HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Abstract Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Add to Personal Folders Download to citation manager Author home page(s): Herbert B. Ward Rosemary F. Kelly Permission Requests Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Adabag, A. S. Articles by Bloomfield, H. E. Search for Related Content PubMed PubMed Citation Articles by Adabag, A. S. Articles by Bloomfield, H. E. Related Collections Coronary disease

Ann Thorac Surg 2007;83:1744-1750
© 2007 The Society of Thoracic Surgeons

---

Original Articles: Cardiovascular

Prognostic Significance of Elevated Cardiac Troponin I After Heart Surgery

^a Division of Cardiology, Veterans Affairs Medical Center and the University of Minnesota, Minneapolis, Minnesota
^b Division of Cardiovascular Surgery, Veterans Affairs Medical Center and the University of Minnesota, Minneapolis, Minnesota
^c Center for Chronic Disease Outcomes Research, Veterans Affairs Medical Center and the University of Minnesota, Minneapolis, Minnesota

Accepted for publication December 29, 2006.

^_* Address correspondence to Dr Adabag, Veterans Affairs Medical Center, Section of Cardiology (111 C), One Veterans Dr, Minneapolis, MN 55417 (Email: adaba001{at}umn.edu).

	Abstract

Top Abstract Introduction Patients and Methods Results Comment Acknowledgments References

 
Background: Cardiac troponin I (cTnI) measured after heart surgery has been associated with operative mortality. We sought to determine whether measuring cTnI after heart surgery provides additional prognostic information beyond that provided by validated preoperative risk scores, the Veterans Affairs (VA) risk score and the European System for Cardiac Operative Risk Evaluation (EuroSCORE).

Methods: We retrospectively collected cTnI levels measured 24 hours after surgery in 1,186 patients who underwent coronary artery bypass graft surgery (n = 696) or valve surgery (n = 490). The outcomes were operative death and perioperative myocardial infarction. The ability of the cTnI and the risk scores to discriminate patients who did or did not have the study outcomes was assessed by the area under the receiver operating curve (c-index).

Results: Mean age was 66 ± 10 years. Median cTnI was 38 ng/mL after valve surgery versus 18 ng/mL after coronary artery bypass graft surgery (p < 0.0001). There were 51 operative deaths (4.3%) and 142 perioperative myocardial infarctions (12%). For every 50 ng/mL increase in cTnI, the odds of operative death increased by 40% (odds ratio, 1.4; 95% confidence interval: 1.2 to 1.6) after coronary artery bypass graft surgery and by 30% (odds ratio, 1.3; 95% confidence interval: 1.1 to 1.5) after valve surgery. Cardiac troponin I was a significant independent correlate of perioperative myocardial infarction and death (p < 0.0001) with a c-index of 0.70 for death. Addition of cTnI improved the c-indexes of the risk scores for predicting death (from 0.75 to 0.79 for the VA risk score; p = 0.1; and from 0.69 to 0.77 for the EuroSCORE; p = 0.005).

Conclusions: Postoperative cTnI measured 24 hours after heart surgery is independently associated with operative death and perioperative myocardial infarction and improves the ability to predict operative mortality in comparison with preoperative risk scores alone.

	Introduction

Top Abstract Introduction Patients and Methods Results Comment Acknowledgments References

 
More than 600,000 open heart surgeries are performed in the United States annually [1]. As operative mortality in heart surgery ranges from 1% to 4%, we can conservatively estimate that more than 6,000 deaths occur annually in relation to these procedures. In an effort to reduce the number of perioperative deaths, risk scores predicting the likelihood of perioperative mortality have been developed [2–12]. These risk scores utilize only preoperative clinical variables, however, and frequently do not account for the adverse intraoperative factors and events that also play a substantial role in the surgical outcome.

Cardiac troponins rise in almost all patients after heart surgery, indicating perioperative myocardial injury from a variety of insults [13–15]. Owing to their high sensitivity and specificity for myocardial injury, cardiac troponins may be utilized as a biomarker reflecting the cumulative intraoperative adverse effects on the myocardium. Indeed, it has been suggested that cardiac troponin level measured 18 to 24 hours after heart surgery is associated with postoperative death or prolonged hospitalization [13–19]. Furthermore, the American Heart Association/American College of Cardiology 2004 Practice Guidelines state that cardiac biomarkers measured in the first 24 hours after coronary artery bypass graft surgery (CABG) may aid in predicting prognosis [20]. Whether including cardiac troponins in a risk prediction model in addition to a validated preoperative risk score would improve our ability to predict perioperative death is unknown. Furthermore, whether cardiac troponins have prognostic value after valve surgery is also unknown, as previous study populations were largely composed of patients undergoing CABG.

We hypothesized that perioperative mortality prediction is more accurate when postoperative cardiac troponin I (cTnI) and a validated preoperative risk score are considered together in a large, retrospective cohort of patients who underwent CABG or valve surgery rather than when either cTnI or the risk score are considered alone.

	Patients and Methods

Top Abstract Introduction Patients and Methods Results Comment Acknowledgments References

 
Patient Population and Data Acquisition
The study included 696 consecutive patients who underwent CABG and 490 consecutive patients who underwent valve surgery with or without concomitant CABG at the Minneapolis Veterans Affairs (VA) Medical Center between January 1998 and December 2004. Patients undergoing other cardiac or thoracic procedures, 1 patient who died in the operating room, and 3 others who did not have postoperative cTnI were excluded from this analysis. Patients hospitalized for acute coronary syndrome who were operated on urgently or emergently (n = 87) were only included if preoperative cTnI was showing a downward trend. Preoperative clinical variables, procedural details, and outcomes, including operative mortality were obtained from the VA Continuous Improvement in Cardiac Surgery Program database, which is an ongoing database of prospectively collected data on all patients undergoing heart surgery in the VA system [3–5]. This database also includes a validated risk score (predicted probability of operative mortality) for each patient based on their preoperative risk factors. Cardiac biomarker results were obtained from the patients’ medical records, blinded to the surgical outcome. For patients who died, a cardiologist, masked to cTnI results, determined the causes of death by reviewing the hospital records. This study was approved by the Human Studies Subcommittee of the Research and Development Committee of the Minneapolis VA Medical Center on January 28, 2005. Individual consent was waived.

Preoperative Risk Scores
Va risk score
Since 1987, all VA cardiac surgical centers have completed a data form for each patient undergoing heart surgery for the Continuous Improvement in Cardiac Surgery Program [3]. The clinical data obtained consisted of 30 preoperative variables, cardiac catheterization findings, 10 variables about the operative procedure, and 11 outcome variables including operative mortality and major complications. Twice each year, statistical analyses are done to assess the performance of each cardiac surgical center and to refine regression models that use preoperative variables to predict operative mortality. Different prognostic models are used for patients undergoing CABG and for patients having valve operation with or without concomitant CABG. Variables exhibiting a p value of less than 0.2 in univariate analysis are included in the logistic regression models.

Euroscore
The European System for Cardiac Operative Risk Evaluation (EuroSCORE) was developed to assess risk factors for mortality in adult patients undergoing cardiac surgery in Europe [10–12]. Data were collected for 68 preoperative and 29 operative risk factors believed to influence hospital mortality. The relationship between risk factors and outcome was assessed by univariate and logistic regression analysis. All variables significant at a p value of less than the 0.2 level were entered into the model provided they were present in at least 2% of the sample. The EuroSCORE has been found to have equal or superior performance in comparison with other preoperative risk stratification models in heart surgery [21].

Biomarkers of Myocardial Necrosis
Cardiac troponin I and creatine kinase myocardial band fraction (CK-MB) are routinely measured after heart surgery at our medical center. Serial samples of approximately 5 mL blood were drawn for cTnI at 8-hour intervals for 24 hours after heart surgery, or longer if a peak cTnI or CK-MB level was not observed within 24 hours. In the present investigation, cTnI level drawn 24 hours after surgery as well as the peak cTnI and CK-MB levels within the first 24 hours were recorded.

Blood samples were assayed for CK-MB mass utilizing a commercially available assay (Abbott Laboratories, Abbott Park, Illinois). The conventional threshold of this assay for the diagnosis of myocardial injury at our institution was 5 ng/mL. Levels of cTnI were measured utilizing the Abbott assay (Abbott Laboratories). The lower limit of detection was 0.3 ng/mL, and the conventional threshold for the diagnosis of myocardial necrosis at our institution was 2.0 ng/mL. The 95th percentile of the cTnI level in a reference population was 0.4 ng/mL or less. The interassay coefficient of variation was 8.8% at a discriminator value of 2.0 ng/mL. Both assays were performed on an Abbott Axsym analyzer platform (Abbott Laboratories).

Outcomes
The primary outcome in this investigation was operative mortality defined as death within 30 days of heart surgery due to any cause, or death at a later time occurring as a direct consequence of a perioperative complication (eg, mediastinitis). Secondary outcomes were perioperative myocardial infarction and lengths of stay in the intensive care unit (ICU) and the hospital. Perioperative myocardial infarction was defined as typical serial changes on postoperative electrocardiogram (ST-segment elevation followed by new Q waves longer than 40 ms or new persisting ST-segment depressions greater than 2 mm in at least two contiguous leads; new left bundle branch block) and a CK-MB more than five times the upper limit of normal or clinical diagnosis of myocardial infarction by the patient’s physician based on electrocardiogram, echocardiogram, and biomarkers [20].

Data Analysis
Distributions of variables in the study cohorts were summarized as mean ± 1 SD deviation when normally distributed or median and interquartile range if skewed. Distributions of cardiac biomarkers and preoperative risk scores of patients who survived surgery and those who died were compared by the Wilcoxon rank sum test.

The crude association between cardiac biomarkers and operative death was examined by logistic regression analysis in which the biomarker level was used as a continuous variable. The ability of the risk scores and cardiac biomarkers to discriminate patients who did or did not survive the surgery (or who did or did not have perioperative myocardial infarction) was assessed by the c-index (the area under the receiver operating characteristic [ROC] curve) with 95% confidence intervals. A c-index equal to 0.5 indicates that the discrimination was no better than random predictions, whereas a c-index equal to 1.0 indicates perfect discrimination. To determine whether cardiac biomarkers added prognostic information to the preoperative risk score, both variables were entered into a multivariable logistic regression analysis as continuous variables [22]. An interaction term between the type of surgery (CABG or valve) and each biomarker was tested to determine whether the effect of the biomarker varied by the type of surgery. The c-index for the preoperative risk score was compared with the c-index for the combined use of the preoperative risk score and each cardiac biomarker by the method of Delong for correlated data available in the ROC procedure in Stata software (Stata Corp, College Station, Texas).

To determine if an association existed between the postoperative length of stay and cTnI, the number of days spent in intensive care unit and hospital were converted to the logarithmic scale, correlated with biomarkers, and entered into multivariate linear regression with clinical variables shown to be associated with length of stay in previous reports [23–26]. The 51 patients who had an operative death were excluded from the length of stay analysis. A p value of 0.05 was considered statistically significant. Stata software (version 8.2; Stata Corp, College Station, Texas) was used for all analyses. The authors had full access to the data and take responsibility for its integrity. All authors have read and agree to the manuscript as written.

	Results

Top Abstract Introduction Patients and Methods Results Comment Acknowledgments References

 
Patient Characteristics
A total of 1,186 patients who underwent CABG and valve surgery were studied. The mean age of the study population was 66 ± 10 years, 83 patients (7%) were octogenarians, and all but 6 were men (Table 1). Of the 1,186 patients, 481 (41%) had prior myocardial infarction, 134 (11%) had prior heart surgery, and 324 (27%) had left ventricular systolic dysfunction (ejection fraction <45%). On presentation, 386 patients (33%) were severely limited (classes III/IV) by heart failure and 687 (58%) by angina. The median predicted probability of operative death (VA risk score) was 3.3%, and the median EuroSCORE was 6 (Table 1).

Operative Mortality
Causes of death
There were 24 deaths (3.4%) among CABG patients and 27 deaths (5.5%) among patients who had valve surgery, for a total of 51 operative deaths (4.3%). Of these, 12 deaths (24%) were due to congestive heart failure or cardiogenic shock, 7 (14%) were due to sudden death, 5 (10%) were due to myocardial infarction, and 8 (16%) were due to stroke. Additional patients died of respiratory failure (n = 3), renal failure (n = 2), infection (n = 3), multiorgan failure (n = 4), aortic dissection or tear (n = 3), ischemic bowel (n = 1), or unknown causes (n = 3). Median time from surgery to death was 13 days (interquartile range, 5 to 24).

Risk scores
The descriptive statistics of the risk scores are outlined in Table 1. The EuroSCORE and the VA risk score were highly correlated with each other (Spearman rho = 0.79, p < 0.0001). Both risk scores were positively associated with operative death (OR, 1.2; 95% CI: 1.1 to 1.3 for a 1-point increase in the EuroSCORE; and OR, 2.6; 95% CI: 2.0 to 3.4 for a 0.1-point increase in the VA risk score; p < 0.0001). The c-indexes for the EuroSCORE and the VA risk score for predicting operative mortality were 0.69 (95% CI: 0.62 to 0.76) and 0.75 (95% CI: 0.68 to 0.82), respectively (p = 0.002; Fig 1).

View larger version (11K): [in this window] [in a new window]   Fig 1. Receiver operating curves for creatine kinase MB fraction (solid line [c-index = 0.63]), cardiac troponin I (dashed line [c-index = 0.70]), EuroSCORE (dotted line [c-index = 0.69]), and Veterans Affairs risk score (dashed-dotted line [c-index = 0.75]) for predicting operative death in 1,186 patients who underwent heart surgery. (EuroSCORE = European System for Cardiac Operative Risk Evaluation.)

Biomarker and risk score combination
When the cTnI and each of the risk scores were analyzed together in a logistic regression model, cTnI was a significant independent correlate of operative mortality (p < 0.0001 for both EuroSCORE and VA risk score). Addition of cTnI to the risk prediction model improved the ability of the model to predict operative death versus the risk scores alone (c-index for EuroSCORE increased from 0.69 to 0.77, p = 0.005; c-index for VA score increased from 0.75 to 0.79, p = 0.1).

Perioperative Myocardial Infarction
It was determined that 142 patients had perioperative myocardial infarction. Cardiac troponin I was significantly higher in patients who had myocardial infarction (median cTnI, 76 ng/mL; interquartile range, 155 ng/mL) than in patients who did not (median cTnI, 22 ng/mL; interquartile range, 38 ng/mL; p < 0.0001). Furthermore, cTnI was a significant correlate of perioperative myocardial infarction in CABG and valve surgery separately (p < 0.0001). The c-index for predicting perioperative myocardial infarction by cTnI was 0.81 (95% CI: 0.75 to 0.87) for patients who underwent CABG and 0.63 (95% CI: 0.56 to 0.69) for patients who underwent valve surgery.

Length of Stay
Median length of stay was 2.9 days (interquartile range, 1.9 to 4.1) in the ICU and 8.9 days (interquartile range, 6.8 to 13.2) in the hospital (Table 1). The cTnI was independently associated with log length of ICU and hospital stay after adjustment for age, surgical procedure, left ventricular function, New York Heart Association functional class, creatinine, diabetes mellitus, and chronic lung disease (p < 0.0001). However, the contribution of cTnI to the variation in log length of stay in the ICU and the hospital was not substantial (r ² = 0.05 in the univariate model and 0.02 in the final model).

	Comment

Top Abstract Introduction Patients and Methods Results Comment Acknowledgments References

 
This investigation showed that for a large cohort of patients undergoing CABG or valve surgery, cTnI measured 24 hours postoperatively was an independent predictor of operative mortality and perioperative myocardial infarction. Furthermore, including cTnI in addition to a preoperative risk score (eg, EuroSCORE or VA risk score) in the prediction model improved the model in discriminating patients who survived from patients who died compared with when the risk score or cTnI were considered alone. This is an important finding because it suggests that cTnI adds prognostic information above and beyond that already provided by a validated preoperative risk score.

The most notable strength of the present investigation was that cTnI, a biomarker reflecting the cumulative effects of various intraoperative insults on the myocardium, was considered in addition to a validated preoperative risk score to increase the prognostic utility of either one alone. This methodology has not been utilized in previous reports, which have largely focused on the prognostic utility of either preoperative risk scores or cardiac biomarkers [13–16, 18, 19]. The outcome of a cardiac surgical procedure is determined by preoperative as well as intraoperative factors that may be independent of each other. A procedure fraught with intraoperative complications may be associated with poor outcome for an otherwise low-risk patient. Conversely, an uneventful surgery may result in favorable outcome for a high-risk patient. Therefore, outcome predictions based solely on preoperative or intraoperative factors may be inaccurate. Indeed, in this investigation, cTnI level poorly correlated with the preoperative risk scores but, remarkably, was an approximately equal predictor of operative mortality based on c-index.

In the present investigation, the VA risk score was a better predictor of operative mortality than the EuroSCORE, which has gained wide acceptance among cardiothoracic surgeons and has been suggested to outperform other risk scores [21]. This finding may be explained on the basis of the dissimilarities between the present study population and those in the previous studies. The VA risk score was specifically designed and derived from VA patients and may therefore outperform other risk scores in a VA study population.

In comparison with the 24-hour cTnI, the peak CK-MB after heart surgery had a significantly weaker association with operative mortality. Therefore, CK-MB appears to be inferior to cTnI as a marker to assess prognosis after heart surgery. On the other hand, CK-MB returns to baseline levels 24 to 48 hours after its release, as opposed to cardiac troponins, which may stay elevated for 7 to10 days. Because of this feature, CK-MB should still be the cardiac enzyme of choice for diagnosing recurrent myocardial infarctions after heart surgery [27, 28].

We found that the cTnI was almost twice as high and was a more powerful prognostic test among patients who died of cardiovascular causes than among patients who died of other causes. However, perhaps because of the low number of deaths in our cohort, these differences did not achieve statistical significance. Also, cTnI may have been elevated in patients who died of noncardiac causes owing to the adverse effects of these factors on the myocardium. Indeed, cardiac troponins may be elevated in critically ill patients without coronary heart disease, suggesting poor prognosis [29].

In this study, cTnI was independently associated with length of stay in the ICU and the hospital, confirming the findings of a previous report [17]. Although statistically significant, however, this association was very weak after adjusting for preoperative clinical factors known to be associated with length of stay [23–26].

The following limitations of this study should be noted. First, the surgical operations compiled under the heading of valve surgery were heterogeneous. However, in this regard, we followed the categories used in the surgical literature and the Continuous Improvement in Cardiac Surgery Program database in which all operations on heart valves have been gathered under the single heading of valve surgery [3–5]. Also, in this investigation, off-pump and conventional CABG patients were considered as one group. When the analysis was repeated after excluding the off-pump cases, however, the results did not change. Second, short-term mortality was the only outcome variable in this investigation. It is possible that cTnI after surgery has a stronger relationship with long-term mortality in which the deaths due to surgical infection, sepsis, and other mechanical complications are largely eliminated. Third, cTnI level measured 24 hours after heart surgery and the peak cTnI within the first 24 hours were evaluated as predictor variables. While cardiac troponins drawn at other time points (eg, 8 or 16 hours after the operation) have been associated with operative mortality in the previous studies, cTnI at 18 to 24 hours after surgery has had the strongest association [13]. Finally, the cardiovascular surgeons caring for the patients in this study were not blinded to cTnI or CK-MB results. One cannot exclude bias that may have resulted from this knowledge. This is an inherent limitation of retrospective studies such as the present one.

In addition to the new methodology that utilized a validated preoperative score in the analysis, the strengths of this investigation include the relatively large sample size in comparison with the previous reports, which usually involved 200 to 500 patients [13–18]. In some of these reports, the small number of operative deaths necessitated using other, less-robust outcomes [13]. Also, in previous reports, valve surgery patients comprised only a small fraction of the study populations, whereas in this investigation, more than 40% of the study cohort underwent valve surgery.

In conclusion, cTnI measured 24 hours after heart surgery is an independent predictor of operative mortality, perioperative myocardial infarction, and length of stay in the hospital. Furthermore, considering cTnI in addition to a validated preoperative risk score such as the EuroSCORE or the VA risk score improves our ability to detect patients at high risk of perioperative death.

	Acknowledgments

Top Abstract Introduction Patients and Methods Results Comment Acknowledgments References

 
The authors are indebted to Jana Bonawitz-Conlin, BSN, MSH, RNC, for the collection of data for the Continuous Improvement in Cardiac Surgery Program. This work was supported by the Health Services Research and Development Offices of the Department of Veterans Affairs, Washington, DC. Doctor Adabag is supported, in part, by VA Clinical Science Research and Development Service (Grant no. 04S-CRCOE-001), Washington, DC. The views expressed in this article do not necessarily represent the views of the Department of Veterans Affairs.

	References

Top Abstract Introduction Patients and Methods Results Comment Acknowledgments References

 

1. American Heart Association Heart disease and stroke statistics—2006 update. Dallas, Texas: American Heart Association; 2006.
2. Jones RH, Hannan EL, Hammermeister KE, 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]
3. Grover FL, Hammermeister KE, Burchfiel C. Cardiac Surgeons of the Department of Veterans AffairsInitial report of the Veterans Administration preoperative risk assessment study for cardiac surgery. Ann Thorac Surg 1990;50:12-28.[Abstract]
4. Grover FL, Johnson RR, Shroyer AL, Marshall G, Hammermeister KE. The Veterans Affairs continuous improvement in cardiac surgery study Ann Thorac Surg 1994;58:1845-1851.[Abstract]
5. Grover FL, Johnson RR, Marshal G, Hammermeister KE. Factors predictive of operative mortality among coronary artery bypass subsets Ann Thorac Surg 1993;56:1296-1306.[Abstract]
6. Edwards FH, Grover FL, Shroyer AL, Schwartz M, Bero J. The Society of Thoracic Surgeons national cardiac surgery database: current risk assessment Ann Thorac Surg 1997;63:903-908.[Abstract/Free Full Text]
7. Hannan EL, Kumar D, Racz M, Siu AL, Chassin MR. New York State’s cardiac surgery reporting system: four years later Ann Thorac Surg 1994;58:1852-1857.[Abstract]
8. O’Connor GT, Plume SK, Olmstead EM, et al. Northern New England Cardiovascular Disease Group Multivariate prediction of in-hospital mortality associated with coronary artery bypass graft surgery Circulation 1992;85:2110-2118.[Abstract/Free Full Text]
9. Magovern JA, Sakert T, Magovern GJ, et al. A model that predicts morbidity and mortality after coronary artery bypass graft surgery J Am Coll Cardiol 1996;28:1147-1153.[Abstract]
10. Nashef SA, Roques F, Michel P, Gauducheau E, Lemeshow S, Salamon R. European system for cardiac operative risk evaluation (EuroSCORE) Eur J Cardiothorac Surg 1999;16:9-13.[Abstract/Free Full Text]
11. Roques F, Michel P, Goldstone AR, Nashef SA. The logistic EuroSCORE Eur Heart J 2003;24:881-882.[Medline]
12. Roques F, Nashef SA, Michel P, et al. Risk factors and outcome in European cardiac surgery: analysis of the EuroSCORE multinational database of 19030 patients Eur J Cardiothorac Surg 1999;15:816-823.[Abstract/Free Full Text]
13. Januzzi JL, Lewandrowski K, MacGillivray TE, et al. A comparison of cardiac troponin T and creatine kinase-MB for patient evaluation after cardiac surgery J Am Coll Cardiol 2002;39:1518-1523.[Abstract/Free Full Text]
14. Lasocki S, Provenchere S, Benessiano J, et al. Cardiac troponin I is an independent predictor of in-hospital death after adult cardiac surgery Anesthesiology 2002;97:405-411.[Medline]
15. Fellahi J-L, Gue X, Richomme X, Monier E, Guillou L, Riou B. Short- and long-term prognostic value of postoperative cardiac troponin I concentration in patients undergoing coronary artery bypass grafting Anesthesiology 2003;99:270-274.[Medline]
16. Kathiresan S, Servoss SJ, Newell JB, et al. Cardiac troponin T elevation after coronary artery bypass grafting is associated with increased one-year mortality Am J Cardiol 2004;94:879-881.[Medline]
17. Baggish AL, MacGillivray TE, Hoffman W, et al. Postoperative troponin-T predicts prolonged intensive care unit length of stay following cardiac surgery Crit Care Med 2004;32:1866-1871.[Medline]
18. Steen LS, Sievers HH, Peters H, et al. Cardiac troponin T for prediction of short- and long-term morbidity and mortality after elective open heart surgery Clin Chem 2004;50:1560-1567.[Abstract/Free Full Text]
19. Croal BL, Hillis GS, Gibson PH, et al. Relationship between postoperative cardiac troponin I levels and outcome of cardiac surgery Circulation 2006;114:1468-1475.[Abstract/Free Full Text]
20. Eagle KA, Guyton RA, Davidoff R, et al. ACC/AHA 2004 guideline update for coronary artery bypass graft surgery: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (committee to update the 1999 guidelines for coronary artery bypass graft surgery) Circulation 2004;110:e340-e437.[Free Full Text]
21. Nilsson J, Algotsson L, Hoglund P, Luhrs C, Brandt J. Comparison of 19 pre-operative risk stratification models in open-heart surgery Eur Heart J 2006;27:867-874.[Abstract/Free Full Text]
22. McIntosh M, Pepe MS. Combining several screening tests: optimality of the risk score Biometrics 2002;58:657-664.[Medline]
23. London MJ, Shroyer LW, Jernigan V, et al. Fast-track cardiac surgery in a Department of Veterans Affairs patient population Ann Thorac Surg 1997;64:134-141.[Abstract/Free Full Text]
24. Wong DT, Cheng DCH, Kustra R, et al. Risk factors of delayed extubation, prolonged length of stay in the intensive care unit and mortality in patients undergoing coronary artery bypass graft with fast-track cardiac anesthesia Anesthesiology 1999;91:936-944.[Medline]
25. Tu VJ, Jaglal SB, Naylor CD, Steering Committee of the Provincial Adult Cardiac Care Network of Ontario Multicenter validation of a risk index for mortality, intensive care unit stay, and overall hospital length of stay after cardiac surgery Circulation 1995;91:677-684.[Abstract/Free Full Text]
26. Katz NM, Ahmed SW, Clark BK, Wallace RB. Predictors of length of hospitalization after cardiac surgery Ann Thorac Surg 1988;45:656-660.[Abstract]
27. Wu AH, Apple FS, Gibler WB, Jesse RL, Warshaw MM, Valdes Jr R. National Academy of Clinical Biochemistry standards of laboratory practice: recommendations for the use of cardiac markers in coronary artery diseases Clin Chem 1999;45:1104-1121.[Abstract/Free Full Text]
28. Chen-Scarabelli C, Scarabelli T. Comparison of troponin T and creatine kinase-MB fraction in evaluating cardiac patients postoperatively J Am Coll Cardiol 2003;41:1065.[Free Full Text]
29. Ammann P, Maggiorini M, Bertel O, et al. Troponin as a risk factor for mortality in critically ill patients without acute coronary syndromes J Am Coll Cardiol 2003;41:2004-2009.[Abstract/Free Full Text]

This article has been cited by other articles:

				A. A. Mohammed, A. K. Agnihotri, R. R.J. van Kimmenade, A. Martinez-Rumayor, S. M. Green, R. Quiroz, and J. L. Januzzi Jr Prospective, Comprehensive Assessment of Cardiac Troponin T Testing After Coronary Artery Bypass Graft Surgery Circulation, September 8, 2009; 120(10): 843 - 850. [Abstract] [Full Text] [PDF]

				J. D. Muehlschlegel, T. E. Perry, K.-Y. Liu, L. Nascimben, A. A. Fox, C. D. Collard, E. G. Avery, S. F. Aranki, M. N. D'Ambra, S. K. Shernan, et al. Troponin is superior to electrocardiogram and creatinine kinase MB for predicting clinically significant myocardial injury after coronary artery bypass grafting Eur. Heart J., July 1, 2009; 30(13): 1574 - 1583. [Abstract] [Full Text] [PDF]

				L. Petaja, M. Salmenpera, K. Pulkki, and V. Pettila Biochemical Injury Markers and Mortality After Coronary Artery Bypass Grafting: A Systematic Review. Ann. Thorac. Surg., June 1, 2009; 87(6): 1981 - 1992.e3. [Abstract] [Full Text] [PDF]

				V. Aboyans, M. Frank, P. Lacroix, and M. Laskar Reply to Apostolakis et al. Eur. J. Cardiothorac. Surg., April 1, 2009; 35(4): 746 - 747. [Full Text] [PDF]

				J. E. Tcheng, I. H. Lim, S. Srinivasan, J. Jozic, C. M. Gibson, J. C. O'Shea, J. A. Puma, and D. I. Simon Stent Parameters Predict Major Adverse Clinical Events and the Response to Platelet Glycoprotein IIb/IIIa Blockade: Findings of the ESPRIT Trial Circ Cardiovasc Interv, February 1, 2009; 2(1): 43 - 51. [Abstract] [Full Text] [PDF]

This Article Abstract Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Add to Personal Folders Download to citation manager Author home page(s): Herbert B. Ward Rosemary F. Kelly Permission Requests Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Adabag, A. S. Articles by Bloomfield, H. E. Search for Related Content PubMed PubMed Citation Articles by Adabag, A. S. Articles by Bloomfield, H. E. Related Collections Coronary disease