Reviews in Cardiovascular Medicine (Sep 2021)

The association between serum uric acid levels and 10-year cardiovascular disease incidence: results from the ATTICA prospective study

  • Niki Katsiki,
  • Matina Kouvari,
  • Demosthenes B Panagiotakos,
  • Claudio Borghi,
  • Christina Chrysohoou,
  • Dimitri P Mikhailidis,
  • Christos Pitsavos

DOI
https://doi.org/10.31083/j.rcm2203108
Journal volume & issue
Vol. 22, no. 3
pp. 991 – 1001

Abstract

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Limited data suggests possible gender-specific association between serum uric acid (SUA) and cardiovascular disease (CVD) incidence. The aim of the present analysis was to evaluate the association between SUA levels and 10-year CVD incidence (2002–2012) in the ATTICA study participants. Overall, 1687 apparently healthy volunteers, with SUA measurements, residing in the greater metropolitan Athens area (Greece), were included. Multivariable Cox-regression models were used to estimate the hazard ratios for SUA in relation to 10-year CVD incidence. Receiver operating curve analysis was conducted to detect optimal SUA cut-off values. Participants in the 2nd and 3rd SUA tertile had 29 and 73% higher 10-year CVD incidence compared with those in the 1st tertile (p < 0.001). In gender-specific analysis, only in women SUA was independently associated with CVD incidence; women in the 3rd SUA tertile had 79% greater 10-year CVD event risk compared to their 1st tertile counterparts. Obese in the 3rd SUA tertile had 2-times higher CVD incidence compared to those in the 1st tertile. Similar findings were observed in metabolically healthy (vs. unhealthy) and metabolically healthy obese. SUA thresholds best predicting 10-year CVD incidence was 5.05 and 4.15 mg/dL (0.30 and 0.25 mmol/L) in men and women, respectively. In conclusion, increased SUA levels were independently related to 10-year CVD event rate in women, obese and metabolically healthy individuals. SUA could predict 10-year CVD incidence even at low levels. Further studies are warranted to identify SUA cut-off values that may improve the detection of individuals at higher CVD risk in clinical practice.

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