Abstract
Background and objectives: Intracranial artery calcification (IAC) is frequently observed on brain computed tomography (CT) scans in stroke patients. This retrospective study was designed to determine the prevalence, risk factors, and clinical relevance of IAC in a cohort of patients with ischemic stroke.
Design, setting, participants, & measurements: We included all eligible patients admitted to Amiens University Hospital for acute ischemic stroke between January and December 2006 and assessed using 64-slice multidetector-row CT (n = 340). Patients were classified according to the presence or absence of IAC in the internal carotid arteries, middle cerebral arteries, vertebral arteries, and basilar artery. GFR was estimated using the MDRD equation. Chronic kidney disease (CKD) was defined as a GFR < 60 ml/min/1.73 m2. We also studied a control group of patients admitted for neurologic diseases other than stroke.
Results: Two hundred fifty-nine stroke patients (76.2%) displayed IAC, which was independently associated with carotid atherosclerosis > 50%, age, and GFR. One hundred three nonstroke patients (60.2%) had IAC, with age, arterial hypertension, and GFR as independently associated factors. For all patients taken together, age, arterial hypertension, stroke, and GFR were independently associated with IAC.
Conclusion: These results confirm the high prevalence of IAC in patients with and without ischemic stroke and show for the first time that IAC is associated with the presence of CKD in these patients. The frequency of IAC was significantly higher in stroke patients than in nonstroke patients. The association between IAC and stroke outcome requires further investigation.
Vascular calcification is widely acknowledged to be an integral part of the atherosclerotic process and occurs in 80 to 90% of atheromatous lesions (1). Arterial calcifications have a number of adverse hemodynamic consequences that can cause cardiac, vascular, and brain diseases (2). Several studies have demonstrated that atherosclerosis in end-stage renal disease patients and in patients with less advanced CKD is more frequent than in the general population (reviewed by Vanholder et al. [3]). Furthermore, exacerbated atherosclerotic disease in patients with CKD is characterized by a high degree of medial and intimal calcification (4,5). The mechanisms by which CKD may increase vascular calcification have not been elucidated but may include factors associated with a decline in renal function, i.e., anemia, oxidative stress (6), deregulation in calcium-phosphate homeostasis, inflammatory syndrome (7), decreased nitric oxide availability (8), and conditions promoting coagulation.
Arterial calcification is an easily identifiable marker. In clinical practice, the methods used to assess vascular calcification in CKD patients include standard radiography of the aorta and iliac arteries (9,10) and echocardiography of the heart valves (11). Furthermore, the sensitive, reliable assessment of coronary artery calcification using multi-detector-row computed tomography (MDCT) (12,13) constitutes a significant step forward in the routine detection of coronary artery disease.
Vascular calcification can also be assessed in various peripheral sites from plain radiographs of the hands (9) and a head CT scan (14). Indeed, intracranial artery calcification (IAC) is frequently observed on head CT scans in stroke patients (14–16). However, the link between IAC and atherosclerosis has not been evaluated. Moreover (and to the best of our knowledge), no report has evaluated the impact of CKD on the pathogenesis of IAC. Lastly, the predictive value for IAC on the patient's outcome has not been determined. The aim of the present study was therefore to evaluate the prevalence, risk factors, and clinical relevance of IAC in a retrospective study of a cohort of ischemic stroke patients.
Materials and Methods
This retrospective study was performed in Amiens University Hospital's Department of Neurology and Stroke Unit and received Institutional Review Board approval. All patients referred for transient ischemic attack (TIA) or acute ischemic stroke between January and December 2006 (inclusive) were retrospectively screened. For each patient, clinical data were collected according to a standardized protocol (17). Computed tomography, electrocardiogram (ECG), cervical Doppler ultrasonography, transthoracic echocardiography, and standard laboratory tests were performed in all patients on admission. Transoesophageal echocardiography, specialized laboratory tests, Holter ECG monitoring, magnetic resonance imaging, and/or angiography were performed in selected patients.
A total of 379 consecutive ischemic stroke patients were admitted to the Neurology Department during 2006. Thirty-nine patients were excluded from the study: 8 died prematurely, 7 had been referred from another hospital where a CT scan has been performed, and 24 had missing data (LDL cholesterol [LDL-c]: n = 17; body mass index [BMI]: n = 7). The remaining 340 patients were included.
The following variables concerning the acute stage of ischemic stroke were collected: age, gender, cause of ischemic stroke (according to the TOAST criteria (18)) and previously identified stroke risk factors or those discovered during hospitalization, including hypertension (antihypertensive treatment or systolic BP > 140 mmHg or diastolic BP > 90 mmHg before hospitalization), diabetes (insulin or oral antidiabetic therapy or fasting blood glucose > 7 mmol/L on two occasions during hospitalization), hyperlipidemia (lipid lowering treatment or LDL-c > 1 g/L), coronary artery disease (defined as a known history of myocardial infarction or angina), current smoking, regular alcohol consumption (>2 alcoholic drinks daily), peripheral artery disease, and BMI (kg/m2). The serum C-reactive protein (CRP) concentration was also recorded. The GFR was estimated using the four-component Modification of Diet in Renal Disease (MDRD) equation, which is based on age, gender, race, and serum creatinine concentration determined on admission (19). The presence of CKD was defined as a GFR <60 ml/min/1.73 m2, in accordance with the National Kidney Foundation criteria (20).
All CT examinations were performed on a 64-slice MDCT system (0.625 mm maximum slice thickness, with no intersection gap). Bone window CT images covered the whole brain (from the skull base to the vertex), to identify the presence of IAC. Calcification foci were defined as hyperdense foci with a median density greater than 130 Hounsfield units (21). The scoring system was based on a modification of the method originally described by Woodcock for calcification noted in carotid angiography and then adapted by Erbay for grading intracranial carotid artery calcification on CT scans (22,23). According to our modification, grade 0 corresponds to the absence of calcifications or tiny scattered calcification foci seen on only one slice, and grade 1 corresponds to thick contiguous calcification; thick interrupted calcification; thin confluent calcification; or tiny, scattered calcification foci seen on at least two adjacent slices (Figure 1). This semiquantitative scoring system was applied to seven intracranial arteries: the right and left internal carotid arteries, the right and left middle cerebral arteries, the right and left vertebral arteries, and the basilar artery. Hence, the IAC scores ranged from 0 (no calcification) to 7 (calcification in all seven intracranial arteries examined). The anterior cerebral and posterior cerebral arteries were not evaluated because IAC in these locations is very rare (14). Two trained neurologists examined the CT scan independently to grade the calcification. Interobserver variability was assessed by blinded rereview of 50 patients: the interobserver agreement on the presence of IAC was excellent: all patients free of IAC were well categorized (κ = 1), and 46 patients had exactly the same grade of calcification; in four patients, the value differed by only one grade, and this concerned carotid arteries (right carotid artery: κ = 0.96; left carotid artery: κ = 0.92).
Figure 1.
Bone window computed tomography (CT) images illustrating the intracranial artery calcification score used. (A) CT scan showing thick, confluent calcification in both carotid siphons (score = 1 for each carotid artery. (B) CT scan showing thick, contiguous calcification in the right carotid artery (score = 1) and tiny, scattered calcification foci seen on only one slice in the left carotid artery (score = 0). (C) CT scan showing tiny, scattered calcification foci seen on at least two adjacent slices in the right middle cerebral artery (score 1) and tiny, scattered calcification foci seen on only one slice in the left middle cerebral artery (score = 0). (D) CT scan showing thick, contiguous calcification foci on both vertebral arteries (score 1 for each vertebral artery). (E) CT scan showing thick, interrupted calcification in the right vertebral artery (score = 1) and tiny, scattered calcification foci seen on only one slice in the left vertebral artery (score = 0). (F) CT scan showing thick, interrupted calcification in the basilar artery (score = 1). Arrows show calcification.
Given that hospitalization was too short (<90 d) in the majority of patients to see any differences in the modified Rankin scale (24), disability was evaluated using the length of hospitalization as an index of overall severity. The median length of hospitalization was used to dichotomize good (≤9 d) and poor (>9 d) outcomes.
To determine the prevalence of IAC in a control group, we selected patients who had been admitted for neurologic diseases other than stroke or ischemic attacks. All patients referred for nonstroke neurologic disorders from January to July 2007 were screened, and the same clinical and biochemical variables were analyzed. A total of 223 patients were admitted during this period. Fifty-two controls were subsequently excluded from the study (30 did not had a brain CT scan performed with a 64-slice MDCT and no GFR was available for 22 individuals). The remaining 171 controls were included.
Statistical Analyses
Risk factors in patients with and without IAC were compared using t test for continuous variables and χ2 tests for categorical variables. The dependent variables were: age, gender, main risk factors (hypertension, diabetes mellitus, hypercholesterolemia, ischemic heart disease, smoking, alcohol, peripheral artery disease, and BMI), previous stroke or TIA, CKD, causes of ischemic stroke (according to the TOAST criteria (18)), LDL-c, CRP, GFR, and log-transformed CRP levels. Stepwise backward logistic regression analysis was used to select independent variables predicting the presence of IAC (absence = grade 0; presence = grade ≥1). Pertinent variables selected in a univariate analysis with P < 0.1 (age, length of hospitalization, hypertension, smoking, diabetes mellitus, coronary artery disease, peripheral artery disease, carotid atherosclerosis > 50%, cardioembolic stroke, GFR, fasting glucose, and CRP levels) were tested in a multivariate analysis, and adjusted odd ratios (ORs) and 95% confidence intervals (CIs) were generated. The relationships between the degree of renal function according to National Kidney Foundation subgroups (defined as follows: stage I: GFR: ≥ 90 ml/min; stage II: GFR between 60 and 89 ml/min; stage III: GFR between 30 and 59 ml/min; stage IV: GFR between 15 and 29 ml/min; stage V: GFR < 15 ml/min) and IAC scores were examined in a separate analysis. A second series of analyses examined the predictors of overall stroke severity, as indexed by the length of hospitalization. The dependent variables were: age, gender, vascular risk factors, causes of ischemic stroke (according to the TOAST criteria (18)), IAC, and renal clearance. Stepwise forward logistic regression analyses were performed as described above, using the length of hospitalization (≤9 d, >9 d) as the dependent variable. Similar statistical analysis were performed in the population of patients with nonstroke disorders (n = 171) and in the entire population (i.e., pooled stroke and nonstroke patients, n = 511) to examine factors predicting the presence of IAC. P values < 0.05 were considered to be statistically significant. All statistical analyses were performed with SPSS statistical software.
Results
Stroke Patients (n = 340)
Two hundred fifty-nine patients (76.2%) displayed IAC. The highest prevalence of IAC was seen in internal carotid arteries (72.9%; right: 66.5%; left: 62.6%), followed by vertebral arteries (37.3%; right: 25.0%; left: 26.5%). A similar prevalence of IAC was observed in the middle cerebral (4.4%; right: 6.7%; left: 3.8%) and basilar (3.5%) arteries.
Patient characteristics according to the presence of IAC are listed in Table 1. On the basis of a univariate analysis, patients with IAC were older and had more hypertension, diabetes mellitus, coronary artery disease, peripheral artery disease, carotid atherosclerotic disease > 50%, cardioembolic stroke, and CKD. The GFR was significantly lower in patients with IAC, whereas serum creatinine, fasting blood glucose, and LDL-c levels were significantly higher (Table 2). A significant association between the IAC score and the MDRD subgroups was also observed (Figure 2). Stepwise logistic regression selected the following independent factors for IAC: age (OR: 2.7 every 10 yr; 95% CI: 2.1 to 3.6; P < 0.001), carotid stenosis > 50% (OR: 5.9; 95% CI: 1.3 to 16.1; P = 0.02), and GFR (OR: 0.82 for every decrease of 10 ml/min/1.73 m2; 95% CI: 0.70 to 0.99; P = 0.014).
Table 1.
Results of univariate analysis: Demographic and clinical characteristics of the stroke population, according to the presence or absence of intracranial artery calcification (IAC)
| Characteristic | All patients (n = 340) | No IAC (n = 81) | IAC (n = 259) | P |
|---|---|---|---|---|
| Age (years) | 65.7 ± 13.6 | 52.4 ± 13.6 | 69.8 ± 10.6 | <0.001 |
| Number of males | 193 (56.8) | 48 (59.3) | 145 (56.0) | 0.70 |
| Length of hospitalization (days) | 12.9 ± 12.3 | 10.0 ± 9.5 | 13.7 ± 13.5 | 0.007 |
| Previous main risk factors | ||||
| hypertension | 233 (68.5) | 40 (49.4) | 193 (74.5) | <0.001 |
| diabetes mellitus | 125 (36.7) | 20 (24.7) | 105 (40.5) | 0.012 |
| dyslipidaemia | 301 (88.5) | 73 (90.1) | 228 (88) | 0.69 |
| smoking | 77 (22.6) | 24 (29.6) | 53 (20.5) | 0.09 |
| CAD | 50 (14.7) | 5 (6.2) | 45 (17.4) | 0.012 |
| PAD | 35 (10.3) | 2 (2.5) | 33 (12.7) | 0.006 |
| stroke/TIA | 57 (16.8) | 14 (17.3) | 43 (16.6) | 0.86 |
| BMI (kg/m2) | 27 ± 5 | 26.6 ± 4.1 | 26.9 ± 4.7 | 0.56 |
| Causes of ischemic stroke | ||||
| atherosclerosis > 50% | 55 (16.2) | 2 (2.5) | 53 (20.5) | <0.001 |
| cardioembolic | 87 (25.6) | 7 (8.6) | 80 (30.9) | <0.001 |
| lacunar | 48 (14.1) | 13 (16.0) | 35 (13.5) | 0.58 |
| undetermined | 163 (47.9) | 53 (65.4) | 110 (42.5) | <0.001 |
| other | 20 (5.9) | 9 (11.1) | 11 (4.2) | 0.03 |
Results are presented either as means ± standard deviation (age and length of hospitalization) or as n (%) with n = number of patients and % = percentage of patients in the group. NS, nonsignificant; CAD, coronary artery disease; PAD, peripheral artery disease; TIA, transient ischemic attack; BMI, body mass index.
Table 2.
Laboratory parameters for the stroke population, according to the presence or absence of intracranial artery calcification (IAC)
| Parameter | All patients (n = 340) | No IAC (n = 81) | IAC (n = 259) | P |
|---|---|---|---|---|
| CKD | 92 (27.1) | 4 (4.9) | 88 (34.0) | <0.001 |
| Creatinine (μmo/L) | 94.6 ± 39.6 | 82.7 ± 16 | 98.3 ± 22 | 0.001 |
| GFR (ml/min/1.73m2) | 72.1 ± 21.7 | 82.2 ± 12.4 | 68.9 ± 17.9 | <0.001 |
| Fasting glucose (mM) | 5.7 ± 1.6 | 5.35 ± 1.1 | 5.82 ± 1.7 | 0.005 |
| LDL-c (g/L) | 1.24 ± 0.4 | 1.19 ± 0.4 | 1.37 ± 0.4 | 0.001 |
| CRP (log) | 1.2 ± 1.4 | 1.06 ± 1.2 | 1.22 ± 1.4 | 0.37 |
| Serum calcium (mM) | 2.26 ± 0.12 | 2.27 ± 0.2 | 2.25 ± 0.1 | 0.16 |
| Serum phosphate (mM) | 0.99 ± 0.2 | 1.0 ± 0.2 | 0.99 ± 0.2 | 0.64 |
| Haemoglobin (g/100 ml) | 14.1 ± 1.5 | 14.3 ± 1.6 | 14.0 ± 1.5 | 0.21 |
Results are presented either as means ± standard deviation or for CKD as n (%) with n = number of patients and % = percentage of patients in the group. NS, nonsignificant; GFR, glomerular filtration rate estimated using the four-component Modification of Diet in Renal Disease (MDRD) equation; LDL-c, low density lipoprotein cholesterol; CRP, C-reactive protein.
Figure 2.
Intracranial artery calcification (IAC) score, according to the CKD subgroups (estimated using the four-component Modification of Diet in Renal Disease (MDRD) equation) in stroke patients. Results are means ± SD; *P < 0.05 versus I, †P < 0.05 versus II. Stages are I: GFR: ≥90 ml/min; II: GFR between 60 and 89 ml/min; III: GFR between 30 and 59 ml/min; IV: GFR between 15 and 29 ml/min; V: GFR <15 ml/min)
In a univariate analysis, a longer length of hospitalization was associated with peripheral artery disease, atherosclerotic disease > 50%, IAC, age, CKD, and major cardiovascular events. However, in the stepwise logistic regression, only age was selected as an independent predictor of the length of hospitalization (OR: 1.5 every 10 yr; 95% CI: 1.2 to 1.8; P < 0.001).
Control Group (n = 171)
Indications for hospitalization in the nonstroke population are reported in Table 3. Sixty-three (36.8%) nonstroke patients had hypertension, 28 (16.4%) had dyslipidaemia, 24 (14.0%) had diabetes, and 17 (9.9%) smoked. One hundred three patients (60.2%) had IAC. Patients with IAC were older (70.3 ± 9.9 versus 55.3 ± 15.9 yr; P < 0.001) and had a lower GFR (72.4 ± 21.3 versus 92.7 ± 19.3 ml/min/1.73 m2; P < 0.001). Hypertension (P < 0.001), diabetes (P = 0.013), and CKD (P < 0.001) were also more frequent in patients with IAC. In a multivariate analysis, age (OR: 2.6 every 10 yr; 95% CI: 1.48 to 2.84; P < 0.001), hypertension (OR: 2.9; 95% CI: 1.22 to 6.70; P < 0.016), and GFR (OR: 0.74 for every decrease of 10 ml/min/1.73 m2; 95% CI: 0.60 to 0.90; P = 0.002) were found to be independently associated with IAC.
Table 3.
Indications for hospitalization in the control group
| Indication | Patients (n, %) |
|---|---|
| Cognitive disorders | 63 (36.8) |
| Seizure | 39 (22.8) |
| Multiple sclerosis | 23 (13.5) |
| Movement disorders | 18 (10.5) |
| Neuropathy | 18 (10.5) |
| Migraine | 5 (2.9) |
| Motor neuron diseases | 4 (2.4) |
| Tumor | 1 (0.6) |
| Total | 171 (100) |
All Patients (N = 511)
The patients’ characteristics according to the presence of IAC are listed in Table 4. In a univariate analysis, patients with IAC were significantly older and were more likely to have vascular risk factors (hypertension, diabetes mellitus, coronary artery disease, peripheral artery disease, carotid atherosclerotic disease > 50%, cardioembolic stroke) and CKD. In addition, the frequency of IAC was significantly higher in stroke patients than in nonstroke patients. Age (OR: 2.6 every 10 yr; 95% CI: 1.10 to 3.11; P < 0.001), hypertension (OR: 1.7; 95% CI: 1.01 to 2.76; P = 0.044), stroke (OR: 1.89; 95% CI: 1.13 to 3.14; P < 0.014), and GFR (OR: 0.82 for every decrease of 10 ml/min/1.73 m2; 95% CI: 0.73 to 0.90; P = 0.001) were found to be independently associated with IAC.
Table 4.
Results of univariate analysis: Demographic and clinical characteristics of all patients, according to the presence or absence of intracranial artery calcification (IAC)
| Characteristic | All patients (N = 511) | No IAC (n = 149) | IAC (n = 362) | P |
|---|---|---|---|---|
| Age (years) | 65.2 ± 14.0 | 53.7 ± 14.8 | 69.9 ± 10.5 | <0.001 |
| Male gender | 279 (54.6) | 85 (57.0) | 194 (53.6) | 0.49 |
| Hypertension | 287 (55.8) | 49 (32.9) | 238 (65.7) | <0.001 |
| Diabetes mellitus | 96 (18.8) | 13 (8.7) | 83 (22.9) | <0.001 |
| Dyslipidaemia | 166 (32.5) | 33 (22.1) | 133 (36.7) | 0.001 |
| Smoking | 94 (18.4) | 32 (21.5) | 62 (17.1) | 0.26 |
| PAD | 35 (6.8) | 2 (1.3) | 33 (9.2) | 0.001 |
| CAD | 66 (12.9) | 10 (6.7) | 56 (15.5) | 0.008 |
| CKD | 122 (23.9) | 5 (3.4) | 117 (32.3) | <0.001 |
| GFR | 74.9 ± 22.4 | 87.0 ± 18.3 | 69.9 ± 22.1 | <0.001 |
| Stroke | 340 (66.5) | 81 (54.4) | 259 (71.5) | <0.001 |
Results are presented either as means ± standard deviation (age and GFR) or as n (%) with n = number of patients and % = percentage of patients in the group. CAD, coronary artery disease; PAD, peripheral artery disease; GFR, glomerular filtration rate estimated using the four-component Modification of Diet in Renal Disease equation.
Discussion
The present study confirms the high prevalence of IAC in patients with ischemic stroke. It shows for the first time that IAC is associated not only with aging and severe atherosclerosis but also with the presence of CKD. Lastly, IAC was associated with increased length of hospitalization in a univariate analysis but not in a multivariate analysis. We also found a high prevalence of IAC in nonstroke patients, although with lower frequency than was observed in stroke patients. Furthermore, the association between IAC and CKD is not restricted to patients hospitalized for stroke but is also found in a population of patients hospitalized for other neurologic disorders.
The prevalence of IAC in stroke patients in the present study (76.2%) was higher than that observed in work by Sohn et al. (40%) (16). This discrepancy may be due to the different methods used to determine IAC; Sohn et al. used conventional CT with a slice thickness of 5 mm, whereas we used the more sensitive 64-slice MDCT (16). In contrast, a more recent study performed in China with the same technique as used here (i.e. MDCT) reported a higher prevalence of IAC (92%) in patients with ischemic stroke (15). This finding cannot be attributed to a difference in the mean age of the patients (which was similar in the two studies) but may be related to the fact that intracranial atherosclerosis is more frequent in Chinese patients than in Caucasian populations (25). An additional explanation may be related to the difference in CT attenuation threshold used, because it has been suggested that a CT attenuation threshold of at least 130 Hounsfield units is needed to adequately resolve calcification from the surrounding tissues (26). Chen et al. (14) used a lower limit of over 90 and may thus have overestimated the calcification.
In the present study, age was found to be a risk factor associated with IAC. The increasing prevalence of IAC with advanced age has already been reported and might reflect the progressive development of atherosclerosis (27). We also found a strong association between IAC and carotid atherosclerotic stenosis, one of the most well defined stroke vascular risk factors. Previous studies have shown a similar association between stroke vascular risk factors and IAC in stroke-free patients (14,28).
Although aortic and coronary calcification is a strong predictor of cardiovascular morbidity and mortality, the clinical significance of IAC remains unclear. Some investigators indicate that vascular calcification is a marker of atherosclerotic plaque burden (13,29), whereas others have reported that calcified carotid atherosclerotic plaques are associated with fewer ischemic symptoms than noncalcified carotid atherosclerotic plaques (21,30). IAC was recently shown to be a risk factor for ischemic stroke in a Chinese population (15). In contrast, other studies report that IAC does not seem to play a major role in cerebral infarcts (31,32). Only Erbay et al. reported a partial association between acute small vessel cerebral infarcts and high-grade internal carotid calcification (22). The latter authors suggested that IAC may be a marker for intracranial artery stenosis, an uncommon cause of ischemic stroke. However, a recent histologic study of atherosclerotic stenosis in the middle cerebral artery did not support this hypothesis, because only the degree of luminal stenosis, lipid area, and neovasculature were found to be predictors of cerebrovascular events (33).
We also found a high prevalence of IAC in nonstroke patients, although with a lower frequency than in stroke patients. A high prevalence of IAC in stroke-free patients was first described by Chen et al. (15), who found a prevalence of 76.4% of IAC in their control group, compared with a high value of 92.6% in stroke patients (P < 0.01). The high prevalence of IAC in nonstroke patients could suggest that IAC may not be linked to atherosclerosis-related stroke. However, the frequency of IAC was significantly higher in stroke patients than in nonstroke patients. Moreover, stroke was selected in a multivariate analysis as an independent factor associated with IAC. Although we have no information regarding atherosclerosis lesions in nonstroke patients, their clinical characteristics (e.g., the frequency of diabetes, hypertension, and hyperlipidemia) argue in favor of the presence of such damage, albeit in a less severe form than in stroke patients. It has long been suggested that intracranial atherosclerosis is a potential marker of extensive systemic atherosclerotic disease (34). In light of our results and the fact that carotid atherosclerosis and coronary atherosclerosis develop simultaneously and are associated with aortic arch atherosclerosis (35,36), we hypothesize that IAC could be a marker of widespread systemic atherosclerosis. Further prospective studies are needed to confirm this hypothesis.
We observed that GFR was an independent predictor of IAC in patients hospitalized for stroke and in patients with other neurologic disorders. Although this type of association has not been reported in ischemic stroke patients, a strong relationship between atherosclerosis and calcification has been established in CKD patients. Atherosclerosis is the most frequent underlying cause of cardiovascular disease in patients with end-stage renal disease (37–39). Furthermore, there is evidence to suggest that the increased risk of ischemic stroke in CKD patients can be partly explained by more advanced atherosclerotic disease (37,40), which is characterized by a high degree of medial and intimal calcification (4,5). This relationship can also be applied to patients with more moderate degrees of renal function impairment, suggesting a graded worsening of atherosclerosis in parallel with renal failure (41,42) (review by Vanholder et al. [3]). The present study showed that greater degrees of renal dysfunction were associated with higher IAC scores, although this relationship was not linear and was mainly due to the comparison between grade I and II and grade III and IV MDRD subgroups. This relationship remains to be investigated in a specifically designed study. It would also be interesting to explore the relationship between IAC and CKD in a younger stroke population (to exclude an age effect).
Lastly, we did not find any association between IAC and the length of hospitalization. This negative result does not support the hypothesis whereby patients with IAC suffer from a more severe stroke. However, the outcome is usually measured 3 mo after stroke onset and according to specific scales (24). Our study protocol was not designed to examine the issue of poorer outcomes in the presence of IAC. Hence, assessment of the association between IAC and stroke outcome requires further investigation.
Our study presents a number of limitations. Our cohort was restricted to patients with neurologic disorders. Furthermore, we used estimations of GFR rather than direct measurements, and serum creatinine was measured only once, thereby disregarding possible intraindividual fluctuations. Lastly, data on microalbuminuria or other renal-specific factors were not available. However, the method used in this study to assess vascular calcification is widely available and relatively inexpensive and is the most common imaging study prescribed in the initial assessment of stroke patients. IAC therefore provides immediate vascular information in stroke patients. We therefore strongly support the use of screening for IAC in ischemic stroke patients to detect the severity of systemic atherosclerosis disease. Further studies are required to determine whether IAC is also predictive of short-term and long-term outcomes in these patients.
Disclosures
None.
Published online ahead of print. Publication date available at www.cjasn.org.
References
- 1.Berliner JA, Navab M, Fogelman AM, Frank JS, Demer LL, Edwards PA, Watson AD, Lusis AJ: Atherosclerosis: Basic mechanisms. Oxidation, inflammation, and genetics. Circulation 91: 2488–2496, 1995 [DOI] [PubMed] [Google Scholar]
- 2.Pannier B, Guerin AP, Marchais SJ, Safar ME, London GM: Stiffness of capacitive and conduit arteries: Prognostic significance for end-stage renal disease patients. Hypertension 45: 592–596, 2005 [DOI] [PubMed] [Google Scholar]
- 3.Vanholder R, Massy ZA, Argiles A, Spasovski G, Verbeke F, Lameire N: Chronic kidney disease as cause of cardiovascular morbidity and mortality. Nephrol Dial Transplant 20: 1048–1056, 2005 [DOI] [PubMed] [Google Scholar]
- 4.Goodman WG, Goldin J, Kuizon BD, Yoon C, Gales B, Sider D, Wang Y, Chung J, Emerick A, Greaser L, Elashoff RM, Salusky IB: Coronary-artery calcification in young adults with end-stage renal disease who are undergoing dialysis. N Engl J Med 342: 1478–1483, 2000 [DOI] [PubMed] [Google Scholar]
- 5.London GM, Marchais SJ, Metivier F, Guerin AP: Cardiovascular risk in end-stage renal disease: vascular aspects. Nephrol Dial Transplant 15 [Suppl 5]: 97–104, 2000 [DOI] [PubMed] [Google Scholar]
- 6.Annuk M, Zilmer M, Lind L, Linde T, Fellstrom B: Oxidative stress and endothelial function in chronic renal failure. J Am Soc Nephrol 12: 2747–2752, 2001 [DOI] [PubMed] [Google Scholar]
- 7.Drüeke TB, Nguyen Khoa T, Massy ZA, Witko-Sarsat V, Lacour B, Descamps-Latscha B: Role of oxidized low-density lipoprotein in the atherosclerosis of uremia. Kidney Int Suppl 78: S114–S119, 2001 [DOI] [PubMed] [Google Scholar]
- 8.Bonomini M, Pandolfi A, Di Pietro N, Sirolli V, Giardinelli A, Consoli A, Amoroso L, Gizzi F, De Lutiis MA, Felaco M: Adherence of uremic erythrocytes to vascular endothelium decreases endothelial nitric oxide synthase expression. Kidney Int 67: 1899–1906, 2005 [DOI] [PubMed] [Google Scholar]
- 9.Adragao T, Pires A, Lucas C, Birne R, Magalhaes L, Goncalves M, Negrao AP: A simple vascular calcification score predicts cardiovascular risk in haemodialysis patients. Nephrol Dial Transplant 19: 1480–1488, 2004 [DOI] [PubMed] [Google Scholar]
- 10.Kauppila LI, Polak JF, Cupples LA, Hannan MT, Kiel DP, Wilson PW: New indices to classify location, severity and progression of calcific lesions in the abdominal aorta: A 25-year follow-up study. Atherosclerosis 132: 245–250, 1997 [DOI] [PubMed] [Google Scholar]
- 11.Ribeiro S, Ramos A, Brandao A, Rebelo JR, Guerra A, Resina C, Vila-Lobos A, Carvalho F, Remedio F, Ribeiro F: Cardiac valve calcification in haemodialysis patients: Role of calcium-phosphate metabolism. Nephrol Dial Transplant 13: 2037–2040, 1998 [DOI] [PubMed] [Google Scholar]
- 12.Moe SM, O'Neill KD, Fineberg N, Persohn S, Ahmed S, Garrett P, Meyer CA: Assessment of vascular calcification in ESRD patients using spiral CT. Nephrol Dial Transplant 18: 1152–1158, 2003 [DOI] [PubMed] [Google Scholar]
- 13.Nitta K, Akiba T, Suzuki K, Uchida K, Ogawa T, Majima K, Watanabe R, Aoki T, Nihei H: Assessment of coronary artery calcification in hemodialysis patients using multi-detector spiral CT scan. Hypertens Res 27: 527–533, 2004 [DOI] [PubMed] [Google Scholar]
- 14.Chen XY, Lam WW, Ng HK, Fan YH, Wong KS: The frequency and determinants of calcification in intracranial arteries in Chinese patients who underwent computed tomography examinations. Cerebrovasc Dis 21: 91–97, 2006 [DOI] [PubMed] [Google Scholar]
- 15.Chen XY, Lam WW, Ng HK, Fan YH, Wong KS: Intracranial artery calcification: A newly identified risk factor of ischemic stroke. J Neuroimaging 17: 300–303, 2007 [DOI] [PubMed] [Google Scholar]
- 16.Sohn YH, Cheon HY, Jeon P, Kang SY: Clinical implication of cerebral artery calcification on brain CT. Cerebrovasc Dis 18: 332–337, 2004 [DOI] [PubMed] [Google Scholar]
- 17.Bugnicourt JM, Chillon JM, Canaple S, Lamy C, Godefroy O: Stroke secondary prevention and blood pressure reduction: An observational study of the use of PROGRESS therapy. Fundam Clin Pharmacol 22: 217–222, 2008 [DOI] [PubMed] [Google Scholar]
- 18.Adams HP, Jr., Bendixen BH, Kappelle LJ, Biller J, Love BB, Gordon DL, Marsh, EE, 3rd: Classification of subtype of acute ischemic stroke: Definitions for use in a multicenter clinical trial. TOAST. Trial of Org 10172 in Acute Stroke Treatment. Stroke 24: 35–41, 1993 [DOI] [PubMed] [Google Scholar]
- 19.Levey AS, Bosch JP, Lewis JB, Greene T, Rogers N, Roth D: A more accurate method to estimate glomerular filtration rate from serum creatinine: A new prediction equation. Modification of Diet in Renal Disease Study Group. Ann Intern Med 130: 461–470, 1999 [DOI] [PubMed] [Google Scholar]
- 20.Levey AS, Coresh J, Balk E, Kausz AT, Levin A, Steffes MW, Hogg RJ, Perrone RD, Lau J, Eknoyan G: National Kidney Foundation practice guidelines for chronic kidney disease: Evaluation, classification, and stratification. Ann Intern Med 139: 137–147, 2003 [DOI] [PubMed] [Google Scholar]
- 21.Nandalur KR, Baskurt E, Hagspiel KD, Phillips CD, Kramer CM: Calcified carotid atherosclerotic plaque is associated less with ischemic symptoms than is noncalcified plaque on MDCT. AJR 184: 295–298, 2005 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Erbay S, Han R, Baccei S, Krakov W, Zou KH, Bhadelia R, Polak J: Intracranial carotid artery calcification on head CT and its association with ischemic changes on brain MRI in patients presenting with stroke-like symptoms: Retrospective analysis. Neuroradiology 49: 27–33, 2007 [DOI] [PubMed] [Google Scholar]
- 23.Woodcock RJ, Jr., Goldstein JH, Kallmes DF, Cloft HJ, Phillips CD: Angiographic correlation of CT calcification in the carotid siphon. AJNR Am J Neuroradiol 20: 495–499, 1999 [PMC free article] [PubMed] [Google Scholar]
- 24.Rankin J: Cerebral vascular accidents in patients over the age of 60: II. Prognosis. Scott Med J 2: 200–215, 1957 [DOI] [PubMed] [Google Scholar]
- 25.Caplan LR, Gorelick PB, Hier DB: Race, sex and occlusive cerebrovascular disease: a review. Stroke 17: 648–655, 1986 [DOI] [PubMed] [Google Scholar]
- 26.Miralles M, Merino J, Busto M, Perich X, Barranco C, Vidal-Barraquer F: Quantification and characterization of carotid calcium with multi-detector CT-angiography. Eur J Vasc Endovasc Surg 32: 561–567, 2006 [DOI] [PubMed] [Google Scholar]
- 27.Strong JP: Atherosclerotic lesions. Natural history, risk factors, and topography. Arch Pathol Lab Med 116: 1268–1275, 1992 [PubMed] [Google Scholar]
- 28.Ptak T, Hunter GH, Avakian R, Novelline RA: Clinical significance of cavernous carotid calcifications encountered on head computed tomography scans performed on patients seen in the emergency department. J Comput Assisted Tomogr 27: 505–509, 2003 [DOI] [PubMed] [Google Scholar]
- 29.Yokoyama K: Evaluation of coronary artery calcification in ESRD patients. Clin Calcium 14: 109–115, 2004 [PubMed] [Google Scholar]
- 30.Shaalan WE, Cheng H, Gewertz B, McKinsey JF, Schwartz LB, Katz D, Cao D, Desai T, Glagov S, Bassiouny HS: Degree of carotid plaque calcification in relation to symptomatic outcome and plaque inflammation. J Vasc Surg 40: 262–269, 2004 [DOI] [PubMed] [Google Scholar]
- 31.Babiarz LS, Yousem DM, Bilker W, Wasserman BA: Middle cerebral artery infarction: Relationship of cavernous carotid artery calcification. AJNR Am J Neuroradiol 26: 1505–1511, 2005 [PMC free article] [PubMed] [Google Scholar]
- 32.Taoka T, Iwasaki S, Nakagawa H, Sakamoto M, Fukusumi A, Takayama K, Wada T, Myochin K, Hirohashi S, Kichikawa K: Evaluation of arteriosclerotic changes in the intracranial carotid artery using the calcium score obtained on plain cranial computed tomography scan: Correlation with angiographic changes and clinical outcome. J Comput Assisted Tomogr 30: 624–628, 2006 [DOI] [PubMed] [Google Scholar]
- 33.Chen XY, Wong KS, Lam WW, Zhao HL, Ng HK: Middle cerebral artery atherosclerosis: Histological comparison between plaques associated with and not associated with infarct in a postmortem study. Cerebrovasc Dis 25: 74–80, 2008 [DOI] [PubMed] [Google Scholar]
- 34.Marzewski DJ, Furlan AJ, St Louis P, Little JR, Modic MT, Williams G: Intracranial internal carotid artery stenosis: Longterm prognosis. Stroke 13: 821–824, 1982 [DOI] [PubMed] [Google Scholar]
- 35.Demopoulos LA, Tunick PA, Bernstein NE, Perez JL, Kronzon I: Protruding atheromas of the aortic arch in symptomatic patients with carotid artery disease. Am Heart J 129: 40–44, 1995 [DOI] [PubMed] [Google Scholar]
- 36.Kallikazaros IE, Tsioufis CP, Stefanadis CI, Pitsavos CE, Toutouzas, PK: Closed relation between carotid and ascending aortic atherosclerosis in cardiac patients. Circulation 102: III263–III268, 2000 [DOI] [PubMed] [Google Scholar]
- 37.Kawamura M, Fijimoto S, Hisanaga S, Yamamoto Y, Eto T: Incidence, outcome, and risk factors of cerebrovascular events in patients undergoing maintenance hemodialysis. Am J Kidney Dis 31: 991–996, 1998 [DOI] [PubMed] [Google Scholar]
- 38.London GM: Cardiovascular calcifications in uremic patients: Clinical impact on cardiovascular function. J Am Soc Nephrol 14: S305–S309, 2003 [DOI] [PubMed] [Google Scholar]
- 39.Seliger SL, Gillen DL, Longstreth WT, Jr., Kestenbaum B, Stehman-Breen CO: Elevated risk of stroke among patients with end-stage renal disease. Kidney Int 64: 603–609, 2003 [DOI] [PubMed] [Google Scholar]
- 40.Maeda N, Sawayama Y, Tatsukawa M, Okada K, Furusyo N, Shigematsu M, Kashiwagi S, Hayashi J: Carotid artery lesions and atherosclerotic risk factors in Japanese hemodialysis patients. Atherosclerosis 169: 183–192, 2003 [DOI] [PubMed] [Google Scholar]
- 41.Fried LF, Shlipak MG, Crump C, Bleyer AJ, Gottdiener JS, Kronmal RA, Kuller LH, Newman AB: Renal insufficiency as a predictor of cardiovascular outcomes and mortality in elderly individuals. J Am Coll Cardiol 41: 1364–1372, 2003 [DOI] [PubMed] [Google Scholar]
- 42.Levin A, Singer J, Thompson CR, Ross H, Lewis M: Prevalent left ventricular hypertrophy in the predialysis population: identifying opportunities for intervention. Am J Kidney Dis 27: 347–354, 1996 [DOI] [PubMed] [Google Scholar]