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(Circulation. 2007;116:1465-1472.)
© 2007 American Heart Association, Inc.
Coronary Heart Disease |
From the Cardiovascular Special Studies Center, US Renal Data System, and the Division of Cardiology, Department of Medicine, Hennepin County Medical Center, University of Minnesota, Minneapolis (C.A.H.); Genentech, Inc, South San Francisco, Calif (K.L., M.B.); US Renal Data System Coordinating Center, Minneapolis, Minn (C.A.); and ICON Lifecycle Sciences Group, San Francisco, Calif (P.D.F.).
Correspondence to Charles A. Herzog, MD, Cardiovascular Special Studies Center, US Renal Data System, 914 S 8th St, Ste S-206, Minneapolis, MN 55404. E-mail cherzog{at}usrds.org
Received February 14, 2007; accepted July 26, 2007.
| Abstract |
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Methods and Results— This retrospective cohort study used data from the US Renal Data System (USRDS) database (n=1 285 177) and the third National Registry of Myocardial Infarction (NRMI 3) (n=537 444). AMI hospitalizations from April 1, 1998, through June 30, 2000, were identified using International Classification of Diseases, 9th edition, clinical modification, codes 410, 410.x, 410.x0, and 410.x1. The 9418 unique dialysis patients identified with AMI hospitalizations in the USRDS database were cross-matched with the NRMI registry, creating a cohort for analysis that consisted of 3049 matching patients. Clinical characteristics of dialysis and nondialysis (n=534 395) AMI patients were compared by use of the
2 test. Of clinical significance, 44.8% of dialysis patients were diagnosed as not having acute coronary syndrome on admission, versus 21.2% of nondialysis patients; 44.4% presented with chest pain, versus 68.3% of nondialysis patients; and 19.1% had ST elevation, versus 35.9% of nondialysis patients. Cardiac arrest was twice as frequent for dialysis patients (11.0% versus 5.0%), and in-hospital death was nearly so (21.3% versus 11.7%). In a logistic regression model, the odds ratio for in-hospital death for dialysis versus nondialysis patients was 1.498 (95% CI, 1.340 to 1.674).
Conclusions— Dialysis patients hospitalized for AMI differ strikingly from nondialysis patients, which possibly explains their poor outcomes. Intensive efforts for early, accurate recognition of AMI in dialysis patients are warranted.
Key Words: electrocardiography kidney failure, chronic myocardial infarction renal dialysis
| Introduction |
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Clinical Perspective p 1472
The Cardiovascular Special Studies Center of the US Renal Data System (USRDS) has designed an ongoing 3-part study to collect data pertaining to dialysis patients hospitalized for AMI: prehospitalization data obtained from dialysis center medical record abstraction, data on the clinical characteristics of dialysis patients hospitalized for AMI, and data on long-term survival after hospital discharge. Here, we report the results of our collaborative retrospective cohort study with the National Registry of Myocardial Infarction (NRMI) on the clinical characteristics of dialysis patients hospitalized for AMI in the United States.
| Methods |
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Patients were initially identified in the USRDS database (n=1 285 177 at the time of the study). AMI hospitalizations were identified by International Classification of Diseases, 9th edition, clinical modification, codes 410, 410.x, 410.x0, and 410.x1. The study period was April 1, 1998, through June 30, 2000, corresponding to the time of enrollment for NRMI 3 (n=537 444 patients, 1553 hospitals), the third NRMI data collection study.7 Eligible patients had received renal replacement therapy for at least 90 days and dialysis for at least 60 days before AMI. A total of 9418 unique dialysis patients hospitalized for AMI were identified in the USRDS database. This patient list was then cross-matched with the NRMI 3 registry, which does not identify dialysis dependency, by the Ovation Research Group (San Francisco, Calif) using variables including age; gender; birth date; first, middle, and last initials; claim admit and through dates; and provider (hospital).8
The cohort for our analysis was made up of the 3049 matching patients found in the USRDS database and the NRMI 3 registry. The
2 test was used to analyze categorical variables pertaining to the characteristics of dialysis versus nondialysis patients in the NRMI 3 registry. A 1-way ANOVA and the nonparametric alternative Wilcoxon rank-sum test were used to evaluate continuous variables that were normally distributed or skewed, respectively. (Patient age, systolic and diastolic blood pressures, pulse, weight, number of days in the intensive care unit, and left ventricular ejection fraction were normally distributed, and mean values were compared; onset of symptoms to first admission data in hours were skewed, and median values were compared.) For nonparametric comparisons involving >2 groups, the Kruskal-Wallis test was used. All tests are 2 tailed on the basis of a level of significance set at 0.05. A 2-sided Bonferroni probability value was used to control for experimental type I error rate for multiple comparisons; the reported probability values reflect this adjustment for multiple comparisons. Characteristics included demographics, prior medical history, temporal variables, clinical variables on admission, and in-hospital variables such as therapeutic strategies. A standard NRMI 3 definition of eligibility for acute coronary reperfusion was based on the following characteristics: time from symptom onset to evaluation <12 hours; ST-segment–elevation myocardial infarction (STEMI, which by convention includes both ST elevation and left bundle-branch block) on first ECG; no Killip class IV; and no spontaneous reperfusion, major organ failure, or early death. This definition is problematic for the end-stage renal disease (ESRD) cohort because all patients would be considered to have major organ failure. A more meaningful definition for the ESRD cohort includes tabulation in the registry of the reasons reperfusion was not used, described below.
To further analyze the association of in-hospital death and dialysis, a logistic regression analysis was performed. The logistic regression model included variables pertaining to dialysis (yes or no), demographic characteristics (including age, gender, and race), insurance status, hospital characteristics, medical history (such as congestive heart failure or diabetes), clinical presentation (including ECG findings of STEMI, Killip class, pulse, and blood pressure), medications administered within 24 hours of admission, and any initial coronary reperfusion therapy.
The authors had full access to and take responsibility for the integrity of the data. All authors have read and agree to the manuscript as written.
| Results |
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Demographically, the 2 patient groups were of similar age, with 47.5% of dialysis and 48.5% of nondialysis patients
70 years of age (Table 1). Proportionately more dialysis patients were female (46.9% versus 39.2% for nondialysis). Reflecting the disproportionate representation of black patients with ESRD, only 63.6% of dialysis patients were white, compared with 85.3% of nondialysis patients.
The 2 patient groups differed significantly by prior medical history (Table 1). Dialysis patients had a lower prevalence of current smoking (10.7% versus 26.0%), hypercholesterolemia (18.6% versus 31.2%), and family history of cardiovascular disease (12.9% versus 26.8%). About twice as many dialysis patients were identified as diabetic (57.4% versus 28.8%). Dialysis patients had a greater prevalence of known cardiovascular disease: hypertension (77.8% versus 56.2%), congestive heart failure (30.9% versus 15.7%), prior coronary artery bypass surgery (19.6% versus 12.7%), and stroke (15.3% versus 9.6%). The prevalence of prior AMI (25.9% versus 24.0%) and the prevalence of angina (14.7% versus 12.8%) were minimally higher in dialysis patients than in nondialysis patients.
A trend toward less prehospital delay for nondialysis patients appeared (29.4% presented at <2 hours versus 20.7% of the dialysis group), but the interpretation is muddied by missing data (Table 2). The mean±SD time from symptom onset to evaluation was similar for both groups, 5.8±9.2 hours for dialysis and 5.5±9.0 hours for nondialysis patients, but the median time was less for the nondialysis group (2.3 versus 2.7 hours).
We found a markedly lower diagnostic suspicion of AMI and, notably, of acute coronary syndromes in dialysis patients (Table 3). In the nondialysis group, 43.8% had an admitting diagnosis of AMI, versus 21.8% of dialysis patients. Of clinical significance, 44.8% of dialysis patients were diagnosed as not having acute coronary syndrome on admission, compared with 21.2% of nondialysis patients. Concordant with the lower diagnostic suspicion for acute coronary syndrome, fewer than half of the dialysis patients (44.4%) presented with chest pain, compared with 68.3% of nondialysis patients. Fewer dialysis patients were classified as Killip class I (58.4% versus 75.2%).
Another clinically important difference between dialysis and nondialysis patients is ECG data (Table 3) because ECGs are major determinants of selection for acute coronary reperfusion therapy. Among nondialysis patients, 35.9% had ST elevation, compared with only 19.1% of dialysis patients. The prevalence of ST depression was comparable for dialysis and nondialysis patients (27.7% and 28.9%, respectively). Left bundle-branch block was slightly higher among dialysis patients (8.1% versus 5.8%), and nonspecific ECG findings were more common (44.1% versus 35.8%). If we assumed that all of the left bundle-branch block findings were new, only 27.2% of dialysis patients would be deemed ECG eligible for acute coronary reperfusion, compared with 41.7% of nondialysis patients. (Using the NRMI 3 registry STEMI definition, either ST elevation or new/unknown/old left bundle-branch block, which is a separate data entry field, 26.0% of dialysis patients and 40.0% of nondialysis patients would be ECG eligible for acute coronary reperfusion.) Because not all of these findings are new, the actual percentage of STEMI is likely to be lower in both groups. The larger proportion of non–Q-wave MI in dialysis patients (77.8% versus 62.6%) reflects this difference.
On the basis of NRMI definitions, only a small proportion of the dialysis patients presenting with AMI were considered eligible for acute coronary reperfusion (Table 4). Only 10.2% of dialysis patients were deemed reperfusion eligible, compared with 24.6% of nondialysis patients. However, the NRMI definition of reperfusion eligibility is problematic for dialysis patients because it excludes on the basis of major organ failure. A less restrictive definition that includes all dialysis patients with STEMI on first ECG and time from symptom onset to evaluation of <12 hours raises the number of reperfusion-eligible dialysis patients from 310 (10.2%) to 408 (13.4%).
In descending order of frequency, STEMI dialysis patients did not receive reperfusion for the following reasons: contraindications to thrombolysis (22.4%), major organ failure (21.3%), quality of life (15.3%), history of cerebral vascular accident (8.2%), Killip class IV (2.0%), early death (0.7%), and spontaneous reperfusion (0.2%). STEMI nondialysis patients did not receive reperfusion for the following reasons: contraindications to thrombolysis (16.6%), quality of life (10.6%), history of cerebral vascular accident (6.5%), major organ failure (2.3%), Killip class IV (2.1%), early death (0.6%), and spontaneous reperfusion (0.7%).
Of the reperfusion-eligible patients, 47% of dialysis patients (n=146) and 75% of nondialysis patients (n=98 528) received some type of coronary reperfusion (P<0.0001 for use of coronary reperfusion in reperfusion-eligible dialysis versus nondialysis patients). Overall, only 8.3% of dialysis patients presenting with AMI, regardless of STEMI or reperfusion eligibility status, actually received any acute coronary reperfusion therapy, compared with 28.7% of nondialysis patients (data not shown). Coronary angiography and coronary revascularization (both done in nonacute reperfusion settings) were more common among nondialysis than dialysis patients: coronary angiography, 34.6% versus 28.4%; percutaneous coronary intervention, 18.6% versus 8.2%; and coronary artery bypass surgery, 9.1% versus 4.2%. Evidence-based medical therapies were used less commonly among dialysis patients on admission (aspirin, 69.8% versus 83.3%; and ß-blockers, 45.8% versus 54.7% among nondialysis patients) and at discharge (aspirin, 66.8%; ß-blockers, 56.6%; and angiotensin-converting enzyme [ACE] inhibitors, 34.5% for dialysis patients; for nondialysis patients, 80.3%, 63.6%, and 40.7%, respectively).
More dialysis patients had impaired left ventricle systolic performance (27.4% with left ventricular ejection fraction <40%, compared with 18.0% of nondialysis patients; Table 5). Consistent with this finding were greater numbers of dialysis patients with congestive heart failure (25.1% versus 19.1%). From a clinical standpoint, the most striking differences relate to unexpected cardiac arrest and in-hospital death. Cardiac arrest was twice as frequent in dialysis patients as in nondialysis patients (11.0% versus 5.0%). After exclusion of patients transferred to other institutions, the in-hospital death rate of dialysis patients was 21.3%, compared with 11.7% for nondialysis patients.
Dialysis and nondialysis patients in this study showed different demographic and clinical characteristics. In the logistic regression analysis, despite these differences, we found an independent association of dialysis status and in-hospital death. Compared with nondialysis patients, the odds ratio of in-hospital death for dialysis patients was 1.498 (95% CI, 1.340 to 1.674). Although there were significantly more nonwhite patients in the dialysis group, black (versus white) race was not independently associated with in-hospital death; the odds ratio for death was 0.980 (95% CI, 0.934 to 1.027).
| Discussion |
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Our work identified several important clinical issues. There is a lower index of clinical suspicion and a higher level of inaccuracy for initial diagnosis of acute coronary syndromes in dialysis patients with AMI because twice as many patients (44.8%, versus 21.2% of nondialysis patients) were incorrectly diagnosed on admission. This diagnostic inaccuracy is understandable if clinicians relied on a history of chest pain, present in only 44.4% of dialysis patients versus 68.3% of nondialysis patients, and presence of diagnostic ECG changes because relatively fewer dialysis patients had ST elevation. Further diagnostic confusion may have resulted from the greater prevalence of hypertension and likely attendant hypertensive heart disease and uninterpretable ST depression in the dialysis cohort. Our finding of a lower prevalence of chest pain in dialysis patients with AMI is concordant with the study by Sosnov et al,9 which reported that patients with chronic kidney disease (estimated glomerular filtration rate <60 mL · min–1 · 1.73 m–2) in the Worcester Heart Attack Study were 43% less likely to report chest pain than patients without chronic kidney disease, independently of the presence of diabetes.
The cornerstone of AMI treatment is acute coronary reperfusion, but only a minority of the general population, those with STEMI presenting sufficiently early from symptom onset and no contraindications to treatment, are reperfusion eligible. The ECG (ST elevation or new left bundle-branch block) defines the initial patient population eligible for acute coronary reperfusion. In this study, we found a remarkable difference between ECG findings for dialysis patients with AMI and those for nondialysis AMI patients. Only 19.1% of dialysis patients had ST elevation, versus 35.9% of nondialysis patients. Assuming that all left bundle-branch blocks are new, an assumption that might be unpalatable in the clinical setting, by ECG criteria, 27.2% of dialysis patients and 41.7% of nondialysis patients might be considered for acute coronary reperfusion before exclusions (or 26.0% and 40.0%, respectively, using the definition of either ST elevation or new/unknown/old left bundle-branch block). By NRMI criteria, only 10.2% of dialysis patients and 24.6% of nondialysis patients were reperfusion eligible. Ultimately, only 8.3% of our dialysis cohort and 28.7% of our nondialysis cohort received acute coronary reperfusion.
From the perspective of our original speculations on underdiagnosis and therapeutic nihilism in dialysis patients with AMI, a third distinct category appears necessary: potential differences in pathophysiology. Our data support the concept of underdiagnosis of acute coronary syndromes, including AMI, and less aggressive treatment in dialysis patients with AMI; 47% of reperfusion-eligible dialysis patients and 75% of nondialysis patients received acute coronary reperfusion. However, the ECG data imply that there also may be an important mechanistic difference. A higher proportion of non-STEMI might suggest a greater prevalence of preexisting obstructive coronary artery disease and perhaps attendant increased coronary collateralization and myocardial ischemic preconditioning in dialysis patients, reducing the likelihood of transmural ischemia in the setting of acute coronary occlusion. Another less likely possibility (for which there are no supporting data) is that diagnostic ST elevation is somehow masked in dialysis patients suffering transmural ischemia; ie, the ECG is less accurate for identifying anatomically appropriate coronary reperfusion candidates. Our ECG findings differ from those reported by Berger at al10 using data from the Cooperative Cardiovascular Project (CCP). They found that 31.3% of dialysis patients and 37.4% of nondialysis patients with AMI in the CCP database had ECG findings of ST elevation. The reasons for these discordant findings are unclear. It is plausible, however, that treatment patterns could vary by registry. Berger et al10 reported a greater relative underuse of aspirin, ß-blockers, and ACE inhibitors in dialysis patients than in nondialysis patients. Consistent themes reported in prior publications include the increased risk of death associated with chronic kidney disease and AMI, the inverse relationship of renal dysfunction and likelihood of receiving evidence-based therapies (aspirin, ß-blockers, and ACE inhibitors) for improving survival, and the association with improved survival of these treatments in chronic kidney disease patients who sustain AMI.10–14
The concept of "accelerated atherosclerosis" in dialysis patients was advanced in a classic article by Lindner et al15 3 decades ago that was based on 39 patients. Surprisingly, few systematic attempts have been made in the modern treatment era to obtain coronary angiographic data for dialysis patients to better define the incidence, prevalence, and rate of progression of coronary artery disease in ESRD patients.
On the basis of our reported ECG and other clinical data, we believe that performing a prospective study of coronary angiographic and other clinical findings in dialysis patients with acute coronary syndrome would also be valuable.
Not unexpectedly, we found a markedly increased rate of in-hospital death for dialysis patients (21.3%, compared with 11.7% for nondialysis patients). We previously reported a 26% in-hospital death rate for dialysis patients hospitalized for AMI from 1977 through 1995.2 We also found a significant cardiac arrest hazard complicating AMI in dialysis patients; 11% of dialysis patients versus 5% of nondialysis patients sustained an unexpected cardiac arrest. Sudden cardiac death is the single largest cause of death among chronic dialysis patients16; that they would also be at increased vulnerability to cardiac arrest in the setting of acute myocardial ischemia is not surprising.
We have attempted to provide a clinical picture of the special characteristics of dialysis patients with AMI to better understand the potential mechanisms for their poor outcome. Our study is limited by its uncontrolled, observational nature and potential biases inherent in any selective registry. Nevertheless, we believe that our initial impressions are likely to be clinically valid on the basis of the data sources. Ultimately, we hope that these observations will help to increase awareness and understanding of the special characteristics of patients with chronic kidney disease, including ESRD, and to improve their care.
| Acknowledgments |
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Sources of Funding
This project was performed under a collaborative agreement between the National Institute of Diabetes and Digestive and Kidney Diseases (National Institutes of Health, Bethesda, Md) and the NRMI/Genentech (South San Francisco, Calif). The Cardiovascular Special Studies Center of the USRDS is supported by contract No. N01-DK-9-2344 (National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Md). Some data reported here have been supplied by the USRDS. The interpretation and reporting of these data are the responsibility of the authors and in no way should be seen as an official policy or interpretation of the US government.
Disclosures
Kathee Littrell and Martha Blaney are employed by Genentech, Inc, which sponsors NRMI. Paul D. Frederick is employed by ICON Lifecycle Sciences Group (formerly Ovation Research Group), which receives research funding from Genentech, Inc. Charles A. Herzog and Cheryl Arko report no conflicts.
| References |
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Circulation 2007 116: 1433.
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