The National Kidney Foundation–Kidney Disease Outcomes Quality Initiative (NKF-KDOQI) guideline for evaluation, classification, and stratification of chronic kidney disease (CKD) was published in ...2002. The KDOQI guideline was well accepted by the medical and public health communities, but concerns and criticisms arose as new evidence became available since the publication of the original guidelines. KDIGO (Kidney Disease: Improving Global Outcomes) recently published an updated guideline to clarify the definition and classification of CKD and to update recommendations for the evaluation and management of individuals with CKD based on new evidence published since 2002. The primary recommendations were to retain the current definition of CKD based on decreased glomerular filtration rate or markers of kidney damage for 3 months or more and to include the cause of kidney disease and level of albuminuria, as well as level of glomerular filtration rate, for CKD classification. NKF-KDOQI convened a work group to write a commentary on the KDIGO guideline in order to assist US practitioners in interpreting the KDIGO guideline and determining its applicability within their own practices. Overall, the commentary work group agreed with most of the recommendations contained in the KDIGO guidelines, particularly the recommendations regarding the definition and classification of CKD. However, there were some concerns about incorporating the cause of disease into CKD classification, in addition to certain recommendations for evaluation and management.
Background Chronic kidney disease (CKD) and hyperuricemia often coexist, and both conditions are increasing in prevalence in the United States. However, their shared role in cardiovascular risk ...remains highly debated. Study Design Cross-sectional and longitudinal. Setting & Participants Participants in the National Health and Nutrition Examination Survey (NHANES) from 1988 to 2002 (n = 10,956); data were linked to mortality data from the National Death Index through December 31, 2006. Predictors Serum uric acid concentration, categorized as the sex-specific lowest (<25th), middle (25th-<75th), and highest (≥75th) percentiles; and kidney function assessed by estimated glomerular filtration rate (eGFR) based on the CKD-EPI (CKD Epidemiology Collaboration) creatinine-cystatin C equation and urinary albumin-creatinine ratio (ACR). Outcomes Cardiovascular death and all-cause mortality. Results Uric acid levels were correlated with eGFRcr-cys ( r = −0.29; P < 0.001) and were correlated only slightly with ACR ( r = 0.04; P < 0.001). There were 2,203 deaths up until December 31, 2006, of which 981 were due to cardiovascular causes. Overall, there was a U-shaped association between uric acid levels and cardiovascular mortality in both women and men, although the lowest risk of cardiovascular mortality occurred at a lower level of uric acid for women compared with men. There was an association between the highest quartile of uric acid level and cardiovascular mortality even after adjustment for potential confounders (HR, 1.48; 95% CI, 1.13-1.96), although this association was attenuated after adjustment for ACR and eGFRcr-cys (HR, 1.25; 95% CI, 0.89-1.75). The pattern of association between uric acid levels and all-cause mortality was similar. Limitations GFR not measured; mediating events were not observed. Conclusions High uric acid level is associated with cardiovascular and all-cause mortality, although this relationship was no longer statistically significant after accounting for kidney function.
Kidney function monitoring using creatinine-based glomerular filtration rate estimation is a routine part of clinical practice. Emerging evidence has shown that cystatin C may improve classification ...of glomerular filtration rate for defining chronic kidney disease in certain clinical populations and assist in understanding the complications of chronic kidney disease. In this review and update, we summarize the overall literature on cystatin C, critically evaluate recent high-impact studies, highlight the role of cystatin C in recent kidney disease guidelines, and suggest a practical approach for clinicians to incorporate cystatin C into practice. We conclude by addressing frequently asked questions related to implementing cystatin C use in a clinical setting.
Since 1980, the American College of Cardiology (ACC) and American Heart Association (AHA) have translated scientific evidence into clinical practice guidelines with recommendations to improve ...cardiovascular health. These guidelines, which are based on systematic methods to evaluate and classify evidence, provide a foundation for the delivery of quality cardiovascular care. The ACC and AHA sponsor the development and publication of clinical practice guidelines without commercial support, and members volunteer their time to the writing and review efforts.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Throughout these guidelines similar to the 2013 guidelines, consistent attention is given to a clinician–patient risk discussion for making shared decisions. Besides major risk factors of the pooled ...cohort equations (PCE), the clinician–patient risk discussion can include other risk-enhancing factors, and when risk status is uncertain, a coronary artery calcium (CAC) score is an option to facilitate decision-making in adults ≥40 years of age. Another study projected a similar improvement in economic value (S7.1-6). ...raising the threshold for LDL-C on maximal statin therapy to initiate a PCSK9 inhibitor should improve its cost-effectiveness (Figure 3). ...the value of PCSK9 inhibitor therapy in FH is uncertain.8 Limitations and Knowledge Gaps 8.1 Randomized Controlled Trials ACC/AHA guidelines are based largely on the outcomes of RCTs. ...the clinician–patient risk discussion should include more than the initial treatment decision.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Background:Cardiovascular guidelines include risk prediction models for decision making that lack the capacity to include novel predictors.Methods and Results:We explored a new “predictor patch” ...approach to calibrating the predicted risk from a base model according to 2 components from outside datasets: (1) the difference in observed vs. expected values of novel predictors and (2) the hazard ratios (HRs) for novel predictors, in a scenario of adding kidney measures for cardiovascular mortality. Using 4 US cohorts (n=54,425) we alternately chose 1 as the base dataset and constructed a base prediction model with traditional predictors for cross-validation. In the 3 other “outside” datasets, we developed a linear regression model with traditional predictors for estimating expected values of glomerular filtration rate and albuminuria and obtained their adjusted HRs of cardiovascular mortality, together constituting a “patch” for adding kidney measures to the base model. The base model predicted cardiovascular mortality well in each cohort (c-statistic 0.78–0.91). The addition of kidney measures using a patch significantly improved discrimination (cross-validated ∆c-statistic 0.006 0.004–0.008) to a similar degree as refitting these kidney measures in each base dataset.Conclusions:The addition of kidney measures using our new “predictor patch” approach based on estimates from outside datasets improved cardiovascular mortality prediction based on traditional predictors, providing an option to incorporate novel predictors to an existing prediction model.
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