An artificial intelligence-based gout management system reduced chronic kidney disease incident and improved target
Han Qi1,2, Jie Lu1,2, Nicola Dalbeth3
1Shandong Provincial Clinical Research Center for Immune Diseases and Gout, Qingdao, China.
Insights
An artificial intelligence (AI) gout management system reduced chronic kidney disease (CKD) incidence in gout patients. This AI system also improved serum urate (SU) target achievement, offering a novel approach to managing gout and its renal complications.
Area of Science:
- Nephrology
- Rheumatology
- Artificial Intelligence in Medicine
Background:
- Chronic kidney disease (CKD) affects a significant portion of individuals with gout.
- The impact of urate-lowering therapy (ULT) on CKD progression remains unclear.
- Novel interventions are needed to improve management of gout and its renal complications.
Purpose of the Study:
- To assess the impact of an AI-based gout clinic intervention on CKD incidence.
- To evaluate the effectiveness of the AI intervention in achieving serum urate (SU) targets.
- To compare outcomes between an AI system and standard care in gout patients.
Main Methods:
- An observational study utilized propensity score (PS)-matched cohorts.
- Comparison between an AI-based Gout Intelligent Management System (GIMS) and a standard Electronic Medical Records system (EMRS).
- Follow-up over 4 years for patients with gout and estimated glomerular filtration rate >60 mL/min.
Main Results:
- The GIMS group showed a reduced incidence of CKD stage ≥3 compared to the EMRS group (4.1 vs. 7.7 per 100 person-years).
- Significantly more participants in the GIMS group achieved SU <6.0 mg/dL (49.8% vs. 25.9%, P < 0.001).
- The AI-based system demonstrated improved ULT effectiveness and renal outcomes.
Conclusions:
- The AI-based Gout Intelligent Management System is associated with lower CKD incidence in gout patients.
- This AI system significantly improves the achievement of target serum urate levels.
- The Gout Intelligent Management System offers a novel strategy for enhancing real-world renal outcomes and ULT success in gout management.
Objectives:
Stage ≥3 chronic kidney disease (CKD) affects ∼25% of people with gout. The effects of urate-lowering therapy (ULT) on CKD incidence and progression have remained inconclusive. Here, we assessed the impact of a gout ULT clinic intervention using artificial intelligence (AI) on CKD incidence and achievement of serum urate (SU) target.
Methods:
An observational study compared propensity score (PS)-matched gout cohorts from an AI-based Gout Intelligent Management System (GIMS) and a standard Electronic Medical Records system (EMRS) clinic database. The GIMS included a mobile application, data fusion interface and modules for expert consultation and laboratory results management. All patients had gout and a starting estimated glomerular filtration rate >60 ml/min. Using a 1:2 PS-matched cohort study design, we assessed the impact of the AI-based system on CKD outcomes and ULT effectiveness over 4 years of follow-up.
Results:
Compared with EMRS, GIMS was associated with reduced incidence of CKD stage ≥3. Specifically, 169/4117 new-onset CKD stage ≥3 (incidence 4.1 per 100 person-years) with GIMS compared with 164/2128 with EMRS (incidence 7.7 per 100 person-years) during follow-up. More participants achieved SU <6.0 mg/dl with GIMS versus EMRS during follow-up (49.8% vs 25.9%, P < 0.001).
Conclusion:
Application of the artificial intelligence-based Gout Intelligent Management System was associated with lower incidence of chronic kidney disease stage ≥3 and superior target serum urate achievement in people with gout. The Gout Intelligent Management System represents a novel approach to improve real-world renal outcomes and urate-lowering therapy success in gout.
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