Unsupervised home spirometry <i>versus</i> supervised clinic spirometry for respiratory disease: a systematic methodology review and meta-analysis.

Abstract

Background The number of patients completing unsupervised home spirometry has recently increased due to more widely available portable technology and the COVID-19 pandemic, despite a lack of solid evidence to support it. This systematic methodology review and meta-analysis explores quantitative differences in unsupervised spirometry compared with spirometry completed under professional supervision.

Methods We searched four databases to find studies that directly compared unsupervised home spirometry with supervised clinic spirometry using a quantitative comparison ( e.g. Bland-Altman). There were no restrictions on clinical condition. The primary outcome was measurement differences in common lung function parameters (forced expiratory volume in 1 s (FEV 1 ), forced vital capacity (FVC)), which were pooled to calculate overall mean differences with associated limits of agreement (LoA) and confidence intervals (CI). We used the I 2 statistic to assess heterogeneity, the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool to assess risk of bias and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach to assess evidence certainty for the meta-analyses. The review has been registered with PROSPERO (CRD42021272816).

Results 3607 records were identified and screened, with 155 full texts assessed for eligibility. We included 28 studies that quantitatively compared spirometry measurements, 17 of which reported a Bland-Altman analysis for FEV 1 and FVC. Overall, unsupervised spirometry produced lower values than supervised spirometry for both FEV 1 with wide variability (mean difference -107 mL; LoA= -509, 296; I 2 =95.8%; p 2 =96%; p

Conclusions Analysis under the conditions of the included studies indicated that unsupervised spirometry is not interchangeable with supervised spirometry for individual patients owing to variability and underestimation.