Risk Factors for Incident Stroke among Patients with End-Stage Renal Disease
Stephen L. Seliger*,
Daniel L. Gillen,
David Tirschwell,
Haimanot Wasse*,
Bryan R. Kestenbaum* and
Catherine O. Stehman-Breen
*Division of Nephrology, University of Washington, Seattle, Washington; Department of Biostatistics, University of Washington School of Public Health and Community Medicine, Seattle, Washington; Department of Neurology, University of Washington, Seattle, Washington; and Division of Nephrology, Veterans Affairs Puget Sound Health Care System, University of Washington, Seattle, Washington
Correspondence to Dr. Stephen L. Seliger, Division of Nephrology, Box 356521, University of Washington, Seattle, WA 98102. Phone: 206-543-3792; Fax: 206-685-8661;
ABSTRACT. Although patients with ESRD experience markedly higherrates of stroke, no studies in the US have identified risk factorsassociated with stroke in this population. It was hypothesizedthat black race, malnutrition, and elevated BP would be associatedwith the risk of stroke among patients with ESRD. Data fromthe United States Renal Data Systems were used. Adult Medicare-insuredhemodialysis and peritoneal dialysis patients without a historyof stroke or transient ischemic attack (TIA) were consideredfor analysis. The primary outcome was hospitalized or fatalstroke. Cox proportional hazards models were used to determinethe associations between the primary predictor variables andstroke. The rate of incident stroke was 33/1,000 person-yearsin the study sample. After adjustment for age and other patientcharacteristics, three markers of malnutrition were associatedwith the risk of strokeserum albumin (per 1 g/dl decrease,hazard ratio [HR] = 1.43), height-adjusted body weight (per25% decrease, HR = 1.09), and a subjective assessment of undernourishment(HR = 1.27)as was higher mean BP (per 10 mmHg, HR = 1.11).The association between black race varied by cardiac diseasestatus, with blacks estimated to be at lower risk than whitesamong individuals with cardiac disease (HR = 0.74), but at higherrisk among individuals without cardiac disease (HR = 1.24).This study confirms the extraordinarily high rates of strokein ESRD patients on dialysis and identifies high mean BP andmalnutrition as potentially modifiable risk factors. The associationbetween black race and stroke differs by cardiac disease status;the reasons for this differing effect of race deserve furtherinvestigation. E-mail: seliger@u.washington.edu
Patients with ESRD experience markedly advanced atheroscleroticdisease of the cerebral vasculature (14). Although werecently reported a 5- to 10-fold risk of hospitalized ischemicand hemorrhagic stroke among ESRD patients compared with non-ESRDindividuals (5), little is known regarding potential strokerisk factors among the ESRD population. Risk factors for strokein this population are likely to differ from those in the non-ESRDpopulation. For example, elevated BP and body mass index arerisk factors for stroke in the general population, whereas inthe dialysis population, they are associated with a lower riskof adverse outcomes such as all-cause and cardiac death (69).Only one small study, conducted in a Japanese dialysis population,has examined risk factors for stroke (10), identifying hypertensionas the only significant predictor. However, the study had limitedpower, and results from the younger and healthier Japanese dialysispopulation (11) may not be generalizable to the US dialysispopulation. In addition, although blacks have much higher ratesof stroke in the general population, no previous studies haveexamined black race as a risk factor for incident stroke inthe dialysis population. We used data collected by the UnitedStates Renal Data System (USRDS) to identify patient characteristicsassociated with the risk of hospitalized or fatal stroke indialysis patients, with specific focus on black race, hypertension,and malnutrition as risk factors.
Study Population
We used data from the USRDS Dialysis Morbidity and MortalityStudies, Waves 2 to 4 (DMMS-2 to -4). Details of the studiesperformed by the USRDS are described elsewhere (12). Briefly,the USRDS collects demographic and clinical data on all patientswho have survived >90 d of renal replacement therapy forESRD. DMMS-2 was a prospective observational study of a sampleof adult patients who initiated dialysis in 1996 and early 1997,with deliberate oversampling of patients on peritoneal dialysis.DMMS-3 and -4 were retrospective studies of random samples ofhemodialysis patients who were alive on December 31, 1993. Datacollection techniques and content were kept consistent acrossthe three studies, allowing them to be combined for use in epidemiologicresearch. The study population for this analysis included allpatients who were in DMMS-2 to -4 and treated with dialysisand were Medicare-insured with no previous history of strokeor transient ischemic attack. Following the recommendationsof the USRDS for studies of hospitalization rates (13), patientsfor whom fee-for-service Medicare was not the primary insurerwere excluded from our analysis, because hospitalization datafor these patients are incomplete in the USRDS database (seethe Outcome section).
Ascertainment of Baseline Patient Characteristics
Baseline patient data were abstracted by dialysis facility personnelfrom each patients medical record and through patientinterview. Patient characteristics ascertained included demographic(age, gender, and race), laboratory (albumin, cholesterol, hemoglobin,calcium, parathyroid hormone, and phosphorous), clinical (causeof renal disease, history of cardiovascular disease (CVD), historyof stroke or transient ischemic attack (TIA), dialysis vintage,smoking status, and a subjective assessment of undernourishment),and other measurements (height, weight, and BP). Previous CVDwas defined as any diagnosis of coronary artery disease, myocardialinfarction, coronary artery bypass, angioplasty, cardiac arrest,or congestive heart failure. The average of up to three measurementsof BP during three consecutive dialysis sessions, recorded eitherbefore dialysis (in hemodialysis patients) or randomly (in peritonealdialysis patients), were used in this analysis. For DMMS-2 patients,only single measurements of laboratory variables were available.For patients in DMMS-3 and -4, multiple values for laboratorymeasurements were available for up to 3 mo preceding the startof the study; for these patients, all available values wereaveraged before inclusion into a statistical model.
Outcome
The primary outcome was defined as first hospitalized strokeor fatal nonhospitalized stroke. Hospitalization for strokewas determined by linking Medicare hospital billing recordsto each patient through unique identifier codes supplied bythe USRDS. Diagnosis of stroke was based on the InternationalClassification of Diseases, 9th Revision, Clinical Modification(ICD-9-CM) diagnosis codes contained in these billing records.On the basis of previous studies that examined the relativeaccuracy of different ICD-9-CM diagnosis codes in identifyingpatients with actual hospitalized stroke (1418), we apriori considered the following five codes to identify acutestroke: 430 (subarachnoid hemorrhage), 431 (intracerebral hemorrhage),433.X1 (occlusion of precerebral arteries with infarction),434.X1 (occlusion of cerebral arteries with infarction), and436 (acute cerebrovascular attack), where "X" can be any integerfrom 0 to 9 and refers to specific arterial syndromes. A hospitalizationin which one of these five diagnosis codes was listed in eitherthe primary or the nine secondary positions reported by theUSRDS was considered stroke related.
For information on fatal stroke, survival status and cause ofdeath were linked to the DMMS data from the USRDS Patients StandardAnalysis File via unique patient identifiers. The date and causeof death listed in a patients Standard Analysis Filewas obtained from information submitted to the USRDS by thepatients nephrologist (form HCFA 2746). Fatal nonhospitalizedstroke was defined as a primary cause of death from either "cerebrovasculardisease" or "cerebrovascular accident including intracranialhemorrhage" without a preceding hospitalization for stroke.
Secondary outcomes included hospitalized hemorrhagic stroke(ICD-9 codes 430, 431) and ischemic stroke (codes 433.X1, 434.X1,or 436). Data on hospitalization and mortality were availablethrough December 31, 1999.
Statistical Analyses
The Cox proportional hazards model for censored survival datawas used to assess the association between the primary riskfactors of interest and incident stroke after adjustment forpotential confounders. Primary predictor variables of interestincluded race (white, black, Asian, other), mean BP (MBP; calculatedas [systolic BP + 2*diastolic BP]/3), and markers of malnutrition(serum albumin, body weight, and a subjective assessment ofundernourishment). Adjustment variables to control confoundingwere a priori chosen on the basis of their potential relationshipwith the outcome of interest. Cigarette smoking was not includedas an adjustment covariate in the primary model because of thehigh degree of missing information (15%) for this variable inthe USRDS; rather, the potential confounding effect of smokingwas assessed in an exploratory analysis. Renal replacement modality(hemodialysis, peritoneal dialysis, transplant) was modeledas time-dependent covariates, allowing patients to switch riskgroups over the course of follow-up. All models were furtheradjusted for DMMS study via stratification.
Following recommendations from the USRDS (13), incident patientswere not considered at risk for hospitalizations until day 90of ESRD. Patients were followed from day 90 of ESRD or (forprevalent patients) from the DMMS study start date and werecensored at loss to follow-up, nonstroke death, or the end ofthe study period (December 31, 1999).
Formal and graphic techniques were used to confirm the presenceof proportional hazards and to identify potential outliers.We hypothesized that all continuous covariates would be linearlyrelated to the outcome of interest; however, exploratory residualanalyses were performed to investigate functional form further.In particular, we explored linear and nonlinear forms of MBPto determine whether there was a "U"- or "J"-shaped relationshipbetween BP and stroke. Effect modification by age, gender, CVD,and DMMS wave was explored and tested via stratification andthe use of multiplicative interactions.
Study Population
A total of 13,716 patients were included in DMMS-2 to -4. Atotal of 712 patients were excluded because their DMMS studystart date was missing or implausible (n = 120) or because theydid not have information on mortality or treatment history (n= 365), were younger than 18 yr (n = 22), did not survive untilday 90 of ESRD care (n = 125), had a functioning transplantat the study start date (n = 30), or had other errors in theirbaseline data collection (n = 50). Finally, because we wereinterested in risk factors for incident stroke only, we excluded1958 patients with a reported history of stroke or TIA beforestudy start date. After these exclusions, 11,046 patients remained.Of these, 2126 (19%) patients did not have Medicare as a primaryinsurer at the start of follow-up and were excluded. Baselinecharacteristics of the final study cohort of 8920 patients arepresented in Table 1. There were 6862 patients with completedata available for inclusion in the fully adjusted multivariatemodels; baseline characteristics were similar in this groupcompared with the total cohort (Table 1).
Table 1. Characteristics of study cohort at baselinea
All Strokes
In the total cohort, 915 hospitalized or fatal nonhospitalizedstrokes occurred over a median follow-up of 3.1 yr, with anincidence density of 33/1000 person-years (95% confidence interval[CI]: 31 to 35). Model-based unadjusted and adjusted estimatesof the association of patient characteristics with incidentstroke are presented in Table 2. The association between raceand incident stroke differed significantly among individualswith and without prevalent CVD (P = 0.001 for test of interaction).Among patients without prevalent CVD, blacks were estimatedto be at higher risk of stroke when compared with whites (hazardratio [HR] = 1.24; 95% CI = 0.96 to 1.6), whereas among patientswith prevalent CVD, blacks were at significantly lower risk(HR = 0.74; 95% CI = 0.60 to 0.92). Patients of other raceswere not found to have experienced a significantly differentrisk of stroke, regardless of CVD status (Table 2).
Table 2. Patient characteristics associated with incident strokea
Among our other predictors of interest, markers of malnutritionall were strongly associated with a higher risk of stroke. Patientswho were described by dialysis staff as being undernourishedwere estimated to have a 27% higher risk of stroke (HR = 1.27;95% CI = 1.01 to 1.61). A 1-g/dl decrement in serum albuminwas associated with a 43% higher risk of stroke (HR = 1.43;95% CI = 1.17 to 1.74), and there was a trend toward higherrisk of stroke associated with low body weight, after adjustmentfor height (per 25% relative decrease, HR = 1.08; 95% CI = 1.00to 1.18; P = 0.057).
MBP was also predictive of incident stroke with an increaseof 10 mmHg in MBP associated with an 11% increased risk of stroke(HR = 1.11; 95% CI = 1.05 to 1.18). There was no evidence ofexcess risk at very low BP (e.g., MBP <75 mmHg), althoughthere were relatively few patients in this category (n = 183,eight strokes). The association of MBP with incident strokewas similar among hemodialysis (when measured before dialysis)and peritoneal dialysis patients (measured randomly) and amongpatients of different races, types of renal disease, and durationof ESRD (P > 0.05 for all tests of interaction; data notshown). Among hemodialysis patients, postdialysis MBP was notsignificantly associated with incident stroke (per 10 mmHg increment,HR = 1.03; 95% CI = 0.95 to 1.12), and adjustment for this BPmeasurement did not meaningfully change the HR estimate forpredialysis MBP. Further adjustment for smoking status did notmaterially change the associations between any of the primarypredictors and stroke, and smoking was not a significant independentpredictor of stroke (data not shown).
In exploratory analyses, we assessed the association with strokeof other laboratory parameters that could possibly contributeto the risk of stroke in the dialysis population. There wasno relationship between baseline cholesterol (per 10 mg/dl increment,HR = 1.00), serum calcium, phosphorous, or parathyroid hormoneand incident stroke (data not shown). Among hemodialysis patients,the change in MBP from predialysis to postdialysis was not associatedwith incident stroke (P = 0.7). Hemoglobin levels were modestlyassociated with stroke, after adjustment for other covariates.In comparison with patients with hemoglobin levels of 10 to12 g/dl, those with very low hemoglobin (<9 g/dl) were ata 22% higher risk for stroke (HR = 1.22, 95% CI = 1.00 to 1.49).
Hemorrhagic Strokes
A total of 131 incident hospitalized hemorrhagic strokes occurredduring the follow-up period, with an estimated incidence densityof 4.6 per 1000 person-years (95% CI = 3.9 to 5.5). Patientcharacteristics associated with risk of hemorrhagic stroke areshown in Table 3. The association between race and hemorrhagicstroke differed significantly among individuals with and withoutprevalent CVD (P = 0.002 for test of interaction). Comparedwith whites without CVD, blacks without CVD had twice the rateof hemorrhagic stroke (HR = 2.19; 95% CI = 1.21 to 3.98). Amongindividuals without CVD, however, blacks had much lower ratesof hemorrhagic stroke (HR = 0.52; 95% CI = 0.24 to 1.10).
Table 3. Patient characteristics associated with incident hemorrhagic strokea
Higher MBP was associated with a higher stroke risk (per 10mmHg increase, HR = 1.32; 95% CI = 1.15 to 1.53). Among themarkers of malnutrition, undernourishment showed a trend towardan association with a higher stroke rate (HR = 1.76; 95% CI= 0.98 to 3.18); serum albumin and height-adjusted weight werenot predictive of stroke. Patients with polycystic kidney diseasewere at a 2.5-fold risk for hemorrhagic stroke compared withpatients with primary glomerulonephritis (HR = 2.55; 95% CI= 0.94 to 6.86), although this association was short of statisticalsignificance (P = 0.07).
Ischemic Stroke
There were 700 incident hospitalized ischemic strokes observedover the course of follow-up, corresponding to an incidencedensity of 25.2/1000 person-years (95% CI = 23.4 to 27.1). Forischemic stroke, the effects of the major predictors of interestdiffered among patients with and without prevalent CVD (P <0.05 for interaction terms), so separate multivariate modelswere developed for these two subgroups (Table 4). Among patientswith prevalent CVD, blacks were at 23% lower risk of ischemicstroke when compared with whites (HR = 0.77; 95% CI = 0.60 to0.98), and there were no significant associations between BPand stroke. Among the markers of malnutrition, only a subjectiveassessment of undernourishment was associated with higher strokerisk (HR = 1.40; 95% CI = 1.02 to 1.92). Among patients withoutprevalent CVD, blacks were at equal risk to whites, and higherMBP was associated with an increased risk for ischemic stroke(HR per 10 mmHg increment, HR = 1.16; 95% CI = 1.04 to 1.30).Low serum albumin levels in this subgroup were also associatedwith a higher ischemic stroke risk (per 1-g/dl decrease, HR= 1.84; 95% CI = 1.28 to 2.64), although height-adjusted bodyweight was not.
In a cohort of incident and prevalent US dialysis patients,the incidence of hospitalized and fatal stroke was 33/1000 person-years.Markers of malnutrition (low height-adjusted body weight, hypoalbuminemia,and undernourishment) and elevated MBP were predictive of incidentstroke, as was low hemoglobin. Stroke risk among blacks relativeto whites differed among those with and without clinical cardiacdisease: their risk was somewhat higher among individuals withoutcardiac disease but was significantly lower among individualswith cardiac disease.
Most studies of stroke in the general population have foundthat blacks are at a 50 to 200% higher risk than whites (14,15,1924).This increased risk seems to be independent of traditional strokerisk factors such as hypertension and diabetes (14,20,24). Toour knowledge, no study has examined whether these racial differencesin stroke rate differ by cardiac disease status. In the dialysispopulation, although racial differences in stroke incidencehave not been assessed, previous studies reported a lower rateof all-cause mortality, cardiac-specific mortality (25), cerebrovascularmortality (26), and coronary artery disease prevalence (27).Our finding of a significant and large interaction between raceand prevalent cardiac disease on the risk of stroke raises thequestion of whether a similar interaction exists with regardto other important outcomes.
The reason for this interaction is unclear. One possible explanationis a nondifferential misclassification of cardiac disease betweenblacks and whites. Information on comorbid illness in DMMS wasobtained by dialysis facility personnel from the patients themselvesand from notation in the medical record available in the dialysiscenters; there was no independent verification of comorbid status.If cardiac disease was less accurately characterized among blackpatients (as a result of less self-knowledge of their medicalconditions or because of lower rates of screening for cardiacdisease) than among whites, then resulting selective misclassificationwould create the appearance of an interaction between blackrace and cardiac disease.
If the observed interaction between race and CVD is not dueto bias, then one interpretation of this interaction is thatblacks are less "susceptible" to the adverse effects of CVDon risk of stroke. Some authors have suggested that a selectionprocess occurs in which blacks who have early renal diseaseand survive long enough to reach ESRD represent a relativelyhealthier subgroup, as a result of a competing risk betweena premature death and ESRD among blacks (28). In this scenario,blacks with cardiac disease and early renal insufficiency wouldbe more likely to have a premature death before reaching ESRDthan whites with similar cardiac disease, such that only blackswho are in some way more "resistant" to the effects of thiscardiac disease would survive to ESRD. Although this is a plausiblehypothesis, there is currently neither supporting nor refutingevidence.
Consistent with data from the general population (2932),elevated BP was associated with an increased risk for stroke.We found no evidence of a U- or J-shaped effect of MBP. Ourfinding is also in agreement with those of Iseki et al. (10),who reported a 120% increased stroke risk associated with hypertensionin a Japanese dialysis cohort. The effect of BP on stroke riskseems to differ from its effect on all-cause mortality, as suggestedby several studies in which predialysis BP (especially systolicBP) was inversely related to mortality risk, with an excessrisk at low BP (68). Among hemodialysis patients, wedid not find an association between postdialysis BP and stroke,in contrast to previous reports suggesting a U-shaped associationbetween postdialysis BP and mortality (6,7).
The finding of a positive relationship between BP and strokeshould be interpreted with some caution. Our analysis did notdistinguish those patients using antihypertensive medications,and it is possible that the effect of BP is confounded by theuse of these medications or differs among patients accordingto their use of antihypertensives. In addition, the observedeffect of BP could be biased by a competing risk between mortalityand stroke, in which patients with low BP are less likely tosurvive long enough to be at risk for stroke.
In an exploratory analysis, profound anemia (hemoglobin <9.0g/dl) was associated with a significant 22% increase risk ofstroke, compared with a hemoglobin level of 10 to 12 g/dl. Thisis in strong contrast to findings from the general population,in which high, not low, hemoglobin was associated with an increasedrisk (3336). However, these studies may have had insufficientpower to detect an association between very low hemoglobin levelsand stroke given the low prevalence of severe anemia in thenon-ESRD population. Our findings may represent a type I error,given that several secondary risk factors were tested for associationwith incident stroke. However, an increased risk of stroke fromprofound anemia in ESRD is biologically plausible and couldbe mediated either through the direct effects of low oxygen-carryingcapacity in regions of the brain already poorly perfused fromvascular disease or dialysis-related hypotension or throughthe detrimental effects of chronic anemia on arterial and cardiachypertrophy (37), which are associated with increased strokerisk in the non-ESRD population (38,39).
In the current study, several markers of malnutrition, includinglow serum albumin, low height-adjusted body weight, and a subjectiveassessment of undernourishment, were associated with a higherrisk of incident stroke. This is in contrast to the generalpopulation, in which obesity, rather than malnutrition, confersa higher stroke risk (40). However, malnutrition has been wellrecognized as a strong risk factor for total (4144) andcardiovascular-specific (9) mortality in the dialysis population.Several authors have suggested that malnutrition in ESRD patientsreflects not merely poor nutrient intake but also the effectsof a chronic microinflammatory state (45,46). Elevated inflammatorymarkers have been associated with higher rates of stroke inthe general population (4749). It is possible that themechanism that leads to the association of inflammation andstroke in the general population exerts a similar effect inthe dialysis population and might explain the observed associationbetween malnutrition and stroke in the present study.
This study has a number of limitations. First, acute strokeswere detected through hospital discharge diagnosis codes andESRD cause-of-death forms; it was not possible to validate theseevents in the data sources used. It therefore is likely thatsome patients in this study were misclassified with regard totheir stroke status. However, the combination of ICD-9-CM codesused to identify stroke hospitalizations in our study has beenshown to have high sensitivity and specificity in identifyingtrue hospitalized stroke in the general population (18). Inaddition, one would expect such misclassification to be nondifferentialwith regard to baseline patient characteristics, which wouldresult in an underestimation of the true relative risk of strokeassociated with specific risk factors. Our study excluded patientsfor whom fee-for-service Medicare was not the primary insurer,and therefore the results cannot be generalized to this generallyhealthier and younger subgroup of dialysis patients. However,the overwhelming majority (81%) of patients in the DMMS studieshad fee-for-service Medicare as the primary insurer.
Despite these limitations, this is the first study to examinerisk factors for incident stroke among the US dialysis population.Because the study cohort included a national sample of dialysispatients, the results of this study are not limited to a singlecenter or geographic region. These results confirm the extraordinarilyhigh rates of stroke in this population and identify severalmodifiable risk factors, including malnutrition, anemia, andhypertension, as potential targets for preventive therapies.
Acknowledgments
This study was supported by a Veterans Affairs Career DevelopmentAward and PHS grants (DK07721-6 and DK63079-01) from the NationalInstitutes of Health, Bethesda, MD. The data reported here havebeen supplied by the USRDS. The interpretation and reportingof these data are the responsibility of the authors and in noway should be seen as an official policy of or interpretationby the US government.
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Received for publication January 27, 2003.
Accepted for publication July 15, 2003.
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