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Ann Thorac Surg 2001;72:2033-2037
© 2001 The Society of Thoracic Surgeons

Original article: cardiovascular

Risk factors for intermediate-term survival after coronary artery bypass grafting

Sheila C. Gardner, MSa, Gary K. Grunwald, PhDa,b, John S. Rumsfeld, MD, PhDa,c, Todd Mackenzie, PhDb, Dexiang Gao, PhDa, Jonathan B. Perlin, MD, PhDd, Gerald McDonald, MDd, A. Laurie W. Shroyer, PhD*a,c

a Division of Cardiac Research, Denver Department of Veterans Affairs Medical Center, Denver, Colorado, USA
b Department of Preventive Medicine and Biometrics, University of Colorado Health Sciences Center, Denver, Colorado, USA
c Department of Medicine, University of Colorado Health Sciences Center, Denver, Colorado, USA
d Office of Quality and Performance, Veterans Health Administration, Washington, DC, USA

Accepted for publication August 6, 2001.

* Address reprint requests to Dr Shroyer, Cardiac Research, Denver Department of Veterans Affairs Medical Center, 820 Clermont St (112R), Denver, CO 80220, USA
e-mail: laurie.shroyer{at}med.va.gov


   Abstract
Top
 Abstract
Introduction
 Material and methods
 Results
 Comment
 Acknowledgments
 References
 
Background. Risk factors for short-term mortality after coronary artery bypass grafting are well established, but little is known about risk factors for intermediate-term mortality.

Methods. We analyzed the outcomes of 11,815 patients undergoing coronary artery bypass grafting in one of the 43 cardiac surgery programs of the Department of Veteran Affairs. Risk factors for intermediate- and short-term mortality were determined using Cox proportional hazards regression models. Effects of risk factors during these two periods were explicitly compared.

Results. We found important differences in mortality risk-factor sets between the intermediate- and short-term periods after coronary artery bypass grafting. The majority of predictors of intermediate-term mortality were noncardiac-related variables, whereas the majority of predictors of short-term mortality were cardiac-related variables. Impaired functional status, chronic obstructive pulmonary disease, and renal dysfunction had greater effects in the intermediate-term period. Previous heart operation, angina class III or IV, previous myocardial infarction, and preoperative use of an intraaortic balloon pump had greater effects in the short-term period.

Conclusions. The risk factors for intermediate-term mortality identified in this study can augment preoperative risk assessment and counseling of patients. Clinicians should be aware of the importance of noncardiac-related variables as predictors of mortality in the intermediate-term period after coronary artery bypass grafting.


   Introduction
Top
 Abstract
 Introduction
Material and methods
 Results
 Comment
 Acknowledgments
 References
 
Coronary artery bypass grafting (CABG) remains one of the most frequently performed surgical procedures in the United States; more than 550,000 such operations were performed in 1998 [1]. The factors predictive of short-term (<= 30 days) mortality after CABG are well described and include age, history of previous heart operation, prior myocardial infarction, priority of operation, and extent of noncardiac comorbidity [2–7]. Clinicians can use these risk factors to identify patients at increased risk for short-term mortality after CABG and to counsel them on their risk before the operation.

To date, however, there is limited information regarding risk factors predictive of intermediate-term (31 to 210 days) mortality after CABG. Faced with the responsibility of providing the patient with full disclosure of the risk of the operation, the clinician lacks knowledge of the additional risk factors that could be predictive of longer term survival after the initial 30-day postoperative period. Knowing the risk factors for intermediate-term mortality could help clinicians identify those patients at increased risk for death during the posthospital recovery phase. Such knowledge could also augment preoperative counseling because the patient would receive information about risks of mortality beyond the first month. This information would be particularly valuable if the risk factors for intermediate-term mortality were significantly different from the factors predictive of short-term mortality. The aim of the current study was to determine the factors predictive of survival during the intermediate period after CABG and to compare these factors with those associated with short-term survival in a large cohort of Department of Veterans Affairs patients.


   Material and methods
Top
 Abstract
 Introduction
 Material and methods
Results
 Comment
 Acknowledgments
 References
 
Study population
The Department of Veterans Affairs (VA) Continuous Improvement in Cardiac Surgery Program maintains an ongoing database of individual patient risk variables (collected prospectively) and outcomes on all patients having a cardiac surgical procedure [2, 3]. The present study comprises the cohort of all patients who had CABG from October 1, 1997, through September 30, 1999, at one of the 43 cardiac surgery programs of the VA. Eight patients were excluded because of missing outcome data; therefore, the total study population was 11,815 patients.

Outcomes
The goal of this study was to estimate and compare mortality risk factors between the intermediate- and short-term periods after CABG. Therefore, the primary outcome was intermediate-term mortality, defined as all-cause mortality between 31 days and 210 days after operation (ie, the 6 months after the initial 30-day postoperative period). The secondary outcome was short-term mortality, defined as all-cause mortality within 30 days after operation. Mortality assessments were done using both individual follow-up by VA personnel and the VA Beneficiary Identification and Record Locator System, shown to be comparable with the National Death Index for mortality assessment in a VA population [8]. Outcome assessment was complete for all 11,815 patients for at least 210 days after CABG.

Risk variables
Candidate predictive variables included a wide range of demographic, cardiac-related, and noncardiac (comorbid) risk variables captured for the Continuous Improvement in Cardiac Surgery Program (Table 1). Missing values were imputed using the median for continuous variables or the most frequent category for categorical variables. Only 11 variables had missing values, with no more than five missing values for any variable except the number of stenotic arteries, which had 529 missing values (4.5%).


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  		Table 1. Characteristics of Study Populationa

 
Statistical analysis
All statistical analyses were conducted using SAS version 8 (SAS Institute, Cary, NC)[9]. Survival was modeled using Cox proportional hazards regression methods [10]. For the short-term survival analyses, patients who survived longer than 30 days were censored at 30 days. For the intermediate-term survival analyses, patients who died at or before 30 days were omitted from the analysis, and patients who survived longer than 210 days were censored at 210 days. This is equivalent to creating two time-dependent covariates for each potential risk factor. The first, or intermediate term, time-dependent covariate equals zero for the first 30 days and equals the risk factor thereafter. The second, or short-term, time-dependent covariate equals the risk factor for the first 30 days and is zero thereafter [11]. Backward variable selection with a significance level of 0.05 was used to develop multivariate models containing risk factors predictive of mortality during each time period.

To explicitly compare the differences in effects of the risk variables between the short- and intermediate-term periods, we computed a Wald significance test using the estimated difference in the effects along with the variance of this difference computed as the sum of the variances during the two periods. This method provides an explicit significance test of whether the effect of a given risk variable is different during the two periods.


   Results
Top
 Abstract
 Introduction
 Material and methods
 Results
Comment
 Acknowledgments
 References
 
Study population
Descriptive statistics for the study population are shown in Table 1. The patients had a mean age of 64 years, 99% were male, and had a relatively high prevalence of noncardiac comorbidity. For example, 26% of patients had a history of chronic obstructive pulmonary disease, 26% had a history of peripheral vascular disease, 22% had a history of cerebral vascular disease, and 34% had diabetes. About 7% of patients had had a previous heart operation and 57%, a previous myocardial infarction.

Outcomes
There were 393 deaths in the short-term period (mortality rate, 3.3%) and 347 deaths in the intermediate-term period (mortality rate for this period, 2.9%). The number of deaths was distributed across the 6-month intermediate-term period as follows: 98, 62, 54, 41, 52, and 40, respectively.

Multivariate models
The multivariate risk model for intermediate-term mortality is shown in Table 2. Significant noncardiac-related variables that were predictors of intermediate-term mortality included older age, partially or totally dependent functional status, chronic obstructive pulmonary disease, cerebral vascular disease, and serum creatinine level of 1.5 mg/dL or higher. Significant cardiac-related variables that were predictors of intermediate-term mortality included preoperative digoxin use, preoperative diuretic use, left main coronary artery stenosis of 50% or more, and left ventricular ejection fraction lower than 0.35.


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  		Table 2. Multivariate Risk Model for Intermediate-Term Mortality After Coronary Artery Bypass Graftinga

 
The multivariate risk model for short-term mortality is shown in Table 3. Significant noncardiac-related variables predictive of short-term mortality included older age, peripheral vascular disease, cerebral vascular disease, and serum creatinine level of 1.5 mg/dL or greater. Significant cardiac-related variables predictive of short-term mortality included preoperative diuretic use, previous heart operation, Canadian Cardiovascular Society angina class III or IV, previous myocardial infarction, preoperative intraaortic balloon pump use, preoperative ST segment depression on the electrocardiogram, and New York Heart Association functional class III or IV.


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  		Table 3. Multivariate Risk Model for Short-Term Mortality After Coronary Artery Bypass Graftinga

 
Results of tests explicitly comparing the magnitude of the effect of the various risk factors between the two periods are shown in Table 4. Several risk variables were found to have greater effect during the intermediate-term period compared with the short-term period. These included partially or totally dependent functional status, chronic obstructive pulmonary disease, and mild to moderately elevated serum creatinine levels (1.5 to 3.0 mg/dL). Several risk variables were shown to have greater effect during the short-term period compared with the intermediate-term period. These variables were previous heart operation, Canadian Cardiovascular Society angina class III or IV, previous myocardial infarction, and preoperative requirement of an intraaortic balloon pump.


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  		Table 4. Comparison of Effect of Mortality Risk Variables Between Intermediate-Term and Short-Term Periods After Coronary Artery Bypass Graftinga

 

   Comment
Top
 Abstract
 Introduction
 Material and methods
 Results
 Comment
Acknowledgments
 References
 
The purpose of this study was to determine the risk factors for intermediate-term mortality after CABG (31 to 210 days) and to compare these factors with those predictive of short-term mortality (<= 30 days). We found important differences in risk factor sets between the two periods (see Tables 2, 3). The majority of predictors of intermediate-term mortality were noncardiac-related variables, whereas the majority of predictors of short-term mortality were cardiac-related variables. Impaired functional status, chronic obstructive pulmonary disease, and mild to moderate renal dysfunction were explicitly shown to have greater effects in the intermediate-term period. In contrast, previous heart operation, higher angina class, previous myocardial infarction, and preoperative requirement of an intraaortic balloon pump were explicitly shown to have greater effects in the short-term period.

The results of this study can help clinicians during the preoperative evaluation and counseling of patients because they expand the range of outcomes on which to base mortality risk assessment to include the period beyond the first 30 days after operation. Our results indicate that there are specific risk factors for intermediate-term survival after CABG and suggest that the focus of care should shift toward noncardiac factors such as impaired functional status, chronic obstructive pulmonary disease, and renal dysfunction in this period.

Beyond clinical decision-making for the individual patient, this study may have relevance for health system policy and operations. Most cardiac surgery quality improvement programs focus primarily on short-term mortality risk factors and outcomes. The results of this study can help expand the focus to intermediate-term mortality risk factors and outcomes. For example, the VA plans to implement specific quality-improvement initiatives aimed at modifying risk factors for intermediate-term outcomes after CABG (eg, attempts to modify preoperative functional status). Continued surveillance of intermediate-term risk factors and outcomes by the VA Continuous Improvement in Cardiac Surgery Program can then be used to help identify the most effective approaches to modifying these risk factors and can further validate the relationship between these variables and intermediate-term outcomes. In this way, it is hoped that evidence-based medicine will be extended to evidence-based health care management across a large health-care delivery system.

Limited information has been available regarding risk factors predictive of mortality more than 30 days after CABG. Risum and associates [5] evaluated risk factors for both operative death and longer term mortality after CABG in a study with a median follow-up of 6.45 years. Their study, however, described risk factors for 30-day mortality only and concluded that longer term mortality could not be predicted accurately. Other studies [12–14] have reported factors associated with survival 10 to 20 years after coronary artery bypass operations. These factors include older age, an abnormal electrocardiogram, abnormal exercise test results, peripheral arterial disease, and proximal left anterior descending coronary artery disease. However, the delineation of risk factors for longer term survival was not the primary purpose of these reports, and they did not focus on the intermediate 2- to 7-month postoperative period.

The present study reveals that the patient’s functional status, as determined preoperatively by care providers, appears to be an important predictor of intermediate-term survival. In previous studies, Rumsfeld and colleagues [15] found that patient self-report of physical health status was an independent predictor of 6-month mortality after CABG. These findings highlight the importance of patient function as a predictor of outcome above and beyond traditional demographic, cardiac-related, and noncardiac-related variables.

This study has several strengths. It used a large, prospectively collected database with nearly complete information on all CABG procedures over a 2-year period. We were able to consider a wide range of candidate preoperative predictive variables, including demographic, noncardiac-related, and cardiac-related factors. Furthermore, follow-up was virtually complete. Finally, we employed explicit statistical methods to compare the magnitude of the effect of the various risk factors between the short-term and intermediate-term periods, which is necessary to assess changes in effects of risk factors over time.

Several potential limitations should be addressed. The results may not be generalizable to non-VA populations, as the study population was almost exclusively male, was older, and had a large burden of comorbidity. Data were derived from an existing database not specifically designed to address the question of short-term versus intermediate-term survival after CABG operations. However, risk variables were collected prospectively, and the database included nearly all CABG procedures performed during the study period. Finally, there may be postsurgical variables predictive of intermediate-term survival, but the focus of this study was preoperative risk assessment, with consideration of only preoperative variables as candidate predictors.

We hope that the identification of risk factors for intermediate-term mortality after CABG in this study will augment preoperative mortality risk assessment and counseling of patients. Clinicians should be aware of the importance of noncardiac-related variables as predictors of mortality in the intermediate-term period after operation.


   Acknowledgments
Top
 Abstract
 Introduction
 Material and methods
 Results
 Comment
 Acknowledgments
References
 
Funding for this Quality Improvement Research study was provided in part by the Office of Patient Care Services and the Office of Quality and Performance at the Department of Veterans Affairs Headquarters. Dr Rumsfeld is supported by Career Development Award 98341-1 from the Department of Veterans Affairs Health Services Research and Development Service. Dr Mackenzie is supported by grant MO1 RR00069, General Clinical Research Centers Program, National Institutes of Health.


   References
Top
 Abstract
 Introduction
 Material and methods
 Results
 Comment
 Acknowledgments
 References
 

  1. American Heart Association. 2001 Heart and stroke statistical update. Accessed June 1, 2001. http://www.americanheart.org/statistics/medical.html.
  2. Grover F.L., Johnson R.R., Shroyer A.L.W., Marshall G., Hammermeister K.E. The Veterans Affairs Continuous Improvement in Cardiac Surgery Study. Ann Thorac Surg 1994;58:1845-1851.[Abstract]
  3. Grover F.L., Shroyer A.L.W., Hammermeister K.E. Calculating risk and outcome: the Veterans Affairs database. Ann Thorac Surg 1996;62:S6-S11.
  4. Shroyer A.L.W., Plomondon M.E., Grover F.L., Edwards F.H. The 1996 coronary artery bypass risk model: The Society of Thoracic Surgeons Adult Cardiac National Database. Ann Thorac Surg 1999;67:1205-1208.[Abstract/Free Full Text]
  5. Risum O., Abdelnoor J.L., Svennevig S., et al. Risk factors for early and late mortality in surgical treatment of coronary artery disease. Cardiovasc Surg 1995;3:537-544.[Medline]
  6. Hannan E.L., Kilburn H., O’Donnell J.F., Lukacik G., Shields E.P. Adult open heart surgery in New York State: an analysis of risk factors and hospital mortality rates. JAMA 1990;264:2768-2774.[Abstract/Free Full Text]
  7. Jones R.H., Hannan E.L., Hammermeister K.E., et al. Identification of preoperative variables needed for risk adjustment of short-term mortality after coronary artery bypass graft surgery. J Am Coll Cardiol 1996;28:1478-1487.[Abstract]
  8. Fisher S.G., Weber L., Goldberg J., Davis F. Mortality ascertainment in the veteran population: alternatives to the National Death Index. Am J Epidemiol 1995;141:242-250.[Abstract/Free Full Text]
  9. SAS/STAT user’s guide, Version 8. Cary, NC: SAS Institute Inc, 1999.
  10. Cox D.R. Regression models and life tables. J R Stat Soc [B] 1972;34:187-220.
  11. Allison P.D. Survival analysis using the SAS system. Cary, NC: SAS Institute Inc, 1995:155-157.
  12. Alderman E.L., Bourassa M.G., Cohen L.S., et al. Ten-year follow-up of survival and myocardial infarction in the randomized Coronary Artery Surgery Study. Circulation 1990;82:1629-1646.[Abstract/Free Full Text]
  13. Varnauskas E. Twelve-year follow-up of survival in the randomized European Coronary Surgery Study. N Engl J Med 1988;319:332-337.[Abstract]
  14. Rahimtoola S.H., Fessler C.L., Grunkemeier G.L., Starr A. Survival 15 to 20 years after coronary bypass surgery for angina. J Am Coll Cardiol 1993;21:151-157.[Abstract]
  15. Rumsfeld J.S., MaWhinney S., McCarthy M., Jr, et al. Health-related quality of life as a predictor of mortality following coronary artery bypass graft surgery. Participants of the Department of Veterans Affairs Cooperative Study Group on Processes, Structures, and Outcomes of Care in Cardiac Surgery. JAMA 1999;281:1298-1303.[Abstract/Free Full Text]



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