Low plasma magnesium concentration and future abdominal aortic calcifications in moderate chronic kidney disease.

BACKGROUND: Higher plasma magnesium concentrations are associated with reduced cardiovascular disease risk in chronic kidney disease (CKD) patients. The importance of plasma magnesium concentration for vascular calcification in earlier stages of CKD remains underexplored. This study investigated whether plasma magnesium is a determinant for the presence and severity of vascular calcification in moderate CKD. METHODS: Retrospective analysis was performed using abdominal aortic calcification (AAC) scores in 280 patients with stage 3 and 4 CKD enrolled in the MASTERPLAN trial. Lateral abdominal X-ray was used to evaluate AAC. Plasma magnesium concentration were measured over time. A zero-inflated Poisson model determined the association between plasma magnesium concentration and AAC. RESULTS: 79 out of 280 patients did not have AAC, and in patients with AAC the median calcification score was 3.5 (interquartile range: 0.0-8.6). The mean plasma magnesium concentration was 0.76 ± 0.10 mmol/L at baseline. A 0.1 mmol/L higher plasma magnesium concentration was associated with lower AAC of 0.07 point (95% CI -0.28 - 0.14). A 0.1 mmol/L higher plasma magnesium lowered the odds of detecting any AAC by 30% (OR = 0.63; 95% CI 0.29-1.37). After 1 year and 4 years (at time of X-ray) of follow-up this association was attenuated (OR = 0.93; 95% CI 0.61-1.43 and 0.93; 95% CI 0.60-1.45, respectively). None of these associations reached statistical significance. CONCLUSIONS: Plasma magnesium concentration at baseline is not associated with the risk for future AAC. Interventions increasing magnesium to avoid vascular calcification may have greatest potential in early CKD stages prior to onset of vascular calcification.

Abdominal aortic calcification in patients with CKD.

BACKGROUND: Abdominal aortic calcification (AAC) is independently associated with cardiovascular events in dialysis patients and in the general population. However, data in non-dialysis chronic kidney disease (CKD) patients are limited. We analyzed determinants and prognostic value of AAC in non-dialysis CKD patients. METHODS: We included patients with CKD not receiving renal replacement therapy from the MASTERPLAN study, a randomized controlled trial that started in 2004. In the period 2008-2009, an X-ray to evaluate AAC was performed in a subgroup of patients. We studied AAC using a semi-quantitative scoring system by lateral lumbar X-ray. We used baseline and 2-year data to find determinants of AAC. We used a composite cardiovascular endpoint and propensity score matching to evaluate the prognostic value of AAC. RESULTS: In 280 patients an X-ray was performed. In 79 patients (28 %) the X-ray showed no calcification, in 62 patients (22 %) calcification was minor (<4), while 139 patients (50 %) had moderate or heavy calcification (≥4). Older age, prior cardiovascular disease, higher triglyceride levels, and higher phosphate levels were independent determinants of a calcification score ≥4. AAC score ≥4 was independently associated with cardiovascular events, with a hazard ratio of 5.5 (95 % confidence interval 1.2-24.8). CONCLUSIONS: Assessment of AAC can identify CKD patients at higher cardiovascular risk, and may provide important information for personalized treatment. Whether this approach will ultimately translate into better outcomes remains to be answered.

Nurse practitioner care improves renal outcome in patients with CKD.

Treatment goals for patients with CKD are often unrealized for many reasons, but support by nurse practitioners may improve risk factor levels in these patients. Here, we analyzed renal endpoints of the Multifactorial Approach and Superior Treatment Efficacy in Renal Patients with the Aid of Nurse Practitioners (MASTERPLAN) study after extended follow-up to determine whether strict implementation of current CKD guidelines through the aid of nurse practitioners improves renal outcome. In total, 788 patients with moderate to severe CKD were randomized to receive nurse practitioner support added to physician care (intervention group) or physician care alone (control group). Median follow-up was 5.7 years. Renal outcome was a secondary endpoint of the MASTERPLAN study. We used a composite renal endpoint of death, ESRD, and 50% increase in serum creatinine. Event rates were compared with adjustment for baseline serum creatinine concentration and changes in estimated GFR were determined. During the randomized phase, there were small but significant differences between the groups in BP, proteinuria, LDL cholesterol, and use of aspirin, statins, active vitamin D, and antihypertensive medications, in favor of the intervention group. The intervention reduced the incidence of the composite renal endpoint by 20% (hazard ratio, 0.80; 95% confidence interval, 0.66 to 0.98; P=0.03). In the intervention group, the decrease in estimated GFR was 0.45 ml/min per 1.73 m(2) per year less than in the control group (P=0.01). In conclusion, additional support by nurse practitioners attenuated the decline of kidney function and improved renal outcome in patients with CKD.

Validation of the kidney failure risk equation in European CKD patients.

BACKGROUND: Patients with chronic kidney disease (CKD) are at risk for progression to kidney failure. Using data of Canadian CKD patients, Tangri et al. recently developed models to predict the progression of CKD stages 3-5 to kidney failure within 5 years. We validated this kidney failure risk equation (KFRE) in European CKD patients. METHODS: We selected non-transplanted patients with CKD stages 3-5 who participated in the MASTERPLAN study, a randomized controlled trial in patients with CKD. Kidney failure was defined as the initiation of chronic dialysis or kidney transplantation within 5 years. Patients who died before kidney failure were censored. Patients followed for <5 years, who did not develop kidney failure and did not die, were excluded. The 5-year kidney failure risk was predicted using three different models developed by Tangri et al. and compared with the actual kidney failure rate in MASTERPLAN. Model performance was evaluated using the area under the receiver operating characteristic curve (ROC-AUC), the net reclassification index (NRI) and by comparing the observed and predicted rates of kidney failure. RESULTS: A total of 595 patients were included; 114 developed kidney failure. (Overall observed kidney failure risk in our cohort was 5% lower than in the Canadian validation cohort.) Discrimination of the eight-variable model [including age, sex, estimated glomerular filtration rate (eGFR), albuminuria, calcium, phosphate, bicarbonate, albumin] was similar to that of the four-variable model (including age, sex, eGFR, albuminuria) and the three-variable model (including age, sex, eGFR); ROC-AUCs were 0.89 [95% confidence interval (CI) 0.86-0.92], 0.88 (95% CI 0.85-0.91) and 0.88 (95% CI 0.85-0.92), respectively. Using the NRI, the eight-variable model slightly outperformed the four-variable model (NRI 6.5%) and the three-variable model (NRI 12.4%). The mean differences between the observed and predicted kidney failure risk were -4.0, -7.1 and -7.4% for the eight-, four-, and three-variable model, respectively. CONCLUSIONS: The KFRE accurately predicted the progression to kidney failure in European CKD patients. Discrimination of the three models was similar. Calibration of the eight-variable model was slightly better than that of the simpler models. We question whether this outweighs its added complexity.

Differences between hospitals in attainment of parathyroid hormone treatment targets in chronic kidney disease do not reflect differences in quality of care.

BACKGROUND: Transparency in quality of care (QoC) is stimulated and hospitals are compared and judged on the basis of indicators of performance on specific treatment targets. In patients with chronic kidney disease, QoC differed significantly between hospitals. In this analysis we explored additional parameters to explain differences between centers in attainment of parathyroid hormone (PTH) treatment targets. METHODS: Using MASTERPLAN baseline data, we selected one of the worst (center A) and one of the best (center B) performing hospitals. Differences between the two centers were analyzed from the year prior to start of the MASTERPLAN study until the baseline evaluation. Determinants of PTH were assessed. RESULTS: 101 patients from center A (median PTH 9.9 pmol/l, in 67 patients exceeding recommended levels) and 100 patients from center B (median PTH 6.5 pmol/l, in 34 patients exceeding recommended levels), were included. Analysis of clinical practice did not reveal differences in PTH management between the centers. Notably, hyperparathyroidism resulted in a change in therapy in less than 25% of patients. In multivariate analysis kidney transplant status, MDRD-4, and treatment center were independent predictors of PTH. However, when MDRD-6 (which accounts for serum urea and albumin) was used instead of MDRD-4, the center effect was reduced. Moreover, after calibration of the serum creatinine assays treatment center no longer influenced PTH. CONCLUSIONS: We show that differences in PTH control between centers are not explained by differences in treatment, but depend on incomparable patient populations and laboratory techniques. Therefore, results of hospital performance comparisons should be interpreted with great caution.