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Article 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 ( 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), 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 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 and FVC. Overall, unsupervised spirometry produced lower values than supervised spirometry for both FEV with wide variability (mean difference -107 mL; LoA= -509, 296; I=95.8%; p<0.001; very low certainty) and FVC (mean difference -184 mL, LoA= -1028, 660; I=96%; p<0.001; very low certainty).
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.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10481332 | PMC |
| http://dx.doi.org/10.1183/16000617.0248-2022 | DOI Listing |
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