Risk Factors for Postsurgical Gout Flares after Thoracolumbar Spine Surgeries

Gouty arthritis is the most common form of inflammatory arthritis and flares frequently after surgeries. Such flares impede early patient mobilization and lengthen hospital stays; however, little has been reported on gout flares after spinal procedures. This study reviewed a database of 6439 adult p...

Full description

Bibliographic Details
Main Authors: Kuan-Jung Chen, Yen-Chun Huang, Yu-Cheng Yao, Wei Hsiung, Po-Hsin Chou, Shih-Tien Wang, Ming-Chau Chang, Hsi-Hsien Lin
Format: Article
Language:English
Published: MDPI AG 2022-06-01
Series:Journal of Clinical Medicine
Subjects:
Online Access:https://www.mdpi.com/2077-0383/11/13/3749
Description
Summary:Gouty arthritis is the most common form of inflammatory arthritis and flares frequently after surgeries. Such flares impede early patient mobilization and lengthen hospital stays; however, little has been reported on gout flares after spinal procedures. This study reviewed a database of 6439 adult patients who underwent thoracolumbar spine surgery between January 2009 and June 2021, and 128 patients who had a history of gouty arthritis were included. Baseline characteristics and operative details were compared between the flare-up and no-flare groups. Multivariate logistic regression was used to analyze predictors and construct a predictive model of postoperative flares. This model was validated using a receiver operating characteristic (ROC) curve analysis. Fifty-six patients (43.8%) had postsurgical gout flares. Multivariate analysis identified gout medication use (odds ratio [OR], 0.32; 95% confidence interval [CI], 0.14–0.75; <i>p</i> = 0.009), smoking (OR, 3.23; 95% CI, 1.34–7.80; <i>p</i> = 0.009), preoperative hemoglobin level (OR, 0.68; 95% CI, 0.53–0.87; <i>p</i> = 0.002), and hemoglobin drop (OR, 1.93; 95% CI, 1.25–2.96; <i>p</i> = 0.003) as predictors for postsurgical flare. The area under the ROC curve was 0.801 (95% CI, 0.717–0.877; <i>p</i> < 0.001). The optimal cut-off point of probability greater than 0.453 predicted gout flare with a sensitivity of 76.8% and specificity of 73.2%. The prediction model may help identify patients at an increased risk of gout flare.
ISSN:2077-0383