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NDT Advance Access published online on August 5, 2008
Nephrology Dialysis Transplantation, doi:10.1093/ndt/gfn426
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© The Author [2008]. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved. For Permissions, please e-mail: journals.permissions@oxfordjournals.org


Risk factors for non-fatal myocardial infarction and cardiac death in incident dialysis patients

Hariprasad Trivedi, Qun Xiang and John P. Klein

Medical College of Wisconsin, Milwaukee, WI, USA

Correspondence and offprint requests to: Hariprasad S. Trivedi, 9200 W. Wisconsin Ave., Milwaukee, WI 53226, USA. Tel: +1-414-805-9050; Fax: +1-414-805-9059; E-mail: htrivedi{at}mcw.edu



   Abstract
Top
 Abstract
Introduction
 Methods
 Results
 Discussion
 References
 
Background. The risks of major cardiac events in patients initiating long-term dialysis related to prior coronary disease and various other factors are not well known.

Methods. We used United States Renal Data System data to analyse the outcomes of non-fatal myocardial infarction (MI) and cardiac death in incident dialysis patients from years 1997 through 2001 (n = 214 890). The presence of established coronary artery disease was determined from the Medical Evidence form, non-fatal MI events were determined from Medicare claims’ data and cause of death was determined from the Death Notification form. Multivariable analyses were performed employing Cox proportional hazards models using demographics, co-morbidities, laboratory variables, prior erythropoietin use, body mass index and type of dialysis.

Results. In patients with prior coronary disease as compared to those without, the adjusted relative risk of non-fatal MI was 1.57 (95% CI, 1.5–1.65) and cardiac death was 1.16 (95% CI, 1.14–1.18). The 5-year cumulative incidence of non-fatal MI was 8.1 and 6% and cardiac death was 48.3 and 40.2%, in patients with and without prior coronary disease, respectively. Amongst important factors, blacks had a lower risk of non-fatal MI and cardiac death as compared to whites. A history of hypertension conferred a lower independent risk of cardiac death events. Lower haemoglobin, higher albumin and higher creatinine values each conferred a lower independent risk of non-fatal MI and cardiac death.

Conclusions. Incident dialysis subjects with prior coronary disease have a risk of non-fatal MI greater by 57% and cardiac death by 16% as compared to subjects without prior coronary disease. In both populations, the competing risk of cardiac death is several-fold greater than that of non-fatal MI. There are several factors suggesting reverse epidemiology phenomena with respect to major cardiac events in the dialysis population.

Keywords: cardiac death; end-stage renal disease; epidemiology; myocardial infarction; risk factors



   Introduction
Top
 Abstract
 Introduction
Methods
 Results
 Discussion
 References
 
Poor survival of patients with end-stage renal disease (ESRD) on dialysis continues to be a major problem. In the United States, mortality rates in subjects on long-term dialysis have stubbornly exceeded 20% per year for more than a decade and cardiac causes consistently account for >40% of the deaths [1,2]. In this population, the mortality due to ischaemic heart disease is several-fold greater than the general population [3]. Incident dialysis subjects have a dismal survival rate after acute myocardial infarction (AMI) with a 1-year survival of only ~41% and 2-year survival only 27% [4]. There is an urgent need to implement strategies to reduce these high death rates.

However, the risks of major cardiac events related to prior coronary disease and various other factors present at the time of initiation of long-term dialysis are not well understood. It is also necessary to understand the competing risks of fatal and non-fatal events in these groups of subjects, an issue with implications for targeting investigation and therapeutic interventions. We examined data in a large cohort of patients initiating dialysis therapy and analysed the outcomes of non-fatal MI and cardiac death.



   Methods
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 Abstract
 Introduction
 Methods
Results
 Discussion
 References
 
We used the United States Renal Data System (USRDS) and identified incident Medicare dialysis patients in the years 1997–2001 who survived at least 90 days after the onset of ESRD, and who did and did not have prior coronary disease. The 90-day rule for outcome analysis using USRDS data is well accepted [5] and is based on difficulties of examining data from the first 3 months of ESRD service, which is an unstable time for new patients as renal providers try to determine the best treatment modalities. Furthermore, in-centre dialysis patients younger than 65 and who are not disabled cannot bill Medicare, the primary payer for the majority of dialysis patients until Day 90 after the first ESRD service date. Prior history of coronary disease was determined from the Medical Evidence Form (Form 2728) that is required to be filled for every patient initiating dialysis therapy and contains a variety of medical and demographic data. By regulation, the patient's attending physician is responsible for the information on the form, attested thus by his or her signature. If the form indicated that the patient had a diagnosis of ischaemic heart disease/coronary artery disease (CAD) or MI, then the patient satisfied the definition of coronary disease.

Non-fatal AMI events were determined from claims’ data based on an admission related to ICD-9-CM diagnosis codes 410, 410.x0 or 410.x1 as the principal or secondary diagnosis codes followed by discharge from the hospital alive. Cardiac death data were obtained from the Death Notification Form (Form 2746) that is required for every death amongst this population and lists the primary and secondary causes of death. Death coded as any of the following was defined as cardiac death: myocardial infarction, acute, atherosclerotic heart disease, cardiomyopathy, pericarditis (including cardiac tamponade), cardiac arrhythmia, cardiac arrest (cause unknown), valvular heart disease and pulmonary oedema due to exogenous fluid.

Follow-up was from Day 90 of ESRD onset to the earliest of transplant, loss-to-follow-up, end of Medicare as primary payer status, 5 years after study start date or 31 December 2002. The end-points were non-fatal AMI and cardiac death events. Cardiac aetiologies as primary and secondary causes of death were considered.

The study was approved by the Institutional Review Board of the Medical College of Wisconsin and USRDS data were obtained via a Data Use Agreement with the National Institute of Diabetes and Digestive and Kidney Diseases.

Statistical methods
Adjusted risk of events was determined using proportional hazards models adjusting for age, gender, race, ethnicity, tobacco use, substance abuse, serum albumin, haematocrit, creatinine, prior erythropoietin (EPO) use, body mass index, type of dialysis and co-morbid conditions listed on the Medical Evidence form.

A Cox proportional hazards model was used to evaluate which of the covariates were associated with the outcomes of interest. For each factor, we examined the proportional hazards assumption using a time-dependent covariate model and found no evidence of non-proportionality [6]. The functional form of the continuous covariates was examined using martingale residual plots [6], which suggested that age and body mass index were best explained using a continuous covariate technique. Continuous laboratory variables (haematocrit, serum albumin and serum creatinine) were examined as continuous covariates, and in order to identify potential thresholds, dichotomized into two or three groups based on the maximum likelihood approach [7]. A series of models were built using a backward stepwise regression technique. We included only those factors that had a difference in relative risk of events by >10% (<0.91 or >1.1) in the final model. The rationale for the latter was to include factors that had a clinical significance and not simply statistical significance. All models a priori included the main factor of prior coronary heart disease. A 5% significance level was used for including factors into the final model. End-points were summarized using cumulative incidence functions, and estimates of survival using the Kaplan–Meier estimator were used to describe the composite outcomes of non-fatal MI or cardiac death [6]. The analysis was carried out using SAS® statistical software version 9.1.1 (SAS Institute Inc., Cary, NC, USA).



   Results
Top
 Abstract
 Introduction
 Methods
 Results
Discussion
 References
 
There were 214 980 subjects, 27.4% of whom had documented coronary disease prior to the initiation of dialysis therapy. The population consisted of 53.6% males, majority whites (63.9%), with a median age of 65 years (range 0–113 years). There were marked differences in the characteristics of incident dialysis subjects with and without prior coronary disease. Subjects with prior coronary disease were older, a greater proportion of males, a greater proportion of whites, and had higher haematocrit and lower serum creatinine values. The patient characteristics are shown in Table 1.


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  		Table 1 Patient characteristics

 
From Years 1 through 5, the cumulative incidence of non-fatal MI, cardiac death as the primary cause and cardiac death as any (primary or secondary) cause was greater in subjects with documented coronary disease at the initiation of dialysis. Across all years, the cumulative incidence of cardiac death (either primary or any cause) as the first event was several-fold higher (about five to seven times) as opposed to non-fatal MI both in subjects with and without coronary disease (Figure 1A). For instance, the 5-year cumulative incidence of non-fatal MI was 8.1 and 6% and that of cardiac death was 48.3 and 40.2%, in patients with and without prior coronary disease, respectively. Kaplan–Meier event-free survival curves are shown in Figure 1B.


Figure 1
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  		Fig. 1 Cumulative incidence (A) and event-free Kaplan–Meier survival (B) curves of non-fatal myocardial infarction and cardiac death events.

 
Table 2 depicts the risks of non-fatal MI and cardiac death events independently related to prior coronary disease and other significant factors considering continuous variables as continuous covariates. Prior coronary disease was associated with an increased risk of non-fatal MI by 57%, cardiac death as primary cause by 16% and cardiac death as either the primary or secondary cause by 18%.


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  		Table 2 Multivariate analysis results depicting risks (95% confidence intervals) of non-fatal myocardial infarction and cardiac death events in incident dialysis patients related to various factors

 
Each year of age at the initiation of dialysis conferred an increased risk of cardiac death by ~2.8%. Likewise male gender was associated with a significantly increased risk of cardiac death but not non-fatal MI. As compared to whites, blacks had a decreased risk of all events. Diabetic status conferred an increased relative risk of all outcomes. However, a history of hypertension was associated with a lower risk of cardiac death.

Table 3 shows the independent association of laboratory variables with non-fatal MI and cardiac death events. Higher haematocrit at the initiation of dialysis was associated with an increased risk of non-fatal MI and cardiac death. The relationship was seen for all outcomes when examined as a continuous covariate. When statistically dichotomized into groups of two (>28% versus ≤28%) or three (≤22%, 23–25% and ≥26%), there appeared to be a lower threshold value for the outcomes of non-fatal MI and cardiac death as any cause (Figure 2 and Figure 3, panel A). In these instances the risks became statistically significant for haematocrit values ≥26%. No such threshold was observed for cardiac death as the primary cause. In all instances the trend favoured lower risk with lower haematocrit.


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  		Table 3 Multivariate analysis results depicting risks (95% confidence intervals) of non-fatal myocardial infarction and cardiac death events in incident dialysis patients related to laboratory parameters

 

Figure 2
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  		Fig. 2 Relative risks of non-fatal myocardial infarction (I), cardiac death as primary cause (II), cardiac death as any cause (III), non-fatal myocardial infarction or cardiac death as primary cause (IV) and non-fatal myocardial infarction or cardiac death as any cause (V) related to haematocrit (%), serum albumin (g/dL) and serum creatinine (mg/dL) values dichotomized into two groups (vertical lines represent 95% confidence intervals).

 

Figure 3
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  		Fig. 3 Relative risks of non-fatal myocardial infarction (MI) and cardiac death (CD) events related to haematocrit, albumin and creatinine values divided into three groups: for haematocrit, I represents 23–25 versus ≤22, II represents ≥26 versus 23–25, III represents ≥26 versus ≤22; for albumin, I represents 3.3–3.6 versus ≤3.2, II represents ≥3.7 versus 3.3–3.6, III represents ≥3.7 versus ≤3.2; for creatinine, I represents 6.6–10.4 versus ≤6.5, II represents ≥10.5 versus 6.6–10.4, III represents ≥10.5 versus ≤6.5.

 
Higher albumin at the initiation of dialysis was associated with a lower adjusted risk of non-fatal MI and cardiac death events. For outcomes that included any cardiac death event, the relationship was seen consistently, whether analysed as a continuous covariate or in two (>3.7 g/dL versus ≤3.7 g/dL) or three groups (≤3.2 g/dL, 3.3–3.6 g/dL and ≥3.7 g/dL), without any evident threshold value. There appeared to be a threshold value related to the risk of non-fatal MI, the risk being lower for albumin ≥3.7 g/dL (Figure 2 and Figure 3, panel B).

Higher creatinine at the initiation of dialysis was associated with a lower risk of all non-fatal MI and cardiac death events, the relationship being consistent whether analysed as a continuous covariate, or in two (>6.5 mg/dL versus ≤6.5 mg/dL) or three (≤6.5 g/dL, 6.6–10.4 mg/dL and ≥10.5 mg/dL) groupings. No threshold value was evident for any of the outcomes (Figure 2 and Figure 3, panel C).



   Discussion
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 Abstract
 Introduction
 Methods
 Results
 Discussion
References
 
Patients initiating dialysis therapy with prior diagnosed coronary disease (CAD) have a risk of non-fatal MI greater by 57% and a risk of cardiac death greater by 14% as compared to subjects without documented coronary disease. There is a need to study coronary disease management strategies in this population that might reduce the high event rates. Further, the analyses showed that the cumulative incidence of cardiac death was several-fold greater than the incidence of non-fatal MI (Figure 1A). The striking differences between the competing risks of cardiac death and non-fatal MI were consistent, evident even in patients without prior coronary disease, and through all the years of analysis. While this does raise the issue of over-classification of death attributed to a cardiac aetiology, in clinical trials with adjudication committees, cardiac death rates in this population have been shown to be as high as 38% over a period of <4 years [8]. Such a pattern is reverse as compared to the non-renal failure subjects in whom non-fatal events greatly exceed fatal events [9,10] and possibly explains the lack of significant improvement in cardiac mortality in the dialysis population in spite of several overall advances in ESRD therapy. There is quite a small window of opportunity to intervene and little scope for secondary prevention in patients without known coronary disease since the first event is more likely to be death. Clinical studies are necessary, aimed at reduction of cardiac death events.

Several important risk factors were identified that independently impact the risk of non-fatal MI and cardiac death in patients with ESRD initiating dialysis therapy.

African Americans had a lower risk of non-fatal MI and cardiac death. This pattern of risk is similar to better survival of minorities on dialysis reported in prior studies [11–13]. Though one smaller study found that these differences were mitigated, and though the trend persisted, when adjusting for patient-level factors the weight of evidence suggests better mortality outcomes in minorities, particularly African Americans [14,15]. Whether these outcomes are due to survivor bias or other factors needs investigation. Understanding why minorities have better outcomes, or a pattern of factors that lead to the same, might help to improve overall outcomes of ESRD subjects.

As might be expected, diabetic status was related to a higher risk of all outcomes. However, a history of hypertension was associated with a lower risk of cardiac death. The latter results are consistent with a pattern of reverse epidemiology related to hypertension and survival that has been previously reported in haemodialysis subjects [16]. While there is no question regarding hypertension as a cardiovascular risk factor in the general population, hypertension in patients on dialysis is a complex and controversial issue, and the optimum goals of therapy are poorly understood [17–20]. There is clearly a need to study in-depth the appropriate approach to hypertension in dialysis subjects.

Higher haematocrit values at the initiation of dialysis were independently associated with an increased risk of serious cardiac events. Our results are in contrast with other studies that showed that higher haematocrit (or haemoglobin) values at least up to 36% (or 12 g/dL) were associated with lower risk of cardiac death in haemodialysis subjects [21–23]. The reasons for these perplexing differences are not clear but could be due to factors such as smaller sample sizes, shorter duration of follow-up, differences in the definition of cardiac death or differences in statistical modelling in previous studies. The definition of what constituted cardiac death was not expounded in these studies and cardiac aetiology as a secondary cause of death was not considered. In prior studies, the grouping of haematocrit values (or haemoglobin) to compare with each other was apparently based on intuition or in order to test existing goals while the present study used statistical methodology for discretization [6]. Findings similar to ours relating higher haemoglobin concentration at the initiation of dialysis with a greater risk of cardiac events were observed in a small prospective study (n = 169) of Japanese haemodialysis subjects [24]. Recently, considerable controversy has erupted regarding haemoglobin targets in chronic kidney disease due to adverse outcomes in trials involving erythropoiesis-stimulating agents in trial arms that targeted better haemoglobin values [25–27]. It appears that there is a need for further studies to explore the optimum haemoglobin target in chronic kidney disease that strikes a favourable balance between survival outcomes, potential benefit of EPO use, quality of life and freedom from transfusions.

Another important finding was the lower risk of major cardiac events associated with better albumin values at the initiation of dialysis. The association of low albumin values and poor overall survival is well known [28–30]. In chronic kidney disease subjects, low albumin is not necessarily of nutritional aetiology and may be related to inflammation [31]. A recent prospective study in under-nourished haemodialysis subjects that compared oral versus parenteral nutritional supplementation depicted that improvement in serum albumin was achievable regardless of the inflammatory state as measured by C-reactive protein [32]. An important observational finding that emerged from the study was that improvement in nutritional status was associated with improved survival. Since the albumin values at the initiation of dialysis reflect the pre-dialytic therapy, there is a need to investigate whether nutritional intervention in the late pre-dialytic stage of chronic kidney disease leads to better outcomes.

Higher creatinine values at the initiation of dialysis were strongly associated with a lower risk of serious cardiac events. Better survival of dialysis subjects with higher creatinine, another reverse epidemiology pattern, has been described before and could be a reflection of better muscle mass [33, 34]. On the other hand, in the fully adjusted model we did not find any meaningful association of body mass index and cardiac events regarding which a reverse epidemiology pattern has been described before [35].

Other findings of the analyses are somewhat expected, such as higher risk of cardiac death in subjects with peripheral vascular disease, prior history of cardiac dysrhythmia and those with a history of illicit drug abuse.

There are limitations of the present study. Even though such observational studies offer the opportunity to study large numbers of unselected subjects over an extended period of time, a feature that would be unfeasible in clinical trials, they cannot be considered practice changing, relationships observed cannot be concluded as being casual and findings warrant confirmation by randomized trials. Furthermore, silent MIs were not captured by our analysis and no data were available regarding the use of cardio-protective medications. The analysis of laboratory parameters is limited due to lack of availability of repeated measurements. In addition, there could be parameters that are either unmeasured or not part of reporting that impact the outcomes of interest, such as C-reactive protein, lipids and bone mineral parameters. Lastly, validity of results from analysis of registry data depends on accurate reporting, such as on the Medical Evidence Form. In a small sample of ESRD subjects, it was found that the sensitivity of reporting co-morbidity was not high though specificity was high, a factor that could lead to a bias towards the null [36]. The percent of subjects with pre-existing coronary disease in our study is similar to rates reported in incident ESRD subjects over the last several years indicating that reporting rates in these regards were consistent with historic rates [37].

To summarize, incident dialysis subjects with prior coronary disease have a significantly increased risk of non-fatal MI and cardiac death as compared to subjects without coronary disease. Even in patients without prior coronary disease, the competing risk of cardiac death is far greater than that of non-fatal MI. In subjects initiating dialysis, a pattern of reverse epidemiology is evident with respect to a history of hypertension and cardiac death. In this population, higher haematocrit, lower albumin and lower creatinine values at the initiation of dialysis are independent risk factors for non-fatal MI and cardiac death events.



   Acknowledgments
 
The authors acknowledge Na Lu, PhD, for her contribution to data analysis, Kevin Regner, MD, for assistance in statistical analysis, and Char Klis for administrative support. The authors thank James Kaufman, MD, for reviewing the manuscript and providing helpful suggestions.

Conflict of interest statement. None of the authors have any conflict of interest related to this work. The results presented in this paper have not been published previously in whole or in part.

Notice. The data reported here have been supplied by the United States Renal Data System (USRDS). The interpretation and reporting of these data are the responsibility of the author(s) and in no way should be seen as an official policy or interpretation of the U.S. government.



   References
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 

  1. USRDS. (2007) 2007 Annual Data Report. National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, USA.
  2. USRDS. (2004) 2004 Annual Data Report. National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, USA.
  3. Raine AE, Margreiter R, Brunner FP, et al. Report on management of renal failure in Europe, XXII, 1991. Nephrol Dial Transplant (1992) (Suppl_2):7–35.
  4. Herzog CA, Ma ZA, Collins AJ. Poor long-term survival after acute myocardial infarction among patients on long-term dialysis. N Engl J Med (1998) 339:799–805.[Abstract/Free Full Text]
  5. United States Renal Data. (2006) System, Researcher's Guide to the USRDS Database. National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, USA,
  6. Klein JP, Moeschberger ML. Survival Analysis: Techniques for Censored and Truncated Data (2003) 2nd edn. New York: Springer.
  7. Klein JP, Wu JT. Discretizing a continuous covariate in survival studies. In: Handbook of Statistics, 23: Advances in Survival Analysis—Balakrishnan N, Rao CR, eds. (2004) Amsterdam, The Netherlands: Elsevier. 27–42.
  8. Rocco MV, Yan G, Gassman J, et al. Comparison of causes of death using HEMO study and HCFA end-stage renal disease death notification classification systems. Am J Kidney Dis (2002) 39:146–153.[Web of Science][Medline]
  9. Shepherd J, Cobbe SM, Ford I, et alfor the West of Scotland Coronary Prevention Study Group. Prevention of coronary heart disease with pravastatin in men with hypercholesterolemia. N Engl J Med (1995) 333:1301–1307.[Abstract/Free Full Text]
  10. Scandinavian Simvastatin Survival Study Group. Randomised trial of cholesterol lowering in 4444 patients with coronary heart disease: the Scandinavian Simvastatin Survival Study (4S). Lancet (1994) 8934:1383–1389.
  11. Pugh JA, Tuley MR, Basu S. Survival among Mexican-Americans, non-Hispanic whites, and African-Americans with end-stage renal disease: the emergence of a minority pattern of increased incidence and prolonged survival. Am J Kidney Dis (1994) 23:803–807.[Web of Science][Medline]
  12. Bloembergen WE, Port FK, Mauger EA, et al. Causes of death in dialysis patients: racial and gender differences. J Am Soc Nephrol (1994) 5:1231–1242.[Abstract]
  13. Wong JS, Port FK, Hulbert-Shearon TE, et al. Survival advantage in Asian American end-stage renal disease patients. Kidney Int (1999) 55:2515–2523.[CrossRef][Web of Science][Medline]
  14. Robinson BM, Joffe MM, Pisoni RL, et al. Revisiting survival differences by race and ethnicity among hemodialysis patients: the dialysis outcomes and practice patterns study. J Am Soc Nephrol (2006) 17:2910–2918.[Abstract/Free Full Text]
  15. Price DA, Owen WF Jr. African-Americans on maintenance hemodialysis: a review of racial differences in incidence, treatment, and survival. Adv Ren Replace Ther (1997) 4:3–12.[Medline]
  16. Kalantar-Zadeh K, Kilpatrick RD, McAllister CJ, et al. Reverse epidemiology of hypertension and cardiovascular death in the hemodialysis population: the 58th annual fall conference and scientific sessions. Hypertension (2005) 45:811–817.[Abstract/Free Full Text]
  17. Hypertension Detection and Follow-up Program Cooperative Group. Five-year findings of the hypertension detection and follow-up program: I. Reduction in mortality of persons with high blood pressure, including mild hypertension. JAMA (1979) 242:2562–2571.[Abstract/Free Full Text]
  18. Vasan RS, Larson MG, Leip EP, et al. Impact of high-normal blood pressure on the risk of cardiovascular disease. N Engl J Med (2001) 345:1291–1297.[Abstract/Free Full Text]
  19. Agrawal R. Hypertension and survival in chronic hemodialysis patients—past lesions and future opportunities. Kidney Int (2005) 67:1–13.[CrossRef][Web of Science][Medline]
  20. Salem M. Hypertension in the hemodialysis population? High time for answers. Am J Kidney Dis (1999) 33:592–594.[Web of Science][Medline]
  21. Collins AJ, Li S, St Peter W, et al. Death, hospitalization, and economic associations among incident hemodialysis patients with hematocrit values of 36 to 39%. J Am Soc Nephrol (2001) 12:2465–2473.[Abstract/Free Full Text]
  22. Ma JZ, Ebben J, Xia H, et al. Hematocrit level and associated mortality in hemodialysis patients. J Am Soc Nephrol (1999) 10:610–619.[Abstract/Free Full Text]
  23. Regidor DL, Kopple JD, Kovesdy CP, et al. Associations between changes in hemoglobin and administered erythropoiesis-stimulating agent and survival in hemodialysis patients. J Am Soc Nephrol (2006) 17:1181–1191.[Abstract/Free Full Text]
  24. Tanaka Y, Joki N, Hase H. History of acute coronary events during the predialysis phase of chronic kidney disease is a strong risk factor for major adverse cardiac events in patients initiating haemodialysis. Nephrol Dial Transplant (2007) 22:2917–2923.[Abstract/Free Full Text]
  25. Besarab A, Bolton WK, Brown JK, et al. The effects of normal as compared with low hematocrit values in patients with cardiac disease who are receiving hemodialysis and epoetin. N Engl J Med (1998) 339:584–590.[Abstract/Free Full Text]
  26. Singh AK, Szczech L, Tang KL, et alfor the CHOIR Investigators. Correction of anemia with epoetin alfa in chronic kidney disease. N Engl J Med (2006) 335:2085–2098.
  27. Macdougall IC, Eckardt K-U, Locatelli F. Latest US KDOQI Anaemia Guidelines update—what are the implications for Europe? Nephrol Dial Transplant (2007) 22:2738–2742.[Free Full Text]
  28. Iseki K, Kawazoe N, Fukiyama K. Serum albumin is a strong predictor of death in chronic dialysis patients. Kidney Int (1993) 44:115–119.[Web of Science][Medline]
  29. Avram MM, Mittman N, Bonomini L, et al. Markers for survival in dialysis: a seven-year prospective study. Am J Kidney Dis (1995) 26:209–219.[Web of Science][Medline]
  30. Leavey SF, Strawderman RL, Jones CA, et al. Simple nutritional indicators as independent predictors of mortality in hemodialysis patients. Am J Kidney Dis (1998) 31:997–1006.[Web of Science][Medline]
  31. Kaysen GA, Don BR. Factors that affect albumin concentration in dialysis patients and their relationship to vascular disease. Kidney Int (2003) 84(Suppl):S94–S97.
  32. Cano NJM, Fouque D, Roth H, et althe French Study Group for Nutrition in Dialysis. Intradialytic parenteral nutrition does not improve survival in malnourished hemodialysis patients: a 2-year multicenter, prospective, randomized study. J Am Soc Nephrol. 18:2583–2591.
  33. Fink JC, Burdick RA, Kurth SJ, et al. Significance of serum creatinine values in new end-stage renal disease patients. Am J Kidney Dis (1999) 34:694–701.[Web of Science][Medline]
  34. Kalantar-Zadeh K, Block G, Humphreys MH, et al. Reverse epidemiology of cardiovascular risk factors in maintenance dialysis patients. Kidney Int (2003) 63:793–808.[CrossRef][Web of Science][Medline]
  35. Kalantar-Zadeh K, Kopple JD, Kilpatrick RD, et al. Association of morbid obesity and weight change over time with cardiovascular survival in hemodialysis population. Am J Kidney Dis (2005) 489–500.
  36. Longenecker JC, Coresh J, Klag MJ, et al. Validation of comorbid conditions on the end-stage renal disease medical evidence report: the CHOICE study. J Am Soc Nephrol (2000) 11:520–529.[Abstract/Free Full Text]
  37. USRDS. (2005) 2005 Annual Data Report. National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, USA,
Received for publication: 7. 3.08
Accepted in revised form: 4. 7.08


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