18 research outputs found

    Risk Factors for Prognosis in Patients With Severely Decreased GFR

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    Introduction: Patients with chronic kidney disease (CKD) and estimated glomerular filtration rate (eGFR) < 30 ml/min per 1.73 m 2 (corresponding to CKD stage G4+) comprise a minority of the overall CKD population but have the highest risk for adverse outcomes. Many CKD G4+ patients are older with multiple comorbidities, which may distort associations between risk factors and clinical outcomes. Methods: We undertook a meta-analysis of risk factors for kidney failure treated with kidney replacement therapy (KRT), cardiovascular disease (CVD) events, and death in participants with CKD G4+ from 28 cohorts (n = 185,024) across the world who were part of the CKD Prognosis Consortium. Results: In the fully adjusted meta-analysis, risk factors associated with KRT were time-varying CVD, male sex, black race, diabetes, lower eGFR, and higher albuminuria and systolic blood pressure. Age was associated with a lower risk of KRT (adjusted hazard ratio: 0.74; 95% confidence interval: 0.69–0.80) overall, and also in the subgroup of individuals younger than 65 years. The risk factors for CVD events included male sex, history of CVD, diabetes, lower eGFR, higher albuminuria, and the onset of KRT. Systolic blood pressure showed a U-shaped association with CVD events. Risk factors for mortality were similar to those for CVD events but also included smoking. Most risk factors had qualitatively consistent associations across cohorts. Conclusion: Traditional CVD risk factors are of prognostic value in individuals with an eGFR < 30 ml/min per 1.73 m 2, although the risk estimates vary for kidney and CVD outcomes. These results should encourage interventional studies on correcting risk factors in this high-risk population

    Risk Factors for Prognosis in Patients With Severely Decreased GFR

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    Introduction: Patients with chronic kidney disease (CKD) and estimated glomerular filtration rate (eGFR) &lt;30 ml/min per 1.73 m2 (corresponding to CKD stage G4þ) comprise a minority of the overall CKD population but have the highest risk for adverse outcomes. Many CKD G4þ patients are older with multiple comorbidities, which may distort associations between risk factors and clinical outcomes.Methods: We undertook a meta-analysis of risk factors for kidney failure treated with kidney replacement therapy (KRT), cardiovascular disease (CVD) events, and death in participants with CKD G4þ from 28 cohorts (n ¼ 185,024) across the world who were part of the CKD Prognosis Consortium.Results: In the fully adjusted meta-analysis, risk factors associated with KRT were time-varying CVD, male sex, black race, diabetes, lower eGFR, and higher albuminuria and systolic blood pressure. Age was associated with a lower risk of KRT (adjusted hazard ratio: 0.74; 95% confidence interval: 0.69–0.80) overall, and also in the subgroup of individuals younger than 65 years. The risk factors for CVD events included male sex, history of CVD, diabetes, lower eGFR, higher albuminuria, and the onset of KRT. Systolic blood pressure showed a U-shaped association with CVD events. Risk factors for mortality were similar to those for CVD events but also included smoking. Most risk factors had qualitatively consistent associations across cohorts.Conclusion: Traditional CVD risk factors are of prognostic value in individuals with an eGFR &lt;30 ml/min per 1.73 m2, although the risk estimates vary for kidney and CVD outcomes. These results should encourage interventional studies on correcting risk factors in this high-risk population.</br

    Conversion of urine protein-creatinine ratio or urine dipstick to urine albumin-creatinine ratio for use in CKD screening and prognosis

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    Background: Although measuring albuminuria is the preferred method for defining and staging chronic kidney disease (CKD), total urine protein or dipstick protein is often measured instead. Objective: To develop equations for converting urine protein–creatinine ratio (PCR) and dipstick protein to urine albumin–creatinine ratio (ACR) and to test their diagnostic accuracy in CKD screening and staging. Design: Individual participant–based meta-analysis. Setting: 12 research and 21 clinical cohorts. Participants: 919 383 adults with same-day measures of ACR and PCR or dipstick protein. Measurements: Equations to convert urine PCR and dipstick protein to ACR were developed and tested for purposes of CKD screening (ACR ≥30 mg/g) and staging (stage A2: ACR of 30 to 299 mg/g; stage A3: ACR ≥300 mg/g). Results: Median ACR was 14 mg/g (25th to 75th percentile of cohorts, 5 to 25 mg/g). The association between PCR and ACR was inconsistent for PCR values less than 50 mg/g. For higher PCR values, the PCR conversion equations demonstrated moderate sensitivity (91%, 75%, and 87%) and specificity (87%, 89%, and 98%) for screening (ACR >30 mg/g) and classification into stages A2 and A3, respectively. Urine dipstick categories of trace or greater, trace to +, and ++ for screening for ACR values greater than 30 mg/g and classification into stages A2 and A3, respectively, had moderate sensitivity (62%, 36%, and 78%) and high specificity (88%, 88%, and 98%). For individual risk prediction, the estimated 2-year 4-variable kidney failure risk equation using predicted ACR from PCR had discrimination similar to that of using observed ACR. Limitation: Diverse methods of ACR and PCR quantification were used; measurements were not always performed in the same urine sample. Conclusion: Urine ACR is the preferred measure of albuminuria; however, if ACR is not available, predicted ACR from PCR or urine dipstick protein may help in CKD screening, staging, and prognosis. Primary Funding Source: National Institute of Diabetes and Digestive and Kidney Diseases and National Kidney Foundation

    Serum potassium and adverse outcomes across the range of kidney function: a CKD Prognosis Consortium meta-analysis.

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    Aims: Both hypo- and hyperkalaemia can have immediate deleterious physiological effects, and less is known about long-term risks. The objective was to determine the risks of all-cause mortality, cardiovascular mortality, and end-stage renal disease associated with potassium levels across the range of kidney function and evaluate for consistency across cohorts in a global consortium. Methods and results: We performed an individual-level data meta-analysis of 27 international cohorts [10 general population, 7 high cardiovascular risk, and 10 chronic kidney disease (CKD)] in the CKD Prognosis Consortium. We used Cox regression followed by random-effects meta-analysis to assess the relationship between baseline potassium and adverse outcomes, adjusted for demographic and clinical characteristics, overall and across strata of estimated glomerular filtration rate (eGFR) and albuminuria. We included 1 217 986 participants followed up for a mean of 6.9 years. The average age was 55 ± 16 years, average eGFR was 83 ± 23 mL/min/1.73 m2, and 17% had moderate- to-severe increased albuminuria levels. The mean baseline potassium was 4.2 ± 0.4 mmol/L. The risk of serum potassium of >5.5 mmol/L was related to lower eGFR and higher albuminuria. The risk relationship between potassium levels and adverse outcomes was U-shaped, with the lowest risk at serum potassium of 4-4.5 mmol/L. Compared with a reference of 4.2 mmol/L, the adjusted hazard ratio for all-cause mortality was 1.22 [95% confidence interval (CI) 1.15-1.29] at 5.5 mmol/L and 1.49 (95% CI 1.26-1.76) at 3.0 mmol/L. Risks were similar by eGFR, albuminuria, renin-angiotensin-aldosterone system inhibitor use, and across cohorts. Conclusions: Outpatient potassium levels both above and below the normal range are consistently associated with adverse outcomes, with similar risk relationships across eGFR and albuminuria

    Incorporating kidney disease measures into cardiovascular risk prediction: Development and validation in 9 million adults from 72 datasets

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    Background: Chronic kidney disease (CKD) measures (estimated glomerular filtration rate [eGFR] and albuminuria) are frequently assessed in clinical practice and improve the prediction of incident cardiovascular disease (CVD), yet most major clinical guidelines do not have a standardized approach for incorporating these measures into CVD risk prediction. “CKD Patch” is a validated method to calibrate and improve the predicted risk from established equations according to CKD measures. Methods: Utilizing data from 4,143,535 adults from 35 datasets, we developed several “CKD Patches” incorporating eGFR and albuminuria, to enhance prediction of risk of atherosclerotic CVD (ASCVD) by the Pooled Cohort Equation (PCE) and CVD mortality by Systematic COronary Risk Evaluation (SCORE). The risk enhancement by CKD Patch was determined by the deviation between individual CKD measures and the values expected from their traditional CVD risk factors and the hazard ratios for eGFR and albuminuria. We then validated this approach among 4,932,824 adults from 37 independent datasets, comparing the original PCE and SCORE equations (recalibrated in each dataset) to those with addition of CKD Patch. Findings: We confirmed the prediction improvement with the CKD Patch for CVD mortality beyond SCORE and ASCVD beyond PCE in validation datasets (Δc-statistic 0.027 [95% CI 0.018–0.036] and 0.010 [0.007–0.013] and categorical net reclassification improvement 0.080 [0.032–0.127] and 0.056 [0.044–0.067], respectively). The median (IQI) of the ratio of predicted risk for CVD mortality with CKD Patch vs. the original prediction with SCORE was 2.64 (1.89–3.40) in very high-risk CKD (e.g., eGFR 30–44 ml/min/1.73m2 with albuminuria ≥30 mg/g), 1.86 (1.48–2.44) in high-risk CKD (e.g., eGFR 45–59 ml/min/1.73m2 with albuminuria 30–299 mg/g), and 1.37 (1.14–1.69) in moderate risk CKD (e.g., eGFR 60–89 ml/min/1.73m2 with albuminuria 30–299 mg/g), indicating considerable risk underestimation in CKD with SCORE. The corresponding estimates for ASCVD with PCE were 1.55 (1.37–1.81), 1.24 (1.10–1.54), and 1.21 (0.98–1.46). Interpretation: The “CKD Patch” can be used to quantitatively enhance ASCVD and CVD mortality risk prediction equations recommended in major US and European guidelines according to CKD measures, when available. Funding: US National Kidney Foundation and the NIDDK
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