biostudies-literatureLi MGuangdong Province Basic and Applied Basic Research Foundation609https://www.ebi.ac.uk/biostudies/studies/S-EPMC12584441biostudies-literatureUnknown23(1)<h4>Background</h4>Gout is the most common inflammatory arthritis. Recurrent flares are common among hospitalised patients and contribute to substantial clinical and economic burden. However, the accurate prediction of inpatient recurrence remains challenging, particularly in individuals with comorbid gout. This study aims to evaluate the predictive value of variables and develop a multidimensional, interpretable artificial intelligence (AI) model to predict gout recurrence (GoutRe).<h4>Methods</h4>We conducted a real-world, retrospective, prospective, multicentre cohort study across five tertiary hospitals in China (2010-2024), enrolling 6,526 hospitalised patients with comorbid gout. A total of 82 multidimensional features encompassing laboratory findings, comorbidities, medications, andBMC medicineDevelopment and validation of a multidimensional and interpretable artificial intelligence model to predict gout recurrence in hospitalised patients: a real-world, ambispective multicentre cohort study in China.PMC12584441No.2021A1515220039Wu JLiu JLin RLi JZhang KLi DZhang HCai LLi RLi MCheng ZXie RJiang YXie DZhu JZhong FZheng BChen XChen SYe HWu YfalseDevelopment and validation of a multidimensional and interpretable artificial intelligence model to predict gout recurrence in hospitalised patients: a real-world, ambispective multicentre cohort study in China.<h4>Background</h4>Gout is the most common inflammatory arthritis. Recurrent flares are common among hospitalised patients and contribute to substantial clinical and economic burden. However, the accurate prediction of inpatient recurrence remains challenging, particularly in individuals with comorbid gout. This study aims to evaluate the predictive value of variables and develop a multidimensional, interpretable artificial intelligence (AI) model to predict gout recurrence (GoutRe).<h4>Methods</h4>We conducted a real-world, retrospective, prospective, multicentre cohort study across five tertiary hospitals in China (2010-2024), enrolling 6,526 hospitalised patients with comorbid gout. A total of 82 multidimensional features encompassing laboratory findings, comorbidities, medications, and2025-01-01T00:00:00Z2025 Nov2026-06-05T11:44:39.85Z2026-05-16T03:13:16.215ZS-EPMC125844414118883810.1186/s12916-025-04454-8