SynthesisInternational journal of chronic obstructive pulmonary disease2026
Predictors of Acute Exacerbations in COPD: A Systematic Review.
Synthesis in International journal of chronic obstructive pulmonary disease, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- COPD Assessment Test Variability as a Predictor of Exacerbations in Patients with COPD: A Prospective Study Using Virtual Assistant Monitoring.Advances in respiratory medicine · 2026Observational
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: COPD is characterized by acute exacerbations (AECOPD), which drive its progression and burden. AECOPD can be caused by various factors. Better prediction of AECOPD provides opportunity for initiating preventive treatment. Methods: This systematic review provides an evidence-based overview of clinical predictors of moderate, severe AECOPD and relapse of moderate and severe AECOPD (≤28 days of a previous AECOPD). Cohort studies, case-control studies, or (cluster) randomized controlled trials published in English between January 2011-December 2023 in PubMed, CINAHL, Embase, Web of Science and the Cochrane library were assessed. Eligible studies included patients diagnosed with COPD, aged ≥40 years, and who were current or ex-smokers. Predictors of AECOPD were categorized into: patient characteristics, symptoms, biomarkers, lung function test results, and composite scores. Critical appraisal was performed with the QUIPS-tool. Results: Out of 1261 screened articles, 30 were included. Sixty-one distinct possible predictors of AECOPD were assessed, of which 37 were statistically significant (P < 0.05). Age, AECOPD history, fibrinogen, FEV Discussion: Based on the highest relative statistical significance, combined with the best overall risk of bias, the most promising predictors of AECOPD are history of ≥1 AECOPD, higher SGRQ-C scores, elevated fibrinogen levels, and worse COPD GOLD (2-4, B-D). Future research should focus on standardization of AECOPD and predictor definitions, including the use of clearly defined cut-off values. Given the complexity and heterogeneity of COPD, combining diverse predictor domains into composite measures may enhance predictive accuracy of AECOPD, and the integration of such composites is promising for advancing COPD management in clinical practice.
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Registered trials
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