Lorraine Watson l.watson@keele.ac.uk
202 Gout attack trajectories in a 3-year cohort study in primary care
Watson, Lorraine; Belcher, John; Mallen, Christian D; Roddy, Edward
Authors
John Belcher j.belcher@keele.ac.uk
Christian Mallen c.d.mallen@keele.ac.uk
Edward Roddy e.roddy@keele.ac.uk
Abstract
Background: Gout affects 2.5% of adults in the UK but is often poorly managed. Whilst the hallmark of gout is recurrent sudden-onset attacks of acute joint pain and swelling, little is known about the pattern (trajectory) of attacks over time. We aimed to derive gout attack trajectories and to determine which patients are at most risk of frequent attacks.
Methods: People with gout registered with 20 general practices self-reported the number of gout attacks experienced at 5 time-points (baseline, 6, 12, 24 and 36 months) by completing a postal questionnaire. Latent class growth analysis (LCGA) was used to identify distinct classes of gout attack trajectories. Statistical criteria and practical interpretability were used to decide the optimal number of classes (groups) of gout attacks trajectories. Baseline comorbidities, medications, socio-demographic and gout-specific characteristics of members of gout attack trajectory classes were compared.
Results: 1,164 participants, who had self-reported the number of gout attacks at ≥ 1 time-points, were included in the analysis; mean age 65.6 years (SD 12.5), 972 (84%) male. LCGA identified six latent classes: ‘frequent and persistent’ (n = 95), ‘frequent then improving’ (n = 14), ‘gradually worsening’ (n = 276), ‘moderately frequent’ (n = 287), ‘moderately frequent then improving’ (n = 143) and ‘infrequent’ (n = 349). The ‘frequent and persistent’, ‘frequent then improving’ and ‘gradually worsening’ classes had higher proportions of class members with an eGFR<60 mL/min/1.73m2. (31%, 43%, 30% respectively) compared to other classes. The ‘frequent and persistent’ class had the highest proportion of class members classified as obese (41%) and ‘most deprived’ (45%). The ‘frequent then improving’ class had the lowest proportion of participants reporting to take allopurinol (29%) at baseline, but the highest proportion of class members with a prescription for diuretics in the two years prior to baseline (43%). The ‘gradually worsening’ class had the highest mean serum urate level (481 µmol/L) at baseline. The ‘infrequent’ class had the highest proportion of class members reporting allopurinol use at baseline (73%) and the lowest mean serum urate level (377 µmol/L). Further characteristics of class members will be presented.
Conclusion: For the first-time, distinct gout attack trajectories have been identified. Our findings support the use of urate-lowering therapy to reduce gout attack frequency. Less frequent attacks were associated with allopurinol use and supressed urate. Those with frequent attacks were more likely to be obese, socio-economically deprived and have a high urate. Better understanding of which patients are at most risk of frequent gout attacks will help to target interventions and improve patient care.
Citation
Watson, L., Belcher, J., Mallen, C. D., & Roddy, E. 202 Gout attack trajectories in a 3-year cohort study in primary care
Presentation Conference Type | Conference Paper (published) |
---|---|
Online Publication Date | Apr 12, 2019 |
Publication Date | Apr 1, 2019 |
Deposit Date | Jun 23, 2023 |
Journal | Rheumatology |
Print ISSN | 1462-0324 |
Electronic ISSN | 1462-0332 |
Publisher | Oxford University Press |
Peer Reviewed | Peer Reviewed |
Volume | 58 |
Issue | Supplement_3 |
DOI | https://doi.org/10.1093/rheumatology/kez107.018 |
Keywords | Pharmacology (medical); Rheumatology |
Public URL | https://keele-repository.worktribe.com/output/503454 |
You might also like
The role of diet in serum urate concentration.
(2018)
Journal Article
Downloadable Citations
About Keele Repository
Administrator e-mail: research.openaccess@keele.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search