AB0885 THE RELATIONSHIP BETWEEN METABOLIC SYNDROME SEVERITY AND THE RISK OF MORTALITY IN GOUT PATIENTS: A POPULATION-BASED STUDY. (June 2019)

• Record Type: Journal Article
• Authors: Schlesinger, Naomi; Elsaid, Mohamed; Rustgi, Vinod
• Is Part Of: Annals of the rheumatic diseases. Volume 78(2019)Supplement 2
• Page Start: 1910
• Page End: 1910
• Publication Date: 2019-06
• Subjects: Rheumatism -- Periodicals; 616.723005
• DOI: 10.1136/annrheumdis-2019-eular.664
• Languages: English
• ISSNs: 0003-4967

Abstract

Abstract : Background: Metabolic syndrome (MetS) is common amongst gout patients. The MetS is diagnosed when a patient has at least 3 of the following 5 conditions of hyperglycemia, hypertension, hypertriglyceridemia, low high-density lipoprotein (HDL) cholesterol or abdominal obesity. Little is known about the relationship between the cumulative effects of all five metabolic syndrome conditions and the risk of mortality among adult patients with gout. Metabolic Syndrome Severity Score (MetSSS) is a new clinical prediction score that employs available components (sex, age, race, systolic blood pressure, waistline circumference, high-density lipoprotein, triglycerides and fasting blood glucose). MetSSS is a validated summary score that accounts for the combined effects of all 5 metabolic features. MetSSS allows examination of associations between MetS severity and the risk of mortality. Objectives: to use the MetSSS to examine the overall associations between MetS severity and the risk of mortality related to all-causes, cardiovascular disease and diabetes amongst United States (US) gout patients. Methods: Mortality-linked data for 12, 101 adults aged 18 to 90 years who participated in the Third National Health and Nutrition Examination Survey (NHANES) III (1988-1994) was analyzed. Data from NHANES III were linked to national mortality records for all participants up to time of death or end of study (i.e. 23 years following initial recruitment). All 5 metabolic features were used to calculate gender-race/ethnicity specific MetSSS Z-scores in gout patients. The Z-score is the number of standard deviations from the mean a data point is and allows a continuous representation of all MetS conditions while accounting for gender-race/ethnicity disparities. Results: A total of 3, 381 deaths were observed, of whom 215 had gout. The prevalence of gout amongst adults was 2.59% (95% CI; 2.13%-3.05%). Moderate to high MetS severity was significantly prevalent among gout patients (47.33% vs. 21.16% no gout; P-value <0.0001). The mean MetSSS Z-score for gout patients was significantly higher than those without gout (0.71 vs. -0.04 no gout; P-value <0.0001). For gout patients, a one-unit increase in MetSSS score was associated with a significant increase in the risk of all-cause mortality Adjusted Hazard Ratio (aHR) 1.46 (95% CI; 1.13, 1.87). In a disease-specific survival model, a one-unit increase in MetSSS score was associated with a aHR 1.62 (95% CI; 1.21, 2.15) increase in heart disease related mortality among gout patients. Amongst those with gout, a one-unit increase in MetSSS score was associated with increased risks of diabetes- and hypertension- related mortalities aHR 2.53 (95% CI; 1.43, 4.62), aHR 1.73 (95% CI; 1.07, 2.79), respectively. Conclusion: The Z score calculation in our study allowed a quantification of increased diabetes- and hypertension- related mortalities, all- cause and cardiovascular mortality in patients with gout. Use of the MetSSS can provide an opportunity to identify patients at highest risk influencing patients to change their lifestyle and better comply with treatment. References: [1] Wiley JF, Carrington MJ. A metabolic syndrome severity score: A tool to quantify cardio-metabolic risk factors. Prev Med2016;88:189-195. [2] Thottam GE, Krasnokutsky S, Pillinger MH. Gout and metabolic syndrome: a tangled web. Curr Rheumatol Rep2017;19:60. Disclosure of Interests: Naomi Schlesinger Grant/research support from: Pfizer, Consultant for: YesNovartis, Horizon Pharma, Proteo Thera, Selecta Biosciences, Olatec, IFM Therapeutics, Mallinckrodt Pharmaceuticals, Mohamed Elsaid: None declared, Vinod Rustgi Grant/research support from: Genfit, Consultant for: yes Allergan, Zydus, Abbvie