Published in:
Open Access 01-12-2015 | Research article
Cystatin C and long term risk of community-acquired sepsis: a population-based cohort study
Published in: BMC Nephrology | Issue 1/2015
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Background
Chronic kidney disease (CKD) and systemic inflammation are risk factors for sepsis. While often viewed as a marker of chronic kidney disease, Cystatin C (Cyst-C) may also reflect systemic inflammation. We sought to determine the association between elevated baseline Cyst-C and long-term rates of community-acquired sepsis, and to determine if this relationship is influenced by traditional markers of CKD (estimated glomerular filtration rate [eGFR], albumin-to-creatinine ratio [ACR]) and inflammation (high sensitivity C-reactive protein [hsCRP]).
Methods
We studied 30,239 adults ≥45 years old from the REasons for Geographic and Racial Differences in Stroke (REGARDS) cohort. The primary exposure was elevated Cyst-C (>1.12 mg/dL) measured at study baseline. The primary outcome was the first sepsis hospitalization during a 10-year observation period. Using Cox regression, we evaluated the association between elevated Cyst-C and first sepsis event, adjusted for sociodemographics, health behaviors, chronic medical conditions, eGFR, ACR and hsCRP.
Results
Among participants, 1,532 experienced a sepsis event. Median Cyst-C levels were: sepsis 1.08 (IQR 0.91-1.33) mg/dL (43.8% >1.12 mg/dL), non-sepsis 0.94 (IQR 0.82-1.10) mg/dL (23.4% >1.12 mg/dL). Cyst-C > 1.12 mg/dL was independently associated with increased rates of sepsis, adjusted for participant demographics, health behaviors and chronic medical conditions (HR 1.75; 95% CI: 1.55-1.96). The addition of eGFR < 60 mg/min/1.73 m2, ACR ≥ 30 mg/g and hsCRP > 3.0 mg/dL only partially attenuated the association between Cyst-C > 1.12 mg/dL and rates of sepsis (adjusted HR 1.51; 1.32-1.72).
Conclusions
Elevated Cyst-C is associated with increased long-term rates of community-acquired sepsis, independent of abnormal eGFR, ACR or hsCRP. Cyst-C may play a role in long-term sepsis risk prediction and prevention.