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Title: Hospital admission risk stratification of patients with gout presenting to the emergency department
Authors: WANG HAN 
Allameen, NA
Irwani Binte Ibrahim 
Manjari Lahiri 
Keywords: Clinical decision support systems
Emergency service
Emergency Service, Hospital
Quality of Life
Retrospective Studies
Risk Assessment
Symptom Flare Up
Tertiary Care Centers
Issue Date: 1-Jan-2022
Publisher: Springer Science and Business Media LLC
Citation: WANG HAN, Allameen, NA, Irwani Binte Ibrahim, PREETI DHANASEKARAN, MENGLING FENG, Manjari Lahiri (2022-01-01). Hospital admission risk stratification of patients with gout presenting to the emergency department. Clinical Rheumatology 41 (6) : 1801-1807. ScholarBank@NUS Repository.
Abstract: Abstract: To characterise gout patients at high risk of hospitalisation and to develop a web-based prognostic model to predict the likelihood of gout-related hospital admissions.This was a retrospective single-centre study of 1417 patients presenting to the emergency department (ED) with a gout flare between 2015 and 2017 with a 1-year look-back period. The dataset was randomly divided, with 80% forming the derivation and the remaining forming the validation cohort. A multivariable logistic regression model was used to determine the likelihood of hospitalisation from a gout flare in the derivation cohort. The coefficients for the variables with statistically significant adjusted odds ratios were used for the development of a web-based hospitalisation risk estimator. The performance of this risk estimator model was assessed via the area under the receiver operating characteristic curve (AUROC), calibration plot, and brier score. Patients who were hospitalised with gout tended to be older, less likely male, more likely to have had a previous hospital stay with an inpatient primary diagnosis of gout, or a previous ED visit for gout, less likely to have been prescribed standby acute gout therapy, and had a significant burden of comorbidities. In the multivariable-adjusted analyses, previous hospitalisation for gout was associated with the highest odds of gout-related admission. Early identification of patients with a high likelihood of gout-related hospitalisation using our web-based validated risk estimator model may assist to target resources to the highest risk individuals, reducing the frequency of gout-related admissions and improving the overall health-related quality of life in the long term. Key points: • We reported the characteristics of gout patients visiting a tertiary hospital in Singapore. • We developed a web-based prognostic model with non-invasive variables to predict the likelihood of gout-relatedhospital admissions.
Source Title: Clinical Rheumatology
ISSN: 07703198
DOI: 10.1007/s10067-021-05902-5
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