ABSTRACT
Background: Use of home spirometry to monitor lung function has been increasing in popularity in persons with cystic fibrosis (PwCF) since the start of the COVID-19 pandemic. Although clinic spirometry is interpreted from validated standards, expected test-to-test variation of home spirometry and how variation during baseline health may relate to clinical changes are unknown. The aim of this study was to determine variation in baseline lung function during daily home spirometry and identify associations with clinical outcomes. Method(s): Subjectswere selected based on available spirometry data from a cohort of PwCF enrolled in a long-term airway microbiome study. Subjects were provided with a PiKo-6 hand-held spirometer (nSpire Health, Inc., Longmont, CO) and asked to perform spirometry maneuvers three times per. Validity of home spirometry (percentage predicted forced expiratory volume in 11 second (FEV1pp)) was compared with that clinic spirometry using Bland-Altman plots. Spirometry acceptability across multiple maneuvers in the same day was assessed using the American Thoracic Society (ATS) guidelines, with grade A or B (two or more maneuvers within 150 mL) considered acceptable. Variation in FEV1pp was assessed by calculating a mean FEV1pp and coefficient of variation (CoV). The association between CoV and pulmonary exacerbations (PEx) was tested using Cox proportional hazards regression models. Result(s): Thirteen subjects (62% female) with a mean age of 28.7 +/- 8.3 and mean FEV1pp of 59.9 +/- 8.2%were included. Median study durationwas 377 days (range, 33-730 days). Subjects used the home spirometer on average 51.2% of the study days (range 15-97%). On average, 58.9% of subjects (range 12-100%) used the home spirometer at least twice aweek, and 76.8% (range 65-100%) at least once aweek. To focus on periods of baseline health, days associated with PEx (spirometry performed 2 weeks before and during times of antibiotic therapy) were excluded. A median of 204 days (range 11-728 days) of baseline spirometry readings was available for further analysis. Comparing validity of home spirometry with that of clinic spirometry, Bland-Altman plots demonstrated overall good agreement with a slight bias (+0.042 L) toward higher readings for clinic FEV1pp (95% limits of agreement, -0.11-0.19 L). Spirometry quality was graded as acceptable on most study days (mean 90.6 +/- 4.6%) in which two or more maneuvers were recorded. Intra-individual variation in baseline FEV1pp was high, with a mean variation of 17.6 +/- 5.9% day to day and 15.2 +/- 6.2% week to week. Neither rates of acceptable spirometry grades nor CoV was associated with lung disease severity. Of the 13 subjects, 10 experienced one or more PEx, for a total of 32 PEx during the study. CoV was not associated with time to first PEx (hazard ratio [HR], 0.78;95% confidence interval [CI], 0.51-1.21;p = 0.24) or time to subsequent PEx (HR, 0.91;95% CI, 0.73-1.12;p = 0.28) during the study. Conclusion(s): Although home spirometry has generally good validity and acceptability, variation in lung function during baseline health is present and often exceeds expected variation in clinic spirometry per ATS standards. Variability may represent normal physiological variation or be related to the home spirometer itself or other factors but did not portend upcoming PEx. Recognition of variation during baseline health provides important context for interpretation of home spirometry.Copyright © 2022, European Cystic Fibrosis Society. All rights reserved
ABSTRACT
Background: In the COVID pandemic, patients have had to rely on remote consultations to help them to live with their condition. Aim(s): We aimed to explore how a connected system (A4A+) linking smart devices (inhaler/watch/peak flow meter) could support asthma self-management. Method(s): The A4A+ system collected data from smart devices that could be shared with practices in a pdf attached to patients' electronic health records. We recruited 10 patients via social media, observed their usage of the system over a month, and undertook baseline and exit interviews. We also interviewed 3 GPs and an asthma nurse for their views on the report format. Thematic analysis used the Unified Theory of Acceptance and Use of Technology (UTAUT) model. Result(s): 7517 self-management data-points (asthma symptoms, PEFR, inhaler usage, exercise intensity, heart rate, sleeping pattern, body/air temperature) were collected from 10 patients though recording reduced over the month. Most patients chose to monitor their reliever inhaler rather than the preventer. Patients felt 'positive', found it 'easy' to use the system and chose to use devices they thought were "accurate". Monitoring adjustments to medication, having asthma (or COVID) symptoms triggered and motivated them to adopt the system. Clinicians wanted an overall asthma score/status and reliever usage on the report. Conclusion(s): A connected system could enable flexible digital approaches to care by providing on-going selfmanagement data to support remote consultation. However, providing users with confidence in the 'accuracy' of systems is needed to maintain patients' motivation to use the system.