Renal function, concomitant medication use and outcomes following acute coronary syndromes

Donal N. Reddan1,2, Lynda Szczech2, Manjushri V. Bhapkar2, David J. Moliterno3, Robert M. Califf2, E. Magnus Ohman4, Peter B. Berger5, Judith S. Hochman6, Frans Van de Werf7, Robert A. Harrington2, L. Kristin Newby2 and for the SYMPHONY and 2nd SYMPHONY Investigators

1 University College Galway, Ireland, 2 Duke Clinical Research Institute, Durham, NC, 3 University of Kertucky, Lexington, KY, 4 University of North Carolina-Chapel Hill, Chapel Hill, NC, 5 Mayo Clinic Foundation, Rochester, MN, 6 Columbia University Medical Center, New York, NY, USA and 7 Department of Cardiology, Universitaire Zeikenhuizen Leuven, Belgium

Correpondence and offprint requests to: Donal N. Reddan, MB, MHS, University College Galway, Ireland. Email: dreddan{at}eircom.net



   Abstract
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 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
Background. Chronic kidney disease (CKD) is highly prevalent in patients with cardiovascular disease. We explored the associations of CKD with outcomes using combined data from two large acute coronary syndrome (ACS) trials. We also explored the associations of CKD with prescription patterns for common cardiovascular medications and the association of these prescription patterns with clinical outcomes.

Methods. Patients were stratified by CKD stage using creatinine clearance (CrCl, ml/min) estimated by the modified MDRD equation using baseline core laboratory creatinine measures. Serum creatinine ≥1.5 mg/dl was an exclusion criterion for the SYMPHONY trials. Baseline characteristics and outcomes across CKD categories were compared and Cox proportional hazards regression was used to assess the relationship of renal insufficiency with clinical outcomes after adjusting for previously identified outcome predictors. Interactions between the use of specific medications and calculated CrCl were tested in the final Cox proportional hazards model predicting time to mortality.

Results. Of 13 707 patients analysed, 6840 had CKD stage I (CrCl ≥90 ml/min), 5909 stage II (CrCl 60–89 ml/min), 955 stage III (CrCl 30–59 ml/min) and three stage IV (CrCl <30 ml/min). Patients with more advanced CKD (III) were older, more often female, non-smokers and more likely to have co-morbid diseases including diabetes mellitus, hypertension and congestive heart failure. Cardiovascular medications were used less frequently in patients with CKD. Unadjusted survival was poorer in patients with CKD stages ≥II. In adjusted analyses, for those with CrCl ≤91, each 10 ml/min increase in CrCl was associated with a significantly decreased risk of mortality (hazards ratio 0.897, 95% confidence interval 0.815–0.986) (P = 0.024). The interaction between use of angiotensin-converting enzyme (ACE) inhibitors and CrCl was significantly associated with outcomes; the benefit of drug therapy was greater among patients with CKD.

Conclusions. CKD is an independent predictor of risk among ACS patients, and is associated with less frequent use of proven medical therapies. More aggressive use of conventional cardiovascular therapies in patients with CKD and ACS may be warranted.

Keywords: acute coronary syndromes; concomitant medications; renal dysfunction; chronic kidney disease; cardiovascular medications



   Introduction
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
Chronic kidney disease (CKD) is highly prevalent among patients with cardiovascular disease [1,2], and patients with co-existing cardiovascular and renal disease appear to be at increased risk of poor outcomes [3–6]. Yet, despite strong evidence linking CKD to worse outcomes, the impact of CKD on mortality and morbidity in patients with acute coronary syndrome (ACS) is probably underappreciated and patients with CKD receiving acute cardiac care may not be treated as aggressively or with evidence-based therapies as frequently as those with normal renal function [7–10].

The present study was undertaken to describe outcomes among ACS patients with CKD using combined data from two large, randomized, controlled trials of sibrafiban, an oral platelet glycoprotein IIb/IIIa inhibitor. In addition, we explored prescription patterns for common cardiovascular medications in relation to severity of CKD and the association of these prescription patterns with clinical outcomes.



   Methods
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
Study population
The SYMPHONY (Sibrafiban versus aspirin to Yield Maximum Protection from ischemic Heart events post-acute cOroNary sYndromes) and 2nd SYMPHONY trials complied with the Declaration of Helsinki and were approved by locally appointed ethics committees at all centres. Informed consent was obtained from all patients. These studies enrolled 15 904 patients and were conducted at 931 clinical centres in 37 countries between August 1997 and August 1999. The trial methods and primary end-point results have been published [11–13]. Briefly, SYMPHONY randomly assigned 9233 patients, stabilized for at least 12 h and within 7 days after ACS [ST-segment elevation or non-ST-segment elevation myocardial infarction (MI) or unstable angina], to receive either aspirin, 80 mg orally twice daily or one of two dose regimens (low or high) of sibrafiban twice daily for 90 days. In the 2nd SYMPHONY trial, 6671 patients meeting similar inclusion criteria were randomly assigned to receive aspirin 80 mg orally, low-dose sibrafiban plus aspirin 80 mg, or high-dose sibrafiban alone twice daily. Median treatment duration was 90 (range 36–139) days.

Patients with serum creatinine >1.5 mg/dl were excluded from both trials. Creatinine data for patients enrolled in these trials were available both from local on-site measurements and from samples sent to a central core laboratory. We pre-specified the use of the core laboratory creatinine data for our primary analyses. Of the 15 904 patients enrolled in the SYMPHONY trials, 13 707 patients (86%) with available core laboratory serum creatinine data were included in this analysis.

Estimated creatinine clearance (CrCl, ml/min) was calculated according to the modified MDRD equation [14]. Patients were stratified into discrete groups based on estimated CrCl using standard criteria: normal, ≥90; mild renal insufficiency, 89–60; moderate renal insufficiency, 59–30; severe renal insufficiency, <29 [15]. The three patients with severe CKD were combined with those in the moderate CKD group for graphical display.

Statistical analysis
Baseline characteristics, concomitant medications and outcomes were summarized as percentages and medians (25th, 75th percentiles) across CrCl categories and compared using the Wilcoxon rank sum test for categorical variables and Spearman correlation for continuous variables.

Unadjusted Kaplan–Meier survival estimates were generated for 90 day death and death or MI. End-points were used as defined by a blinded central adjudication committee for the main trials. Cox proportional hazards regression was used to assess the relationship of renal function with clinical outcomes after adjusting for previously identified outcome predictors [16]. To allow for a non-linear effect of CrCl, spline functions [17] were tested in Cox regression models and, where a threshold was defined, CrCl was truncated above the threshold level. In addition to standard covariate adjustments, factors favouring medication selection were accounted for using propensity scores [18–20]. These scores were developed from binary logistic regression models and were represented in Cox regression models by the linear score or logit from logistic models. Interactions between the use of specific medications and calculated CrCl were tested in the final Cox proportional hazards model predicting time to mortality. Where interaction terms were significant, the slope of each interaction term was then used to interpret how the associations of medication use with outcome varied with severity of CKD.

Cox proportional hazards regression was also used to assess the relationship of heparin and/or low molecular weight heparin (LMWH) use at baseline with the risk of major or minor bleeding over 90 days and to test for an interaction between CrCl and heparin use in predicting bleeding risk. For the current analyses, bleeding end-points were used as assigned by algorithm for the main studies. Major bleeding was defined as intracranial haemorrhage or a decrease in haemoglobin of >5 g/dl or haematocrit by ≥15%. Minor bleeding was defined as follows: any skin or mucosal bleeding >30 min in duration, gross haematuria, melaena, haematemesis, haemoptysis, haematochezia, spontaneous bruise >6 cm in diameter, or any change in haemoglobin >3 and ≤5 g/dl or in haematuria ≥9% and <15%.

Concomitant medications
Information on concomitant medication use was collected by study site personnel from medical record review and patient interview and was entered on the main SYMPHONY and 2nd SYMPHONY case report forms. This information was updated at 2 weeks, 1 month and 3 months in SYMPHONY and at 1 month then at 3 month intervals until the 2nd SYMPHONY trial ended. All case report forms were double entered, and concomitant medications were queried as part of safety reconciliation at the end of the studies and were monitored as part of the study monitoring plans. Medications were initially reported by class, e.g. statins, ß-blocker. Approximately half-way through SYMPHONY and for the entire 2nd SYMPHONY trial, data on concomitant medications were collected using the generic name.

All P-values reported are two-sided and were considered significant at the 0.05 level. Hazard ratios (HRs) are displayed with 95% confidence intervals (CIs). No adjustments were made for multiple comparisons.



   Results
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 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
Population characteristics
Baseline characteristics across categories of renal function are displayed in Table 1. Nine hundred and fifty-five (7%) had CrCl 30–59 ml/min [median 54, interquartile range (IQR) 49–57] and were defined as having moderate CKD by standard criteria; 5909 (53%) had mild CKD (CrCl 60–89) [15] (median 78, IQR 71–84), 6840 had CrCl ≥90 (median 106, IQR 97–121). Patients with moderate CKD were older, more often female, of smaller size and less often smokers than patients with normal renal function. They were also more likely to have congestive heart failure, prior angina, cerebrovascular disease, hypertension and prior percutaneous coronary intervention (PCI) or coronary artery bypass grafting (CABG). Patients with CKD were less likely to have had a presenting MI and were less likely than patients with normal renal function to have undergone PCI, CABG or thrombolysis at the time of presentation.


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Table 1. Baseline characteristics by chronic kidney disease category

 
Outcomes by severity of renal impairment
Figure 1 describes the 90 day incidence of death for each CKD category. Patients with moderate CKD had significantly higher unadjusted 90 day mortality than those with normal renal function or mild impairment. Similarly, patients with moderate CKD had a higher incidence of the combined end-point of death or MI over 90 days than patients with normal renal function or mild impairment (Figure 2). After adjusting for the baseline characteristics previously shown to predict 90 day mortality and death or MI in the SYMPHONY population [16], CKD was not a significant predictor of combined death or MI over 90 days but remained an important predictor of death. The threshold value above which CrCl was found not to influence survival was 91 ml/min (Figure 3). For those with CrCl ≤91 ml/min, each 10 ml/min increase in CrCl was associated with a significantly decreased risk of mortality (HR 0.897; 95% CI 0.815–0.986) (P = 0.024).



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Fig. 1. Unadjusted 90 day survival by chronic kidney disease category: normal (dashed line), mild (dotted line), moderate/severe (solid line).

 


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Fig. 2. Unadjusted 90 day event-free (from death or myocardial infarction) survival by chronic kidney disease category: normal (dashed line), mild (dotted line), moderate/severe (solid line).

 


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Fig. 3. Adjusted 90 day mortality (solid line) with 95% confidence intervals (dotted lines) as a function of creatinine clearance using spline transformation.

 
Variability of creatinine measurements
Creatinine measurements from the central laboratory were consistently lower than local values. Therefore, CrCl estimates using the central laboratory values were higher than when the local values were used, and the distribution of patients in the four CrCl categories (<29, 30–59, 60–89 and ≥90) were also different. Using central laboratory values, the percentages of patients in each category were: <1, 7, 43 and 50, respectively. Using local laboratory values, the percentages were: 0, 16, 58 and 25. The threshold value above which CrCl was found not to influence survival also differed for the central and local laboratory data sets. For the core laboratory, it was 91 ml/min and, based on local laboratories, it was 60 ml/min.

Medications
Prescribing patterns for selected medications for a qualifying ACS event and at study discharge across CKD categories are illustrated in Figure 2. Aspirin, ß-blockers, unfractionated heparin and statins were prescribed less frequently in patients with CKD, and patients with CKD were more likely to receive digitalis and angiotensin-converting enzyme (ACE) inhibitors. Table 2 demonstrates the P-values for the CrCl xconcomitant medication interaction terms in the adjusted 90 day mortality model. The interactions between use of ACE inhibitors and CrCl was significantly associated with outcomes; the benefit of ACE inhibitor therapy was greater among patients with CKD.


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Table 2. Interactions between estimated creatinine clearance and concomitant medication with respect to 90-day mortality

 
Bleeding
Use of heparin or LMWH at baseline was associated with an increase in risk of minor or major bleeding over 90 days. The HR for baseline heparin and/or LMWH use was 1.24 (95% CI 1.11–1.39). These results remained significant when propensity scores for the use of heparin were added to the model. Higher CrCl was associated with lower bleeding risk over 90 days. The HR for CrCl (per 10 ml/min) was 0.92 (95% CI 0.89–0.95). Neither unfractionated heparin nor LMWH was noted to have a significant interaction with CrCl with respect to bleeding outcomes.



   Discussion
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
CKD is an under-recognized co-morbidity among patients with coronary artery disease. Our study emphasizes the high prevalence of CKD among patients with acute cardiac disease as documented by others [3,4] and again confirms that CKD is associated with a significantly increased mortality risk. Despite the fact that patients with serum creatinine >1.5 mg/dl were excluded from the SYMPHONY trials, 7% of those enrolled had moderate CKD by conventional criteria [15]. The mortality risk associated with CKD was apparent up to a CrCl of 91 ml/min and was sizeable. Each 10 ml/min increase in CrCl up to 79 ml/min was associated with a 10% reduction in mortality. In addition, we observed that the use of standard evidence-based therapy for treatment of patients of ACS was lower among these high-risk patients with CKD than in patients with normal renal function, but that patients with CKD may derive greater benefit from these therapies.

Informed therapeutic decision making for patients with co-existent renal and cardiac disease is limited by a profound absence of data as patients with CKD are routinely excluded, both directly and indirectly, from cardiovascular clinical trials [21]. Further, cardiovascular disease therapy among patients with co-existing CKD presents a number of therapeutic dilemmas arising from potential drug toxicity and concern about adverse consequences. There is an understandable need for caution in the use of certain therapies among patients with CKD. Inappropriate dosing of anti-arrhythmic drugs is a potential concern [22]; dosing strategies and indications for fibrinolytic therapy, glycoprotein IIb/IIIa inhibitors and antithrombotic agents, including enoxaparin and unfractionated heparin, are unclear; and the appropriate use and targets of statin therapy remains ill-defined [23].



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Fig. 4. Use of concomitant medications at qualifying event (QE) and discharge (Dx) by renal function (MDRD).

 
In our examination of prescription patterns in ACS patients, we found that despite their confirmed higher risk, patients with CKD had fewer invasive cardiovascular procedures such as PCI or CABG and were prescribed aspirin, ß-blockers, unfractionated heparin and statins less frequently. Further, our results suggest that proven secondary prevention measures such as ACE inhibitors may be even more effective in patients with CKD than in those with normal renal function. Other investigators have observed similar patterns for the use of PCI, CABG and ACE inhibitors [7,24], and we have recently reported that glycoprotein IIb/IIIa inhibitor therapy with eptifibatide may also be more effective in CKD [24].

The lower frequency with which cardiovascular medications were prescribed in this population is consistent with the findings of others [8,9], but in our study it is difficult to attribute this finding to concern about adverse consequences associated with CKD because of the relatively stringent creatinine exclusion criterion of 1.5 mg/dl for study entry. Since most physicians caring for ACS patients do not think in terms of CrCl, they most probably were not withholding therapy for reasons related to CKD. It is possible that mild increases in creatinine at baseline may be a surrogate for haemodynamic instability at the time of a qualifying event and that such instability was in some way linked to the relatively less frequent use of certain medications. Whether failure to prescribe these medications was attributable to CKD-related biases or not, it seems apparent from our observations that a more aggressive approach toward such cardiovascular therapy might have been associated with more favourable outcomes. The fact that the one significant concomitant medication x CrCl interaction suggested greater efficacy for the ACE inhibitors in CKD and that no interactions were found that suggested an increase in adverse consequences with any therapy also argues for a more aggressive approach.

The greater proportion of women with moderate or severe CKD probably reflects the particularly reduced sensitivity of serum creatinine as a marker of renal insufficiency in women, and this may indeed have implications for the interpretation of outcomes in women participating in this and other cardiac trials where creatinine was used as an exclusion factor. The greater numbers of women with CKD included is one potential explanatory factor for the generally poor cardiovascular outcomes observed in women in such trials.

The fairly large discrepancy in creatinine values and estimated CrCl we observed between local laboratories and the central core laboratory is an important consideration in the ongoing debate as to what is the most appropriate prediction equation for CrCl in CKD [25], and for the application of measures of creatinine and estimated CrCl in clinical practice. Such variability in laboratory results suggests an overall need for caution in attributing precision to any of these equations. Further, as we demonstrated, even using one standard equation, marked variability in creatinine measures could result in widely disparate assessments of the prevalence and degree of CKD and of the relationship of CrCl with outcome. These findings highlight the need for caution when interpreting creatinine values in the context of clinical decision making.

Limitations
This study is an observational subgroup analysis, and the results should therefore be interpreted with that in mind [26]. Since the majority of patients with CKD in these analyses had mild rather than moderate or severe renal insufficiency and were selected for enrolment in a clinical trial, extrapolation of these findings to patients with moderate or severe renal insufficiency, or those in the general population should be done with caution. Yet it is plausible that more striking results may be observed among those with worse CKD. Further investigation using large registry populations could be undertaken to expand the understanding of the relationship of CKD with the use of and benefit from evidence-based therapies for ACS as applied across the spectrum of clinical practice.

Most of the medications studied may have been subject to significant indication bias that may have confounded the results and, despite our attempts at propensity and covariate adjustment, this and other unmeasured confounders could have affected our observations. One important confounder not measured was the presence of albuminuria. Finally, patient compliance with treatment or changes in medication regimens that occurred after hospital discharge were not assessed. Despite these limitations, this work highlights the prevalence of CKD among ACS patients and the need for further attention to the management of patients with ACS who also have CKD.

Conclusion
Even in an ACS population selected for relatively normal serum creatinine (<1.5 mg/dl), renal insufficiency was an under-recognized co-morbidity, with 7% of patients having significant CKD and 43% having at least mild renal impairment by standard criteria. Not only was CKD an independent predictor of death or MI among ACS patients, it was also associated with less frequent use of proven medical therapies for coronary artery disease. Proven therapies may also be associated with even greater benefit among patients with CKD than in those with normal renal function. More aggressive use of conventional cardiovascular therapies in patients with CKD and ACS is warranted while further investigations are undertaken and surveillance of outcomes continues.



   Acknowledgments
 
The SYMPHONY and 2nd SYMPHONY trials were funded by research grants from F. Hoffmann-La Roche, Ltd., Basel, Switzerland.

Conflict of interest statement. D.J.M. has disclosed receiving honoraria and having been a consultant for the sponsor of the SYMPHONY trials (F. Hoffmann-La Roche, Ltd). R.M.C., L.K.N., F.deW., R.A.H. and J.S.H. received study grants from the sponsor to perform the SYMPHONY trials, and in addition J.S.H. has also received honoraria from the sponsor of the trials. None of the other authors have conflicts of interest to declare.



   References
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 

  1. Culleton BF, Larson MG, Wilson PW et al. Cardiovascular disease and mortality in a community-based cohort with mild renal insufficiency. Kidney Int 1999; 56: 2214–2219[CrossRef][ISI][Medline]
  2. Muntner P, He J, Hamm L et al. Renal insufficiency and subsequent death resulting from cardiovascular disease in the United States. J Am Soc Nephrol 2002; 13: 745–753[Abstract/Free Full Text]
  3. Al Suwaidi J, Reddan DN, Williams K et al. Prognostic implications of abnormalities in renal function in patients with acute coronary syndromes. Circulation 2002; 106: 974–980[Abstract/Free Full Text]
  4. Mann JF, Gerstein HC, Pogue J et al. Renal insufficiency as a predictor of cardiovascular outcomes and the impact of ramipril: the HOPE randomized trial. Ann Intern Med 2001; 134: 629–636[Abstract/Free Full Text]
  5. Best PJ, Lennon R, Ting HH et al. The impact of renal insufficiency on clinical outcomes in patients undergoing percutaneous coronary interventions. J Am Coll Cardiol 2002; 39: 1113–1119[Abstract/Free Full Text]
  6. Szczech LA, Best PJ, Crowley E et al. Outcomes of patients with chronic renal insufficiency in the bypass angioplasty revascularization investigation. Circulation 2002; 105: 2253–2258[Abstract/Free Full Text]
  7. McCullough PA, Sandberg KR, Borzak S et al. Benefits of aspirin and beta-blockade after myocardial infarction in patients with chronic kidney disease. Am Heart J 2002; 144: 226–232[CrossRef][ISI][Medline]
  8. Trespalacios FC, Taylor AJ, Agodoa LY et al. Incident acute coronary syndromes in chronic dialysis patients in the United States. Kidney Int 2002; 62: 1799–1805[CrossRef][ISI][Medline]
  9. Tonelli M, Bohm C, Pandeya S et al. Cardiac risk factors and the use of cardioprotective medications in patients with chronic renal insufficiency. Am J Kidney Dis 2001; 37: 484–489[ISI][Medline]
  10. Tonelli M, Moye L, Sacks FM et al. Pravastatin for secondary prevention of cardiovascular events in persons with mild chronic renal insufficiency. Ann Intern Med 2003; 138: 98–104[Abstract/Free Full Text]
  11. Second SYMPHONY Investigators. Randomized trial of aspirin, sibrafiban, or both for secondary prevention after acute coronary syndromes. Circulation 2001; 103: 1727–1733[Abstract/Free Full Text]
  12. The SYMPHONY Investigators. Comparison of sibrafiban with aspirin for prevention of cardiovascular events after acute coronary syndromes: a randomized trial. Sibrafiban versus Aspirin to Yield Maximum Protection from Ischemic Heart Events Post-acute Coronary Syndromes. Lancet 2000; 355: 337–345[CrossRef][ISI][Medline]
  13. Newby LK. Long-term oral platelet glycoprotein IIb/IIIa receptor antagonism with sibrafiban after acute coronary syndromes: study design of the sibrafiban versus aspirin to yield maximum protection from ischemic heart events post-acute coronary syndromes (SYMPHONY) trial. Symphony Steering Committee. Am Heart J 1999; 138: 210–218[ISI][Medline]
  14. K/DOQI Clinical Practice Guidelines for Chronic Kidney Disease: evaluation, classification, and stratification. Am J Kidney D, 2002; 39 [Suppl. 1]: S1–S261
  15. K/DOQI clinical practice guidelines for chronic kidney disease: evaluation, classification, and stratification. Kidney Disease Outcome Quality Initiative. Am J Kidney Dis 2002; 39 [2 Suppl 2]: S1–246
  16. Newby LK, Bhapkar MV, White HD et al. Predictors of 90-day outcome in patients stabilized after acute coronary syndromes. Eur Heart J 2003; 24: 172–181[Abstract/Free Full Text]
  17. Smith PL. Splines as a useful and convenient statistical tool. Am Stat 1979; 33: 57–62[ISI]
  18. Rosenbaum PR, Rubin DB. Reducing bias in observational studies using subclassification on the propensity score. J Am Stat Assoc 1984; 79: 516–524[ISI]
  19. Cook EF, Goldman L. Asymmetric stratification. An outline for an efficient method for controlling confounding in cohort studies. Am J Epidemiol 1988; 127: 626–639[Abstract]
  20. Myers WO, Schaff HV, Fisher LD et al. Time to first new myocardial infarction in patients with severe angina and three-vessel disease comparing medical and early surgical therapy: a CASS registry study of survival. J Thorac Cardiovasc Surg 1988; 95: 382–389[Abstract]
  21. Reddan DN. Therapy for cardiovascular disease in patients with chronic kidney disease: appropriate caution or the absence of data. Am Heart J 2002; 144: 206–297[CrossRef][ISI][Medline]
  22. Kocheril AG. Arrhythmia issues in patients with renal disease. Semin Nephrol 2001; 21: 57–65[CrossRef][ISI][Medline]
  23. Shoji T, Emoto M, Kawagishi T et al. Atherogenic lipoprotein changes in diabetic nephropathy. Atherosclerosis 2001; 156: 425–433[CrossRef][ISI][Medline]
  24. Reddan DN, O'Shea JC, Sarembock IJ et al. Treatment effects of eptifibatide in planned coronary stent implantation in patients with chronic kidney disease (ESPRIT Trial). Am J Cardiol 2003; 91: 17–21[ISI][Medline]
  25. Vervoort G, Willems HL, Wetzels JF. Assessment of glomerular filtration rate in healthy subjects and normoalbuminuric diabetic patients: validity of a new (MDRD) prediction equation. Nephrol Dial Transplant. 2002; 17: 1909–1913[Abstract/Free Full Text]
  26. Peto R. Misleading subgroup analyses in GISSI. Am J Cardiol 1990; 66: 771–772[Medline]
Received for publication: 10. 9.04
Accepted in revised form: 1. 6.05





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