inhalation (2 s breath-hold) and from 51.8% at zero breath-hold to 87.6% at 10 s breath-hold (500 mL inhalation). Plasma nicotine decreased from pre-smoking levels after zero inhalation indicating that the nicotine retained within the mouth was poorly absorbed into the systemic circulation. After 75 mL inhalation, plasma nicotine levels were significantly greater than for zero inhalation but not significantly less than after 500 mL inhalation except at the time of maximum nicotine concentration. As in every experimental condition, a higher percentage of nicotine than solanesol was retained within the respiratory tract, it was concluded that the difference in retention of the moderately volatile nicotine and the non-volatile solanesol is consistent with the concept of nicotine evaporation from smoke particles and the subsequent efficient retention in the airways of gaseous nicotine. The retention of solanesol followed the expected pattern of particulate deposition i.e., an increase with both increasing depth of inhalation and breath-hold duration. However, nicotine retention was almost complete even at shallow inhalations and short breath-hold durations.