The authors have declared that no competing interests exist.
Conceived and designed the experiments: SL ZM. Performed the experiments: SL LD MT CR. Analyzed the data: SL LD MD. Wrote the paper: SL LD ZM. Patients' inclusion: GC.
Although a variety of non-invasive methods for measuring cardiovascular (CV) risk (such as carotid intima media thickness, pulse wave velocity (PWV), coronary artery and aortic calcification scores (measured either by CT scan or X-ray) and the ankle brachial index (ABI)) have been evaluated separately in chronic kidney disease (CKD) cohorts, few studies have evaluated these methods simultaneously. Here, we looked at whether the addition of non-invasive methods to traditional risk factors (TRFs) improves prediction of the CV risk in patients at different CKD stages.
We performed a prospective, observational study of the relationship between the outputs of non-invasive measurement methods on one hand and mortality and CV outcomes in 143 patients at different CKD stages on the other. During the follow-up period, 44 patients died and 30 CV events were recorded. We used Cox models to calculate the relative risk for outcomes. To assess the putative clinical value of each method, we also determined the categorical net reclassification improvement (NRI) and the integrated discrimination improvement.
Vascular calcification, PWV and ABI predicted all-cause mortality and CV events in univariate analyses. However, after adjustment for TRFs, only aortic and coronary artery calcification scores were found to be significant, independent variables. Moreover, the addition of coronary artery calcification scores to TRFs improved the specificity of prediction by 20%.
The addition of vascular calcification scores (especially the coronary artery calcification score) to TRFs appears to improve CV risk assessment in a CKD population.
Cardiovascular disease (CVD) has become a major cause of morbidity and a leading contributor to mortality [
Chronic kidney disease (CKD) is associated with a high incidence of cardiovascular (CV) mortality [
Over an 18-month period (from January 2006 to June 2007), 143 patients at various stages of CKD were recruited by the Nephrology Department at Amiens Hospital (Amiens, France). The present study was approved by the local investigational review board (
The inclusion criteria included age over 40, close monitoring by a nephrologist, and CKD, as defined by (i) two estimated glomerular filtration rates < 90 ml/min per 1.73 m2 (calculated according to Cockcroft and Gault's equation) at a 3– to 6–month interval [
The main exclusion criteria were the presence of chronic inflammatory disease, atrial fibrillation, complete heart block, abdominal aorta aneurysm, an aortic and/or femoral artery prosthesis, primary hyperparathyroidism, kidney transplantation or any acute CV event in the three months prior to screening.
One hundred and forty-three patients were day-hospitalized for research purposes: laboratory blood tests, blood pressure measurements, IMT, PWV, and ABI determinations, a lateral lumbar X-ray and a multislice spiral computed tomography (CT) scan (to determine CV calcification).
Hemodialysis patients were examined on a dialysis-free day or, if this was not possible, the morning before a dialysis session. These patients underwent a four-hour, standard hemodialysis session three times a week. A patient interview focused on comorbidities, the disease history (especially previous CV events), concomitant medications, and TRFs (age, gender, diabetes, triglyceride levels, hypertension, and smoking status). The patient’s medical files were reviewed in order to gather more exhaustive information. Previous CVD was defined as a history of any of the following events in the patient's medical records: myocardial infarction, stroke, heart failure, angina pectoris or surgical procedures for angina or coronary/peripheral artery disease (including percutaneous transluminal angioplasty). Hypertension was defined as treatment with at least one antihypertensive agent. Diabetes mellitus was defined as treatment with insulin or oral antidiabetic medications.
Blood samples were collected on the morning of the study day (before any other investigations), prepared and then stored at -80°C. All assays were performed on subsequently thawed plasma or serum samples.
Serum total calcium, phosphate, albumin, LDL cholesterol, hemoglobin, creatinine and C-reactive protein levels were measured in an on-site biochemistry laboratory with standard auto-analyzer techniques (the Modular IIP system from Roche Diagnostics, Basel, Switzerland). The laboratory's normative range of phosphate concentrations was 0.8–1.45 mmol/l. Serum intact parathyroid hormone and 25 hydroxyvitamin D levels were assayed with a chemiluminometric immunoassay (the Liaison N-tact PTH CLIA and the Liaison 25 OH vitamin D TOTAL CLIA [which measures both D2 and D3], Diasorin, Stillwater, MN). Serum 1.25 (OH)2 vitamin D levels were determined in an RIA (125I RIA, Diasorin). Serum cystatin C (Cys C) levels were determined by immunonephelometry (N latex Cystatin C, Siemens, Erlangen, Germany) and serum creatinine (Scr) levels were measured using the Jaffe method based on standard isotope-dilution mass spectrometry (
The IMT was measured semi-automatically from carotid ultrasound data using dedicated software (M'Ath, Intelligence in Medical Technologies SARL, Paris, France). All measurements were performed by the same sonographer. Using an automated edge detection algorithm, the IMT was measured along a 10 mm-long segment of the far wall of the common carotid artery (CCA, at a site free of any discrete plaques) and corresponded to the distance between the lumen-intima interface and the media-adventitia interface. A mean of 50 measurements were automatically performed on each image (two images per body side) and on each body side (left and right). The greatest measured values for the right and left CCA-IMTs were used in the analysis. Data on reproducibility have been previously published by our group; the correlation coefficient for repeated readings of the CCA-IMT was 0.96 [
The PWV between the carotid and femoral arteries was determined transcutaneously by trained physicians, using an automatic, dedicated, validated device (Complior Colson, Createch Industrie, Massy, France), as previously described [
The ABI was calculated after the participant had rested in the supine position for 5 minutes. A hand-held Doppler probe was used to measure the systolic pressures at the right brachial artery, right posterior tibial artery, left posterior tibial artery and left brachial artery (in that order). According to a previously validated method, the ABI was calculated as the ratio of brachial to ankle artery pressure for each leg. The lower of the two values was subsequently analyzed (unless the ABI was 1.3 or more, in which case the higher value was selected).[
A technique similar to that described by Kauppila et al. [
In order to quantify the presence and extent of aortic and coronary artery calcifications, each patient underwent a multislice spiral CT scan. All examinations were performed with a 64-detector CT scanner (Lightspeed VCT, GE Healthcare, Milwaukee, WI). Detailed technical information on the procedure has been provided elsewhere[
Patients were followed up prospectively for the occurrence of non-fatal CV events or all-cause death (whichever occurred first). A total of 64 events (composite endpoints) were analyzed. Cardiovascular-related hospitalizations and deaths were collected prospectively every six months and adjudicated by two nephrologists. In each case, the patient's medical records were reviewed and the cause of death or the CV event was assigned on the basis of all the available clinical information. For out-of-hospital deaths, the patient’s family doctor was interviewed to obtain pertinent information on the cause. The following criteria were used for the adjudication: angina pectoris was defined as symptoms with objective evidence of ischemia (electrocardiogram or coronary artery angiography); adjudication as congestive heart failure had to be supported by a physician's diagnosis or treatment for heart failure, pulmonary congestion or cardiac dysfunction.
Cardiovascular mortality was defined as any death directly to CV system dysfunction (stroke, myocardial infarction, congestive heart failure or sudden death). Non-fatal CV events were defined as systemic CV dysfunction (stroke, angina pectoris, myocardial infarction, congestive cardiac failure, peripheral ischemia or new-onset arrhythmia) or surgical procedures for angina or coronary/peripheral artery disease. When several events occurred in the same patient, only the time to the first event was considered in our analysis.
Data were expressed as the mean ± SD, median and range or frequency, as appropriate. In the study population, patients were stratified according to the presence or absence of events. Intergroup comparisons were performed with a chi-squared test for categorical variables and Student’s t test or the Mann-Whitney test for continuous variables. The Kaplan-Meier method was used to estimate percentage survival as a function of the presence or absence of the composite factor (a CV event or death). Survival curves were compared in a log-rank test. Putative associations between clinical factors, biological factors and mortality were assessed in univariate and multivariate Cox models. The proportional hazard assumption was checked with the Kolmogorov-type supremum test. In the multivariate analysis, the initial model included TRFs only: age, gender, diabetes, triglyceride level, hypertension, and smoking status. In the additional models (Models 2 to 7), the TRFs were supplemented with the various non-invasive measurements. The discriminant ability of the seven Cox models was assessed with Harrell’s C-index [
The threshold for statistical significance was set to p≤0.05. All statistical analyses were performed using SPSS software (version 18.0, SPSS Inc., Chicago, IL) for Windows (Microsoft Corp, Redmond, WA) and SAS software (version 9.2, SAS Institute Inc., Cary, NC).
The main characteristics of the 143 CKD patients (grouped according to the occurrence or non-occurrence of the composite outcome, i.e. a CV event or death) are summarized in
Relationship between the aortic calcification scores based on a CT scan or on X-ray data (n = 143, r2 = 0.761, p>0.001).
No event (n = 79) | Events(n = 64) | p | |
---|---|---|---|
Male gender, n (%) | 43 (54.4) | 44 (68.8) | 0.088 |
BMI, kg/m |
28.6 ± 6 | 28 ± 7 | 0.565 |
Diabetes status, n (%) | 32 (40.5) | 29 (45.3) | 0.612 |
Smoking status, n (%) | 9 (11.5) | 8 (12.9) | 0.801 |
Systolic blood pressure, mmHg | 151 ± 24 | 156 ± 29 | 0.256 |
ABI | 1.14 ± 0.3 (1.09; 1–1.18) | 1.22 ± 0.5 (1.09; 0.96–1.39) | 0.266 |
2 | 11 (13.9) | 1 (1.6) | |
3 | 22 (27.8) | 15 (23.4) | |
4 | 22 (27.8) | 15 (23.4) | |
5 | 5 (6.3) | 5 (7.8) | |
5D | 19 (24.1) | 28 (43.8) | |
ACEI | 13 (20.3) | 15 (19) | 0.844 |
ARB | 37 (57.8) | 49 (62) | 0.137 |
Beta-blockers | 32 (40.5) | 31 (48.4) | 0.347 |
Diuretics | 26 (40.6) | 42 (53.2) | 0.613 |
Calcium antagonist | 31 (39.2) | 26 (40.6) | 0.868 |
Vitamin D supplementation | 29 (36.7) | 22 (34.4) | 0.774 |
Sevelamer | 10 (12.7) | 16 (25.0) | 0.065 |
ESA | 24 (30.4) | 29 (45.3) | 0.069 |
Lipid lowering therapy | 34 (53.1) | 53 (67.1) | 0.092 |
Calcium, mmol/l | 2.3 ± 0.2 | 2.3 ± 0.2 | 0.167 |
Phosphate, mmol/l | 1.23 ± 0.42 (1.15; 1.03–1.38) | 1.35 ± 0.49(1.26; 1.02–1.63) | 0.127 |
LDL cholesterol, mmol/l | 2.6 ± 0.9 | 2.7 ± 0.9 | 0.762 |
Total cholesterol, mmol/l | 4.9 ± 1.2 | 4.9 ± 1.2 | 0.815 |
Triglycerides, mmol/l | 2.1 ± 1.6 (1.6; 1.2–2.6) | 2.1 ± 1.1 (1.8; 1.2–2.6) | 0.857 |
Intact parathyroid hormone, pg/ml | 145 ± 163 (80; 42–193) | 126 ± 96 (87; 52–173) | 0.394 |
C-reactive protein, mg/l | 8.8 ± 22.5 (2.3; 1.1–6.6) | 14.1 ± 25.4 (4.0; 1.5–13.9) | 0.186 |
Interleukin 6, pg/ml | 4.0 ± 5.1 (2.1; 0.9–5.8) | 6.6 ± 9.9 (3.8; 1.9–7.0) | 0.710 |
Abbreviation: BMI: body mass index; ABI: ankle-brachial index; CKD: chronic kidney disease, AUs: Agatston units, ACEI: angiotensin-converting-enzyme inhibitors, ARB: Angiotensin receptor blockers, ESA: erythropoietin stimulating agent, LDL: low-density lipoprotein.
CKD stages were evaluated according to the glomerular filtration rate estimated with the CKD-EPI equation.
Non-Gaussian variables are expressed as the mean ± SD (median; 25th-75th quartiles)
IMT | PWV | Aortic calcification score (CT scan) | Aortic calcification score (X-ray) | Coronary artery calcification | ABI | ||
---|---|---|---|---|---|---|---|
IMT | r | -0.159 | |||||
p value | 0.100 | ||||||
PWV | r | -0.071 | |||||
p value | 0.428 | ||||||
Aortic calcification score (CT scan) | r | -0.051 | |||||
p value | 0.583 | ||||||
Aortic calcification score (X-ray) | r | -0.078 | |||||
p value | 0.410 | ||||||
Coronary artery calcification | r | 0.010 | |||||
p value | 0.929 | ||||||
ABI | r | -0.159 | -0.071 | -0.051 | -0.078 | 0.010 | |
p value | 0.100 | 0.428 | 0.583 | 0.410 | 0.929 |
Abbreviations: IMT: intima-media thickness; PWV: pulse wave velocity; ABI: ankle brachial index.
During the follow-up period (mean duration: 873 ± 393 days), 44 patients died (24 from cardiovascular causes, from 12 infectious diseases and 8 from other causes) and 30 patients had CV events leading to 64 composite endpoints for analysis. In a crude analysis (
The various Cox regression models (
The adjusted Cox models' respective abilities to predict outcome with the different non-invasive methods are presented in
Model 1, traditional risk factors (TRFs): 0.67 ± 0.35; Model 2, TRFs + PWV: 0.67 ± 0.036; Model 3, TRFs + IMT: 0.69 ± 0.036; Model 4, TRFs + aortic calcification score (CT scan): 0.70 ± 0.036; Model 5, TRFs + aortic calcification score (X-ray): 0.71 ± 0.05; Model 6, TRFs + coronary artery calcification score: 0.70 ± 0.036; Model 7, TRFs + ABI (<1.3 vs. >1.3) 0.69 ± 0.035. All differences were non-significant.
RR | 95%CI | p | |
---|---|---|---|
Triglycerides | 0.975 | 0.822–1.157 | 0.776 |
Diabetes | 0.969 | 0.514–1.828 | 0.923 |
Hypertension | 0.600 | 0.267–1.350 | 0.217 |
Smoking status | 1.505 | 0.657–3.451 | 0.334 |
Triglycerides | 0.973 | 0.813–1.165 | 0.767 |
Diabetes | 0.913 | 0.483–1.726 | 0.779 |
Hypertension | 0.601 | 0.267–1.350 | 0.217 |
Smoking status | 1.535 | 0.671–3.510 | 0.310 |
PWV | 1.070 | 0.988–1.159 | 0.097 |
Triglycerides | 0.980 | 0.817–1.174 | 0.823 |
Diabetes | 0.874 | 0.409–1.869 | 0.728 |
Hypertension | 0.989 | 0.298–3.280 | 0.985 |
Smoking status | 1.081 | 0.361–3.241 | 0.889 |
IMT | 0.699 | 0.085–5.775 | 0.739 |
Age | 1.020 | 0.990–1.051 | 0.198 |
Diabetes | 1.003 | 0.491–2.050 | 0.992 |
Triglycerides | 0.959 | 0.794–1.158 | 0.660 |
Smoking status | 1.009 | 0.396–2.574 | 0.985 |
Model 5: |
|||
Diabetes | 0.887 | 0.442–1.782 | 0.737 |
Hypertension | 0.395 | 0.157–0.995 | 0.062 |
Triglycerides | 0.937 | 0.773–1.136 | 0.509 |
Smoking status | 1.134 | 0.364–3.527 | 0.828 |
Aortic calcification score (X-ray) | 1.029 | 0.989–1.071 | 0.153 |
Gender | 0.830 | 0.370–1.860 | 0.650 |
Diabetes | 0.772 | 0.285–2.088 | 0.610 |
Hypertension | 0.382 | 0.127–1.152 | 0.088 |
Triglycerides | 1.000 | 0.811–1.233 | 0.998 |
Smoking Status | 2.591 | 0.906–7.404 | 0.076 |
Gender | 0.640 | 0.357–1.145 | 0.133 |
Hypertension | 0.610 | 0.253–1.473 | 0.272 |
Triglycerides | 0.980 | 0.815–1.177 | 0.826 |
Smoking status | 1.546 | 0.641–3.732 | 0.332 |
Ankle brachial index | 1.483 | 0.756–2.908 | 0.252 |
IMT: intima media thickness; PWV: pulse wave velocity; RR: risk ratio; CI: confidence interval. TRFs (traditional risk factors): age (in 1-year increments), gender, diabetes, triglyceride level (in 1 mmol/l increments), hypertension, and smoking status. Coronary calcification severity was considered in 100 AU increments.
The NRI was calculated in order to assess the putative clinical utility of the aortic calcification score (evaluated from the CT scan) and the coronary artery calcification score as markers of CV risk when combined with TRFs (
Predictors | IDI (95% CI) | NRI (95% CI) | |
---|---|---|---|
Event | Nonevent | ||
aortic calcification score (CT scan) | 0.04 (-0.004;0.075) | 0.05 (-0.02;0.12) | 0.06 (-0.04;0.16) |
coronary artery calcification score | 0.08 (-0.03;0.19) |
Abbreviations: CI: confidence interval; NRI: net reclassification improvement; IDI: integrated discrimination improvement.
At present, only TRFs are routinely evaluated as predictors of CV events, CV mortality and all-cause mortality. Some studies have shown that addition of a non-invasive measurement to these TRFs improves the predictive value in the general population and in CKD patients [
It is noteworthy that in our study population, the IMT and PWV did not have predictive value for CVD events and mortality–even after adjustment for TRFs (
In contrast, a study of 438 hemodialysis patients with end-stage renal disease reported that carotid artery IMT is an independently predictor of CV mortality [
It is important to note that the evaluation of vascular calcification adds new information for the prediction and thus the potential prevention of all-cause mortality or CV events. Indeed, patients with an elevated aortic/coronary artery calcification score have an elevated risk of mortality and CV events—regardless of TRFs. Moreover, our evaluation of the coronary artery calcification score increased the specificity of risk reclassification of CKD patients. We also observed a very strong correlation between the two radiologic methods used to derive the aortic calcification scores (X-rays and a CT scan). The X-ray-based evaluation of aortic calcification is a relative simple tool and could be easily performed routinely in CKD populations. Matsushita et al. evaluated a number of methods (IMT, the ABI and a coronary artery calcium score) likely to improve CV risk prediction in 6553 multi-ethnic participants (including subjects with CKD) [
Our study had some limitations, including the relatively small cohort size, the relatively small number of CV events and deaths and the lack of data on proteinuria. However, we used composite criteria to overcome this limitation. In contrast, the study's main strength relates to the simultaneous use of several methods to evaluate atherosclerosis/arteriosclerosis.
In conclusion, we have highlighted a simple, non-invasive diagnostic tool that may be capable of improving CV risk assessment (when compared with TRFs alone) in patients with CKD. Patients with high vascular calcification scores (and especially a high coronary artery calcification score) can be considered as having the highest CV risk. However, the present results should be confirmed in larger cohorts.
This study was funded by a grant from Amiens University Medical Center (PHRC: 2006/0100 (27 March 2006)).