Differentiating the start of an exacerbation from day-to-day variation in people with COPD: a systematic review

区分慢性阻塞性肺疾病患者病情加重与日常波动:一项系统性综述

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Abstract

INTRODUCTION: COPD symptoms occur with day-to-day variation. An exacerbation of COPD is a symptom worsening that exceeds these fluctuations and requires systemic treatment. Differentiating the start of an exacerbation from day-to-day disease variation is an unmet research need. We sought to examine the evidence that monitoring daily variation in COPD can differentiate this from the onset of an exacerbation. METHODS: A systematic review was conducted across MEDLINE, Embase, the Cumulative Index to Nursing and Allied Health Literature, Institute of Electrical and Electronics Engineers and Cochrane databases, as well as a citation search, following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Eligible studies focused on monitoring daily symptoms and/or physiological parameters in stable COPD. Quality assessments were conducted using the Newcastle-Ottawa Scale and the Cochrane Risk of Bias tool. Findings were qualitatively synthesised, considering essential components. RESULTS: 22 studies were included in the review. The definitions of exacerbation were diverse across studies. 14 (64%) of the included studies demonstrated that day-to-day variation in symptoms (e.g. Chronic Airways Assessment Test score), vital signs (heart rate, respiratory rate and peripheral oxygen saturation) and lung function (peak expiratory flow, forced oscillatory technique), alone and in combination, showed promise in differentiating the onset of exacerbations. Daily monitoring provided earlier detection of exacerbation, up to 7 days before the day of onset. Baseline and threshold settings were identified as crucial factors. Continuous monitoring was more effective than once-daily assessments. CONCLUSION: This review summarises evidence on how day-to-day variation differs from the start of an exacerbation in COPD. The combination of continuous monitoring, reliable measurement tools and a refined algorithm, with personalised baseline and threshold values, yields promising results.

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