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(Chest. 1999;116:1570-1574.)
© 1999 American College of Chest Physicians

Factors Associated With Health Indicators in Patients Undergoing Coronary Artery Bypass Surgery*

Yasmin Maor, , MD; Yael Cohen, MD; Liraz Olmer, MsC; Benjamin Mozes, MD and for the Israeli Coronary Artery Bypass (ISCAB) Study Consortium{dagger}

* From the Center for the Study of Clinical Reasoning, The Gertner Institute for Epidemiology and Health Policy Research, Sackler School of Medicine, Tel Aviv University, Sheba Medical Center, Tel Hashomer, Israel. {dagger} A complete list of participants is listed in the Appendix.

Correspondence to: Yasmin Maor, MD, The Center for the Study of Clinical Reasoning, The Gertner Institute for Epidemiology and Health Policy Research, Sheba Medical Center, Tel Hashomer 52621, Israel; e-mail: maory{at}post.tau.ac.il


   Abstract
TOP
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 Appendix
 References
 
Background: The main goals of coronary artery bypass graft (CABG) surgery for most patients are to relieve angina, to improve functional capacity, to return to work, and to improve health. A limited amount of information is available regarding the various attributes that are associated with achieving these goals.

Study Objectives: To investigate different patient attributes affecting these outcomes.

Design: Prospective data collection.

Setting: Fourteen medical centers that perform CABG surgery in Israel.

Patients: The 4,012 patients who underwent CABG surgery during 1994.

Measurements: Trained nurses collected data using structured questionnaires prior to and 4 to 5 months after the operation. Using logistic regression, four risk models were created to the following health indicators: recurrence of angina, functional capacity, return to work, and perception of health. Candidate variables were sociodemographic details, major comorbidities, risk factors for cardiac disease, and severity of cardiac disease.

Results: The mean age of the patients was 63.8 years old, 79.3% were men, 59.9% were elective operations, and left main disease was found in 17.3%. Multivariate logistic regression revealed that the variables that significantly contributed to three or more of the models were Sephardic Jewish origin, female gender, left ventricular dysfunction, and diabetes mellitus.

Conclusions: There is a similarity between risk factors of various health indicators in CABG surgery patients. Thus, it is possible to define a population at high risk that may not benefit from the procedure.

Key Words: coronary artery bypass graft surgery • health indicators • outcome • risk


   Introduction
TOP
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 Appendix
 References
 
Coronary artery bypass graft (CABG) surgery has become a common revascularization procedure.1 2 Over the last decade, many studies assessing the outcomes of patients undergoing CABG surgery have been published.3 4 5 6 7 The outcome used in these studies was mortality. Thus, the conclusions drawn concerning the risk for patients undergoing CABG surgery are related primarily to the probability of dying.

The main goal of CABG surgery in most patients is to relieve angina. As a consequence of angina relief, patients expect to improve their functional capacity, to return to work, to have improved health, and to resume a normal life. These outcomes are not always achieved, either because of the failure of the revascularization procedure or because of complications. Research in this field has demonstrated that surviving the operation does not guarantee a successful outcome. Twenty to 30% of patients experience a recurrence of angina within 1 year after surgery.8 9 10 Seven percent of patients experience neuropsychological deficits 6 months after surgery.11 Only 73 to 79% of patients who undergo CABG surgery return to work within 6 months.8 12 13 One fifth of patients who undergo CABG surgery report that their global quality of life after the procedure was no better or worse than before and this was not related to their physical state.14

Since most outcome studies have dealt with survival, limited data is available10 13 15 regarding risk factors for other health states; therefore, prediction is limited regarding which of the surviving patients will benefit from the intervention.

Therefore, the main aim of this study was to investigate the factors associated with the following health indicators: recurrence of angina, functional capacity, return to work, and general health perception, 4 to 5 months after the operation. We chose this follow-up period because most patients have adjusted to their new health state by this time.


   Materials and Methods
TOP
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 Appendix
 References
 
This study is an analysis of a national study of postoperative mortality associated with CABG surgery in Israel performed during 1994. A full description of data collection and the description of variables has been published elsewhere.16 A brief description is presented here. The study was approved by the institutional review board of each participating hospital, and written informed consent was obtained from all patients included in the study.

Data Collection
In each center, a trained nurse collected the data using a structured questionnaire. Data collection included preoperative direct patient interviews and a follow-up of vital status using official national mortality records. The discharge sheets, operation and catheterization reports, and ECGs before and after the operation were obtained for each patient and sent to the research center where they were coded.

Trained nurses performed the follow-up interview by telephone 4 to 5 months after the operation. To adjust for the possible bias of different follow-up periods, the follow-up period was one of the candidate variables in the logistic models.

Creating the Models
Definition of the Populations:
During 1994, 5,100 isolated CABG operations were performed in Israel. The study included most of the patients who underwent CABG surgery in Israel during this period (n = 4,835). Dropouts were due to vacations taken by the data collectors. In these analyses, we excluded patients who were lost to follow-up (n = 3), patients who died during the follow-up period (n = 251), and patients who could not respond by themselves to the questionnaire (n = 569; we did not accept proxy responses). In the model describing recurrence of angina, we excluded patients who did not suffer from angina prior to the operation (n = 574). In the model describing return to work, we excluded patients who did not work (either full-time or part-time) prior to the operation (n = 2,618).

Definitions of the Dependent Outcome Variables
Recurrence of Angina:
This was defined as chest pain in the last month similar to that experienced prior to the operation and relieved either by rest or by sublingual nitrates, compared to patients suffering from atypical chest pain and patients without chest pain.

Functional Capacity:
The patients were asked to rate their functional capacity on a scale from one to five. The dependent variables were categories four and five grouped together (bedridden or capable of basic functioning only), compared to categories one to three: capable to perform any effort, capable to perform usual daily efforts, and capable to perform mild efforts only.

Return to Work:
This was defined as a return to full-time or part-time work, compared to patients who did not return to work at all.

Health Perception:
The patients were asked to rate their current health state on a scale from one to five. The dependent variable was bad health state (category five), compared to categories one to four: excellent health, very good health, good health, and moderate health.

Definition of the Independent Variables
Candidate variables were the following: sociodemographic details; major comorbidities; risk factors of cardiac disease, such as smoking history and physical activity prior to surgery; and cardiac clinical disease, such as a history of myocardial infarction, the presence of angina, and ejection fraction. For a detailed description of all included variables, refer to Mozes et al.16

Data Analysis
Analyses were performed separately for each outcome to determine which of the patient attributes were significantly associated with the dependent variable.

The following steps were performed: (1) bivariate analysis of the association of each independent variable with the various outcomes; (2) variables were selected as candidates for the multivariate analysis based on the level of significance of the bivariate association with the various outcomes (p < 0.15); (3) variables with > 10% missing data were omitted; and (4) logistic regression analyses were performed for each outcome variable.

The area under the receiver operating characteristic (ROC) curve was used as an overall measure of the ability of the models to predict individual patient outcome.17 18


   Results
TOP
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 Appendix
 References
 
Population Characteristics
A total of 5,100 isolated CABG operations were performed in Israel in 1994. Of these, 4,012 patients were eligible according to the inclusion and exclusion criteria specified above. The mean age of the patients was 63.8 ± 9.7 years old (range, 32 to 92), 79.3% were men, 26.4% had > 12 years of schooling, 9.9% lived alone, and 59.9% were elective operations. Left main disease was found in 17.3% of patients, 4.1% had overt clinical congestive heart failure, 63.4% used diuretics, and 18.3% had ejection fraction < 40%. Diabetes mellitus was identified in 28.6% (see Table 1 ).


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  		Table 1. Characteristics of the Study Population

 
The Risk Models
Multivariate logistic regression revealed that variables predicting recurrence of angina were Sephardic Jewish origin, past angioplasty, congestive heart failure (defined by the use of diuretics and shortness of breath), and time from surgery. The area under the ROC curve was 0.56 (Table 2 ). Variables predictive of limited physical functioning included advanced age (> 75 years old), female gender, Sephardic Jewish origin, diabetes mellitus, peripheral vascular disease, angina, congestive heart failure, and low ejection fraction (< 40%). The area under the ROC curve of this model was 0.71 (Table 3 ). Variables predicting that a patient would not return to work included, once again, female gender, Sephardic Jewish origin, diabetes mellitus, priority of the operation (urgent or emergent), and low ejection fraction. The area under the ROC curve was 0.63 (Table 4 ). Variables predicting the perception of bad health after the operation included female gender, Sephardic Jewish origin, diabetes mellitus, priority of the operation (urgent or emergent), low ejection fraction, and peripheral vascular disease. The area under the ROC curve of this model was 0.64 (Table 5 ).


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  		Table 2. Risk Model for Recurrence of Angina after CABG Surgery*

 

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  		Table 3. Risk Model for Diminished Functional Capacity After CABG Surgery*

 

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  		Table 4. Risk Model for Not Returning to Work After CABG Surgery*

 

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  		Table 5. Risk Model for the Perception of a Bad Health State After CABG Surgery*

 
The timing of the follow-up interview after the operation was significant only in the model predicting recurrence of angina.


   Discussion
TOP
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
Appendix
 References
 
The main results of this study are that the important attributes associated with health indicators after CABG surgery include Sephardic Jewish origin, female gender, left ventricular dysfunction, and diabetes mellitus.

Data regarding risk factors for health states are limited. Guadagnoli et al19 reported that predictors of functioning 6 months after CABG surgery, as measured by the instrumental activity of daily living questionnaire in 268 patients, were comorbidity, level of functioning prior to the operation, and marital state. Age and mental health prior to the operation were important predictors of postsurgical mental health. Jenkins et al15 reported that in 463 patients, the presence of angina, dyspnea, fatigue, sleeping problems, depression, hopefulness, and social support prior to the operation predicted freedom from symptoms 6 months after the operation. The model was able to predict 69.6% of the variance. Several studies addressed the issue of recurrence of angina. Cameron et al10 sought predictors of recurrence of angina during the first year after CABG surgery in 5,289 patients of the CASS registry. Significant predictors included minimal coronary disease, preoperative angina, use of vein grafts only, prior infarction, incomplete revascularization, female gender, current smoking, and young age. Predictors for recurrent chest pain found by Brandrup-Wognsen et al20 included severity of angina prior to the operation, younger age, previous CABG surgery, duration of symptoms, time on pump, and absence of left main disease. Predictors of a return to work 6 months after CABG surgery in 228 patients included the patient’s preoperative expectations to return to work, profile of mood states score, angina, education, cognition, income, and reliance on religion prior to the operation.13

The ability to compare these studies to our data is limited. This is due to the variation in the patients included in the studies, the selection of variables (which varies between studies), and the use of different statistical methods. Furthermore, most of these studies included a small volume of patients, thus limiting the generality of the results.

The only patient attribute that entered all of the models was Sephardic Jewish origin. A lower level of education in this group of patients, the cultural differences that affect coping, and a lower economic status may explain this. Further research is needed in this field.

Several criteria guided us in the selection of variables. As we intended to predict patient outcomes, all variables selected were gathered prior to the intervention, and we did not include process variables or data regarding complications.

All data gathered in our study are part of the common clinical audit. Thus, the inferences drawn may be of practical use and do not require a special effort.

The time period of 4 to 5 months after surgery was chosen because it is the opinion of clinicians that, by this time, most patients have recuperated from the operation; their medical condition has stabilized; and, presumably, they have adjusted to the change in their health state, reaching a new steady state.

The risk factors identified here are similar to those found for the 30-day mortality model we previously published16 and to other models predicting mortality risk.3 4 5 6 7 Advanced age, female gender, diabetes mellitus, left ventricular dysfunction, and priority of the operation were predictive of a worse health state as well as of mortality.16 Thus, when a patient has a higher risk of death, he also has lower chances of gaining other desired outcomes having a considerable impact on quality of life. All aspects being considered, such patients have lower chances of benefiting from the operation.

To conclude, risk factors for health states can be identified for patients undergoing CABG surgery. The important risk factors seem to be similar and apply also to the risk of death. Thus, patients who are not likely to benefit from the operation can be identified and advised accordingly.


   Appendix
TOP
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Appendix
References
 
The members of the Israeli Coronary Artery Bypass (ISCAB) Study Consortium are Azay Appelbaum, Elieser Kaplinsky, Gideon Sahar, Nima Amit, Jacob Lavee, Arie Schachner, Yitzhak Berlovitz, Gideon Merin, Aram K. Smolensky, Dani Biteran, Simcha Milo, Bernardo Vidne, Amram J. Cohen, Gideon Uretzky, and Vladimir Yakirevitch.


   Footnotes
 
Abbreviations: CABG = coronary artery bypass graft; ROC = receiver operating characteristic

Received for publication March 1, 1999. Accepted for publication June 2, 1999.


   References
TOP
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Appendix
 References
 

  1. Wright, SM, Petersen, LA, Daley, J (1998) Availability of cardiac technology: trends in procedure use and outcomes for patients with acute myocardial infarction. Med Care Res Rev 55,239-254[Abstract/Free Full Text]
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  5. O’Connor, GT, Plume, SK, Olmstead, EM, et al (1992) Multivariate prediction of in-hospital mortality associated with coronary artery bypass graft surgery. Circulation 85,2110-2118[Abstract/Free Full Text]
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  7. Jones, RH, Hannan, EL, Hammermeister, KE, et al (1996) Identification of preoperative variables needed for risk adjustment short-term mortality after coronary artery bypass graft surgery. J Am Coll Cardiol 28,1478-1487[Abstract]
  8. Jenkins, DC, Stanton, BA, Savageau, JA, et al (1983) Coronary artery bypass surgery: physical, psychological, social, and economic outcomes six months later. JAMA 250,782-788[Abstract]
  9. Caine, N, Harrison, SCW, Sharples, LD, et al (1991) Prospective study of quality of life before and after coronary artery bypass grafting. BMJ 302,511-516
  10. Cameron, AA, Davis, KB, Rogers, WJ (1995) Recurrence of angina after coronary artery bypass surgery: predictors and prognosis (CASS Registry). J Am Coll Cardiol 26,895-899[Abstract]
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  16. Mozes, B, Olmer, L, Galai, N, et al (1998) A national study of postoperative mortality associated with coronary artery bypass graft surgery in Israel. Ann Thorac Surg 66,1254-1263[Abstract/Free Full Text]
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  18. Ash, A, Shwartz, M (1994) Evaluating the performance of risk-adjustment methods: dichotomous measures. Iezzoni, LI eds. Risk adjustment for measuring health care outcomes ,313-346 Health Administration Press Ann Arbor, MI.
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  20. Brandrup-Wognsen, G, Berggren, H, Caidahl, K, et al (1997) Predictors for recurrent chest pain and relationship to myocardial ischemia during long-term follow-up after coronary artery bypass grafting. Eur J Cardiothorac Surg 12,304-311[Abstract]




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