Albuminuria is the most widely evaluated marker of kidney damage. Many previous studies have demonstrated an association between the presence of albuminuria and increased cardiovascular events. However, there are limited data regarding the impact of albuminuria in patients requiring coronary revascularization. This study investigated whether the urinary albumin excretion rate could predict cardiovascular events in such a population. We enrolled 698 consecutive patients who underwent elective percutaneous coronary intervention. The baseline urinary albumin-to-creatinine ratio (ACR; mg/gCr) was measured and patients were divided into those with normoalbuminuria (ACR <30 mg/gCr), microalbuminuria (ACR 30 to 300 mg/gCr), or macroalbuminuria (ACR >300 mg/gCr). We collected data on the incidences of cardiac death and/or nonfatal myocardial infarction. We identified 389, 230, and 79 patients with normoalbuminuria, microalbuminuria, and macroalbuminuria, respectively. During follow-up (median: 1,564 days), 41 events occurred. The event-free survival rate was 89% in patients with macroalbuminuria, 92% in those with microalbuminuria, and 97% in those with normoalbuminuria, respectively (log-rank test p = 0.002). After adjustment for conventional risk factors, Cox analysis revealed hazard ratios for cardiac death and/or nonfatal myocardial infarction were 2.56 (95% CI 1.23 to 5.32, p = 0.01) in those with microalbuminuria and 4.02 (95% CI 1.59 to 10.12, p = 0.003) in those with macroalbuminuria compared with those with normoalbuminuria. In conclusion, an elevated urinary albumin excretion rate independently predicted adverse cardiovascular outcomes, with a gradual risk increase that progressed from microalbuminuria to macroalbuminuria in patients undergoing elective percutaneous coronary intervention.
Albuminuria is the most widely evaluated marker of renal damage. Many previous studies have demonstrated associations between albuminuria and advanced atherosclerosis and their cardiovascular outcomes. The Kidney Disease Improving Global Outcomes guidelines indicate that both estimated glomerular filtration rate (eGFR), which is a commonly used marker of renal dysfunction, and albuminuria are important when predicting mortality and cardiovascular outcomes. We previously demonstrated the association between albuminuria and the incidence of periprocedural myocardial injury after elective percutaneous coronary intervention (PCI). However, there are limited data regarding the impact of albuminuria on cardiovascular outcome in patients who require coronary revascularization. The aim of this study was to determine whether albuminuria could be a useful marker to detect those subjects at higher risk after elective PCI.
Methods
This observational study consisted of 698 consecutive non-dialysis–dependent patients successfully undergoing elective PCI to de novo lesion in Chubu Rosai Hospital, Nagoya, Japan from January 2008 to December 2012. We excluded patients who were lost to follow-up (4 patients). The ethics committee of Chubu Rosai Hospital approved the study, and all patients provided written informed consent.
According to the Kidney Disease Improving Global Outcomes 2012 Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease, the patients were classified into 3 groups on the basis of their albumin level: normoalbuminuria (albumin-to-creatinine ratio [ACR] <30 mg/gCr), microalbuminuria (ACR 30 to 300 mg/gCr), and macroalbuminuria (ACR >300 mg/gCr). Spot urinary albumin and creatinine were measured by immunonephelometry and enzymatic methods, respectively. The urinary ACR (mg/gCr) was calculated at baseline. Serum eGFR was calculated using the Modification of Diet in Renal Disease equations modified with the Japanese coefficient.
Baseline angiography was evaluated by an independent investigator who was not involved in the procedures and was blinded to the outcomes. A computerized quantitative analysis system (QCA-CMS system, version 6.0.39.0; Medis, Leiden, the Netherlands) was used with the guide catheter for calibration. The operators in charge, who were blinded to the ACR levels, determined the method and device for PCI according to angiography and conventional intravascular ultrasound findings.
Follow-up data were obtained through admission and outpatient medical records or by telephone interview. The primary end point of this study was the incidence of cardiac death and/or nonfatal myocardial infarction. The secondary end points were total major adverse cardiac events (MACEs) defined as the composite of cardiac death, nonfatal myocardial infarction, and any revascularization including target lesion revascularization and new lesion revascularization. Events at the time of the index interventional procedure and during the index hospitalization were not assessed. For multiple occurrences of events, the time to the first event was used as the time when the total MACE was detected. We also assessed the incidence of target lesion revascularization and new lesion revascularization as secondary end points, respectively.
Myocardial infarction was defined as the development of signs and/or symptoms of ischemia accompanied by the elevation of creatine kinase-MB or troponin T levels at least twofold higher than normal or new significant Q waves in 2 or more contiguous leads. The target lesion was defined as the area covered by the stents plus 5-mm margins proximal and distal to the edge of the stent. Any revascularization was driven by clinical findings such as the presence of ischemic symptoms, a positive functional ischemia assessment, or an ischemic electrocardiogram change. The events were assessed by investigators blinded to the clinical data.
All normally or nonnormally distributed continuous values are expressed as the mean ± SD and median (interquartile range), respectively. Categorical variables are expressed as a number (proportion). We compared normally distributed continuous variables using analysis of variance and nonnormally distributed variables (ACR, C-reactive protein) with the Kruskal–Wallis test, whereas categorical variables were compared using the Fisher’s exact test or chi-squared test. Event-free survival rate was analyzed using Kaplan–Meier estimation with a log-rank test. The Cox proportional hazards model was used to estimate the contribution of ACR to the prediction of cardiovascular events during follow-up. We considered age, men, body mass index, ejection fraction, and conventional coronary risk factors (current smoker, eGFR <60 ml/min/1.73 m 2 , diabetes mellitus, hypertension, and dyslipidemia) as candidate variables for inclusion in the multivariate analysis. Predictive performance for cardiovascular events with or without albuminuria stages was evaluated by calculating c-statistics, and the improvement in predictive accuracy was evaluated by calculating the net reclassification improvement and the integrated discrimination improvement. A p value <0.05 was considered statistically significant. Calculations were performed using SPSS statistical software, version 18.0, (SPSS Institute Inc., Chicago, Illinois) and R 2.13.1 with PredictABEL and pROC packages (R Development Core Team 2011, Vienna, Austria).
Results
Normoalbuminuria, microalbuminuria, and macroalbuminuria were determined in 389, 230, and 79 patients, respectively. The normoalbuminuria group was significantly younger (p <0.001) and more male patients (p = 0.007) were included than in the other groups ( Table 1 ). eGFR was significantly lower (p <0.001) in the macroalbuminuria group compared with the other groups. The prevalence of diabetes (p <0.001) and hypertension (p = 0.01) increased from the normoalbuminuria group to the macroalbuminuria group. There was no significant difference in procedural and lesion characteristics in the groups, except for the incidence of balloon angioplasty (p = 0.01, Table 2 ).
| Characteristics | Albuminuria | p-value | ||
|---|---|---|---|---|
| normo (n = 389) | micro (n = 230) | macro (n = 79) | ||
| Age (years) | 68 ± 11 | 72 ± 9 | 71 ± 9 | <0.001 |
| Male | 286 (74%) | 152 (66%) | 45 (57%) | 0.007 |
| Body mass index (kg/m 2 ) | 24.1 ± 3.7 | 23.7 ± 3.5 | 23.9 ± 3.7 | 0.4 |
| C-reactive protein (mg/dl) | 0.11 (0.05 – 0.30) | 0.14 (0.06 – 0.47) | 0.21 (0.07 – 0.55) | 0.2 |
| Serum creatinine (mg/dl) | 0.8 ± 0.2 | 0.9 ± 0.4 | 1.3 ± 0.8 | <0.001 |
| Estimated glomerular filtration rate (ml/min/1.73m 2 ) | 68 ± 16 | 63 ± 22 | 50 ± 21 | <0.001 |
| Estimated glomerular filtration rate <60 ml/min/1.73m 2 | 91 (23%) | 95 (41%) | 54 (68%) | <0.001 |
| Albumin creatinine ratio (mg/gCr) | 10 (6 – 17) | 82 (52 – 138) | 707 (485– 1240) | <0.001 |
| Ejection fraction (%) | 67 ± 11 | 67 ± 13 | 67± 12 | 0.8 |
| Diabetes mellitus | 178 (46%) | 150 (65%) | 68 (86%) | <0.001 |
| Hypertension | 337 (87%) | 208 (90%) | 77 (98%) | 0.01 |
| Dyslipidemia | 329 (85%) | 201 (87%) | 71 (90%) | 0.4 |
| Current smoker | 132 (34%) | 66 (29%) | 17 (22%) | 0.07 |
| Previous myocardial infarction | 99 (25%) | 63 (27%) | 18 (23%) | 0.7 |
| Multiple vessel coronary disease | 170 (44%) | 111 (48%) | 42 (53%) | 0.2 |
| Previous percutaneous coronary intervention | 115 (30%) | 62 (27%) | 24 (30%) | 0.7 |
| Previous coronary artery bypass grafting | 26 (7%) | 20 (9%) | 7 (9%) | 0.6 |
| Medications | ||||
| Aspirin, | 385 (99%) | 230 (100%) | 77 (98%) | 0.1 |
| Thienopyridine derivatives | 369 (95%) | 222 (97%) | 73 (92%) | 0.3 |
| Statins | 353 (91%) | 204 (89%) | 68 (86%) | 0.4 |
| Calcium channel blocker | 142 (37%) | 108 (47%) | 40 (51%) | 0.009 |
| β-blockers | 170 (44%) | 89 (39%) | 37 (47%) | 0.3 |
| Angiotensin converting enzyme inhibitor or angiotensin-II receptor blocker | 230 (59%) | 151 (66%) | 62 (79%) | 0.003 |
| Characteristics | Albuminuria | p-value | ||
|---|---|---|---|---|
| normo (n = 389) | micro (n = 230) | macro (n = 79) | ||
| Coronary artery | ||||
| Right | 121 (31%) | 72 (31%) | 29 (37%) | 0.6 |
| Left anterior descending | 181 (47%) | 118 (51%) | 30 (38%) | 0.1 |
| Left circumflex | 93 (24%) | 42 (18%) | 21(27%) | 0.2 |
| Left main | 14 (4%) | 7 (3%) | 4 (5%) | 0.7 |
| Saphenous vein graft | 0 (0%) | 3 (1%) | 1 (1%) | 0.08 |
| American Heart Association/American College of Cardiology type B2/C | 141 (36%) | 92 (40%) | 33 (42%) | 0.5 |
| Quantitative coronary analysis | ||||
| Reference diameter (mm) | 2.3 ± 0.6 | 2.2 ± 0.6 | 2.1 ± 0.5 | 0.08 |
| Diameter stenosis (%) | 72.3 ± 13.4 | 71.3 ± 12.3 | 70.9 ± 13.0 | 0.5 |
| Bare-metal stent | 66 (17%) | 41 (18%) | 13 (17%) | 0.9 |
| Drug-eluting stent | 310 (80%) | 187 (81%) | 62 (79%) | 0.8 |
| Balloon angioplasty | 17 (4%) | 5 (2%) | 8 (10%) | 0.01 |
| Number of stent | 1.4 ± 0.7 | 1.5 ± 0.7 | 1.4 ± 0.9 | 0.2 |
During follow-up (median: 1,564 days), 41 primary end point events and 210 total events were documented ( Table 3 ). In the Kaplan–Meier analysis ( Figure 1 ), ACR was significantly associated with the incidence of cardiac death and myocardial infarction (log-rank test p = 0.002), total MACE, and new lesion revascularization. In contrast, no association was observed between ACR and the incidence of target lesion revascularization.
| Clinical event | Albuminuria | p-value | ||
|---|---|---|---|---|
| normo (n = 389) | micro (n = 230) | macro (n = 79) | ||
| Primary endpoint | ||||
| Cardiac death or myocardial infarction | 13 (3 %) | 19 (8 %) | 9 (11 %) | 0.004 |
| Secondary endpoint | ||||
| Total MACE | 87 (22 %) | 65 (28 %) | 33 (42 %) | 0.001 |
| Cardiac death or myocardial infarction | 9 (2 %) | 13 (6 %) | 7 (9 %) | 0.01 |
| Target lesion revascularization | 35 (9 %) | 17 (7 %) | 7 (9 %) | 0.8 |
| New lesion revascularization | 44 (11 %) | 35 (15 %) | 19 (24 %) | 0.01 |
| Target lesion revascularization | 37 (10 %) | 21 (9 %) | 8 (10 %) | 0.97 |
| New lesion revascularization | 46 (12 %) | 37 (16 %) | 20 (25 %) | 0.007 |
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