Abnormal levels of both albuminuria and estimated glomerular filtration rate (eGFR) have been reported separately to be associated with cardiovascular risk. This study assessed the contribution of each separately in correctly identifying individuals at cardiovascular risk in the general population beyond traditional risk markers.
Prospective community-based cohort study.
SETTING & PARTICIPANTS:
8,507 individuals from the city of Groningen in the Netherlands followed up for 10.5 years for cardiovascular morbidity and mortality.
PREDICTOR OR FACTOR:
The contribution of albuminuria and eGFR separately on top of the traditional Framingham risk factors was assessed.
The composite of first occurrence of myocardial infarction, stroke, ischemic heart disease, revascularization procedure, and all-cause mortality.
At the baseline visit, albuminuria was measured in 2 consecutive 24-hour urine samples. eGFR was calculated using the serum creatinine-based CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration) equation.
In multivariable Cox regression models, albuminuria, but not eGFR, was associated independently with the primary study outcome (HR, 1.08 [95% CI, 1.04-1.12] per doubling of albuminuria). When added to the risk model consisting of Framingham risk factors, albuminuria significantly contributed to better risk stratification, shown by an increase in net reclassification index of 7.2% (95% CI, 3.3%-11.0%; P < 0.001) and increase in relative incremental discrimination improvement of 3.0% (95% CI, 0.9%-5.1%; P = 0.006).
The cohort includes mainly individuals of European ancestry. Therefore, results should not be extrapolated to other ethnicities.
In a general population cohort, albuminuria, but not eGFR, significantly adds to traditional cardiovascular risk factors in identifying individuals at risk of cardiovascular morbidity and all-cause mortality.
This very interesting piece of research from the PREVEND group shows what was suspected and alluded to by others
(Clase et al http://www.ncbi.nlm.nih.gov/pubmed/21357908
and Chang & Kramer, 2010): http://www.ncbi.nlm.nih.gov/pubmed?term=chang%2C%20kramer%2C%20Nephron)
that eGFR doesnt improve the predictive value of a Framingham Risk Score (FRS) for CVD and related mortality. This supports what I have argued all along that low eGFR in the community reflects underlying atherosclerosis and ischemic renal damage most often associated with the ageing process. http://www.ncbi.nlm.nih.gov/pubmed/20445499
and therefore it is not surprising that is predicts underlying CVD and their outcomes. CKD is in fact a target organ consequence of CVD. So no surprise that CKD predicts CVD and its outcomes but so does a good history taking, physical examination or a Vascular Risk Score like the FRS.
I argued the same for microalbuminuria; that it is merely a urinary reflection of ill health in the community. The Urine ESR or CRP.... This may also be attributable to age related atherosclerosis and vascular dysfunction. So it would not be suprising that a marker of CVD predicts overt CVD and its complications in the community!!!!
However, the study of Smink and Colleagues from Groningen seem ti imply that albuminuria adds to the predicitve value of the FRS. It improves the Net Reclassification Index (NRI) by 7.2%. Interestingly, it doesnt seem to improve the prediction of those who go on to experience an event....in fact it worsens the FRS predictive value by -2.8% in those.....but it improves the predictive value of those who do NOT experience an event....So my reading would be FRS in the absence of albuminuria is good news!!!!! But adding albuminuria to FRS worsens rather than improve the FRS prediction model?????
So for people in the community at risk of CVD, the FRS is most accurate in predicting major CV events and associated mortality.
Neither eGFR nor Albuminuria improve its positive predictive value.
Take a good history and Examine your patients do derive a good prediction model of CVD and outcomes.
Neither eGFR or microalbuminuria add much to good clinical prediction models. On their own they are predicitive of CVD and related mortality as they reflect underlying CVD in communities, but when compared or added to strong and established CVD prediction models they add nothing or little....!!!!