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J Thorac Cardiovasc Surg 2008;135:180-187
© 2008 The American Association for Thoracic Surgery
Evolving Technology |
a Cardiopulmonary Research Science and Technology Institute (CRSTI), Dallas, Tex
b Medical City Dallas Hospital, Dallas, Tex.
Read at the Eighty-seventh Annual Meeting of The American Association for Thoracic Surgery, Washington, DC, May 5-9, 2007.
Received for publication May 4, 2007; revisions received August 29, 2007; accepted for publication September 12, 2007. * Address for reprints: Todd M. Dewey, MD, 7777 Forest Ln, Suite A323, Dallas, TX 75230. (Email: tdewey{at}CSANT.com).
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Abstract |
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 Top Abstract IntroductionPatients and MethodsResultsDiscussionReferences |
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Methods: Data were collected on 638 patients identified as having isolated aortic valve replacement between January 1, 1998 and December 31, 2006, using The Society of Thoracic Surgeons (STS) database. Long-term survival was determined from the Social Security Death Index or family contact. Operative risk was calculated using the STS Predicted Risk of Mortality, the EuroSCORE logistic and additive algorithms, and the Ambler Risk Score. Patients at or above the 90th percentile of risk (8.38% for STS, 33.47% for logistic, 12% for additive, 14.3% for Ambler) were identified as high risk. We then compared actual with predicted mortality and each algorithm’s ability to identify patients with the worst long-term survival.
Results: Operative mortality was 24 of 638 (3.76%). An additional 121 (19.0%) patients died during the follow-up study period (mean 4.2 ± 2.7 years). Overall mortality was 145 of 638 (22.7%). Expected versus observed mortality for the high-risk group by algorithm was 13.3% versus 18.8% for STS, 50.9% versus 15.6% for logistic, 14.0% versus 11.9% for additive, and 19.0% versus 13.4% by Ambler. Long-term mortality, per high-risk group, was 64.1% in the STS Predicted Risk of Mortality, 45.3% in the logistic, 45.2% in the additive, and 40.2% in Ambler Risk Score. Logistic regression showed that the STS algorithm was the most sensitive in defining the patients most at risk for long-term mortality.
Conclusion: The STS Predicted Risk of Mortality most accurately predicted perioperative and long-term mortality for the highest risk patients having aortic valve replacement.
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Introduction |
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TopAbstractIntroductionPatients and MethodsResultsDiscussionReferences |
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The prevalence of AS is expected to markedly increase as the US population ages, with aortic valve calcification and stenosis affecting the health of larger numbers of patients.2-4
Aortic valve replacement (AVR) has been the gold standard for the treatment of critical AS for decades, and the indications for its implementation have been well defined in the American College of Cardiology/American Heart Association 2006 Practice Guidelines for the Management of Patients with Valvular Heart Disease.5
Despite unequivocal data showing the efficacy of AVR for critical AS, there are indications that a significant number of patients may not be referred for surgical therapy. A recent report from Varadarajan and colleagues6 from Loma Linda reported that only 287 (38%) patients of 740 with AS, defined as a valve area of less than 0.8 cm2 by echocardiography, were referred for AVR. Additionally, the Euro Heart Survey on Valvular Heart Disease, a prospective survey of 5001 patients conducted at 92 centers across Europe, reported that 31.8% of patients did not undergo surgical intervention.7 Reasons given for nonoperative management in both studies included "old age," severe comorbidities, and patient refusal.
Transcatheter alternatives to standard AVR, with either self-expanding or balloon expandable valves, have been developed to reduce the anticipated mortality and morbidity of therapy in patients in whom the risk of conventional surgery for critical AS was considered to be too high. Early published data on procedural mortality and morbidity have demonstrated acceptable 30-day results.8 Patients with anticipated diminished operative survival, and by extension likely reduced long-term survival, comprise a logical treatment group in which to evaluate technology whose efficacy and in vivo durability are undetermined but offers the chance for potential decreases in morbidity and mortality. Fundamental to this process, however, is the ability to identify and select patients with an anticipated operative mortality with conventional surgery that would be considered prohibitive. Operative risk scoring algorithms are currently being used to identify the appropriate patient population for transcatheter therapy. However, the accuracy of these risk models in identifying high-risk patients appropriate for nonstandard valve therapy has not been fully validated. We evaluated four common risk scoring algorithms for their reliability in identifying high-risk patients undergoing isolated AVR for critical AS based on their accuracy in predicting operative outcomes and the ability to identify patients most likely to die during longer term follow-up.
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Patients and Methods |
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TopAbstractIntroductionPatients and MethodsResultsDiscussionReferences |
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The STS Predicted Risk of Mortality (STS-PROM) for aortic valve procedures was calculated when patient data were entered into the STS database, whereas the EuroSCORE algorithms (logistic [LES] and additive [AES]) were calculated according to published guidelines (http://www.euroscore.org/). The STS-PROM uses 24 variables of more than 50 total risk factors collected by the algorithm to predict mortality for valve procedures. The LES and AES collect the same 17 variables divided into three categories (patient-related factors, heart-related factors, and operation-related factors) but use differing methods of weighting to arrive at predicted risk. The AES uses an integer approach to calculate risk, whereas the LES uses a logarithmic approach. The Ambler score was also calculated for each patient according to previously published guidelines.9 The Ambler Risk Score (ARS) uses an integer approach with a conversion table to translate the additive score into a predicted risk. Patients’ risk factors are assigned points on the basis of 13 broad categories of preoperative variable ranging from age to the existence of diabetes and hypertension.9
The 90th percentile was calculated for each scoring system and then patients were allocated to a "high-risk" group if their score was at or above the 90th percentile. Inclusion into the high-risk cohort was variable depending on the risk model used to calculate predicted operative mortality.
Perioperative deaths (mortality within 30 days of the operation or during the same admission) were actively tracked from the STS database and late mortality was obtained by searching the Social Security Death Index or through direct telephone contact.10 Long-term follow-up for mortality was available for all patients. All statistical analysis was carried out with SAS 9.1.3 software (SAS Institute, Inc, Cary, NC).
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Results |
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Mean predicted operative mortality for the STS-PROM high-risk group was 13.31% compared with 50.87%, 14.04%, and 19.03% for the LES, AES, and ARS high-risk cohorts, respectively (Table 3).
Measured operative mortality was 18.75% (12/64) in the STS-PROM high-risk cohort, 15.63% (10/64) and 11.90% (10/84) in the LES and AES groups, respectively, and 13.40% (13/97) in the ARS group. The observed/expected ratios calculated for perioperative mortality were 0.31, 0.85, and 0.71 in the LES, AES, and ARS cohorts, respectively. The STS-PROM group had an observed/expected mortality ratio of 1.41. Longer-term follow-up showed that 45.3% (29/64) of the patients identified by the STS-PROM as being at high risk died within the follow-up period. Within the LES and AES groups, 29.7% (19/64) and 33.3% (28/84), respectively, of the patients identified as being at high risk died during the follow-up period. Only 26.8% (26/97) of the ARS patients were noted as having died. The concordant group showed an operative mortality of 27.6% (8/29) and long-term mortality of 34.5% (10/29) for an overall rate of 62.1%. Overall mortality (operative plus follow-up deaths) was greatest in the group designated as high risk by the STS-PROM.
Logistic regression analysis demonstrated that the STS-PROM had the highest odds ratio for predicting increased overall mortality: 8.06 (95% confidence interval [CI]: 4.63–14.01) compared with 3.27 (95% CI: 1.92–5.57) for LES, 3.45 (95% CI: 2.14–5.57) for AES, and 2.76 (95% CI: 1.75–4.36) for ARS when patients were identified as high risk. A Kaplan–Meier survival curve for the four different scoring models illustrates that despite similar operative mortality among the groups, the rate of decline for the STS-PROM cohort, especially in the first year after the operation, indicates a greater sensitivity in identifying patients with the worst long-term survival than the other algorithms (Figure 2).
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Discussion |
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TopAbstractIntroductionPatients and MethodsResultsDiscussionReferences |
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Increasingly, these models are also being used to identify appropriate patients for nonstandard or experimental therapy when their calculated risk profile is considered prohibitive with conventional approaches. The appeal of using these models is the ability to standardize inclusion into trials across many study sites, especially where surgical judgment comes into play and may vary between centers. The STS-PROM, EuroSCORE, and other risk models are currently being incorporated into various pivotal and feasibility studies as part of their patient selection algorithms and inclusion criteria. The usefulness of this approach depends on the accuracy of these algorithms to correctly identify the highest-risk patient populations. It is important to note that model accuracy can fluctuate over time owing to changes in surgical risk, especially for high-risk patients, and requires periodic review. In the case of transcatheter valve implantation, the risk models should reliably identify patients at excessive risk for conventional AVR and the predicted mortality in that cohort should reasonably correlate with observed outcomes.
We compared the three most commonly used risk algorithms, STS-PROM, LES, and AES, as well as a recently published risk model (ARS) developed specifically for patients undergoing valvular heart surgery, for predictive ability in the highest risk decile of a cohort having isolated AVR for critical AS. A different number of patients out of the total study population were calculated to be in the top 10% of risk depending on the model used, and a sizeable number of patients did not overlap between the models. Statistically, models demonstrate the most accuracy when a significant percentage of the study population has a particular risk factor that is included in the risk calculation. However, between each risk algorithm there can exist differences in definitions and differences in actual variables included in the risk calculation, leading to different patient stratification. For example, neurologic dysfunction in the EuroSCORE algorithm was defined to be disease that severely affects ambulation or day-to-day function, whereas the STS-PROM records only the history and timing of a previous cerebrovascular accident. The Ambler score does not include neurologic dysfunction or previous cerebrovascular accident in its calculation of risk of mortality. Other notable differences between algorithms involve the inclusion of New York Heart Association class, presence of cardiogenic shock, and need for preoperative intra-aortic balloon pump in the STS-PROM but not the AES, LES, or the ARS. Interestingly, despite the fact that more than 50 preoperative variables are collected by the STS-PROM, only 24 (listed in Table 1) are actually used in its mortality algorithm for patients having valve surgery, and preoperative ejection fraction is not included in the risk model. All models include patient age, sex, and a measure of renal function through the use of serum creatinine.
The STS-PROM underpredicted but closely approached the actual observed mortality from its identified patient group, with an observed/predicted ratio of 1.41. In contradistinction, the other three models overestimated predicted mortality, and all had an observed/predicted mortality of less than 1. Notably, the concordant population identified as high risk by all of the algorithms demonstrated not only the highest operative mortality (27.6%) but also the worst long-term survival, with an additional 10 (34.5%) of 29 dying during the follow-up period.
This illustrates the potential advantage of using multiple risk algorithms with a variety of risk factors to identify a high-risk population. One hundred percent accuracy is an unrealistic expectation for any single risk model for a number of reasons. These models are developed using large heterogeneous populations of patients and are derived by weighting different risk factors on the basis of the surgical outcomes of the whole study cohort. At the highest risk level, most of the patients have the same risk profiles (Table 2), therefore providing minimal interpatient variability in which to determine risk. This limitation in risk calculation may be a factor accounting for the difference between actual risk and that predicted by each individual model. In fact, several studies have shown that both the LES and AES overestimate the mortality in octogenarians undergoing valvular heart surgery.14,15
A further shortcoming of the models is that there are a number of demographic variables not collected by the risk models that have been shown to affect operative mortality.16 Hypoalbuminemia and poor nutritional status have both been shown to be independent risk factors associated with poor outcomes after cardiac surgery.17 In addition, Chang and colleagues18 have shown that patients receiving chest wall irradiation for an intrathoracic malignant tumor have reduced short- and long-term survival after cardiac surgery. Finally, frailty and debilitation are difficult conditions to objectively quantify for risk modeling and are best viewed through the prism of surgical judgment. It is worth emphasizing that all risk models are derived from patients who have actually undergone surgery; therefore, translating these algorithms to populations previously never referred for AVR may also limit their accuracy. Ultimately, the simultaneous use of multiple models to generate a concordant risk assessment will likely surpass the efficacy of any individual model.
In terms of selecting patients for experimental therapies, some underestimation of risk represents a more conservative approach than does overprediction. Overestimation runs the risk of potentially recruiting patients for a treatment of unknown durability who might do well with conventional surgery with known efficacy and long-term results. Operative mortality has historically been the most important performance parameter collected for patients having cardiac surgery. It is an objective variable with little room for ambiguity in data collection. However, for the elderly undergoing AVR, improvement in quality of life becomes the primary goal of surgical intervention as opposed to extending a diminished life expectancy. Transcatheter valve implantation has the potential to decrease the morbidity associated with standard AVR in a high-risk population owing to the avoidance of a median sternotomy, cardiopulmonary bypass, and cardioplegic arrest. Nevertheless, the selection process necessitates thoughtful consideration of the short- and long-term risks and benefits of the procedure and a comparison of these factors with alternative therapies. Overreliance on individual risk algorithms may introduce bias owing to the limitations of the model.
In summary, the STS-PROM appears to be the most reliable single risk scoring model of those evaluated for both perioperative mortality and long-term survival after isolated AVR for AS in extremely high-risk patients. Patient identification as high risk can differ widely between different models on the basis of the variables collected and the weighting used to calculate predicted mortality. Overestimation of risk, especially when used to identify patients for experimental treatment, may lead to inclusion of patients who could do well with conventional approaches. Determining the appropriate break point in predicted risk that confers candidacy for alternative approaches can be problematic given the illustrated limitations of these four commonly used algorithms. Surgical judgment should continue to be used in conjunction with risk scoring to identify these patients.
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A. Parolari, L. L. Pesce, M. Trezzi, L. Cavallotti, S. Kassem, C. Loardi, D. Pacini, E. Tremoli, and F. Alamanni EuroSCORE Performance in Valve Surgery: A Meta-Analysis Ann. Thorac. Surg., March 1, 2010; 89(3): 787 - 793. [Abstract] [Full Text] [PDF]
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 K. Leslie, P. S. Myles, A. Forbes, and M. T. V. Chan The Effect of Bispectral Index Monitoring on Long-Term Survival in the B-Aware Trial Anesth. Analg., March 1, 2010; 110(3): 816 - 822. [Abstract] [Full Text] [PDF]
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N Piazza, A Otten, C Schultz, Y Onuma, H M Garcia-Garcia, E Boersma, P de Jaegere, and P W Serruys Adherence to patient selection criteria in patients undergoing transcatheter aortic valve implantation with the 18F CoreValve ReValving System Heart, January 1, 2010; 96(1): 19 - 26. [Abstract] [Full Text] [PDF]
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 P. F. Ludman and H. Routledge Chapter 3 Risk assessment and analysis of outcomes Oxford Textbook of Interventional Cardiology, January 1, 2010; 1(1): med-9780199569083-chapter - med-9780199569083-chapter. [Abstract] [Full Text]
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J. G. Webb and F. Nietlispach Chapter 39 Transcatheter aortic valve replacement Oxford Textbook of Interventional Cardiology, January 1, 2010; 1(1): med-9780199569083-chapter - med-9780199569083-chapter. [Abstract] [Full Text]
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T. M. Dewey Invited Commentary Ann. Thorac. Surg., November 1, 2009; 88(5): 1474 - 1475. [Full Text] [PDF]
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 D. S. Bach, D. Siao, S. E. Girard, C. Duvernoy, B. D. McCallister Jr, and S. K. Gualano Evaluation of Patients With Severe Symptomatic Aortic Stenosis Who Do Not Undergo Aortic Valve Replacement: The Potential Role of Subjectively Overestimated Operative Risk Circ Cardiovasc Qual Outcomes, November 1, 2009; 2(6): 533 - 539. [Abstract] [Full Text] [PDF]
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E. Manasse Cooks and recipes Eur J Cardiothorac Surg, November 1, 2009; 36(5): 787 - 790. [Full Text] [PDF]
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T. M. Dewey and M. A. Herbert Editorial comment: Predicting operative risk: a worthy task -- an elusive goal Eur J Cardiothorac Surg, November 1, 2009; 36(5): 797 - 798. [Full Text] [PDF]
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F. De Robertis, A. Asgar, S. Davies, N. Delahunty, A. Kelleher, R. Trimlett, M. Mullen, and N. Moat The left axillary artery -- a new approach for transcatheter aortic valve implantation Eur J Cardiothorac Surg, November 1, 2009; 36(5): 807 - 812. [Abstract] [Full Text] [PDF]
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D. Wendt, B. R. Osswald, K. Kayser, M. Thielmann, P. Tossios, P. Massoudy, M. Kamler, and H. Jakob Society of Thoracic Surgeons Score Is Superior to the EuroSCORE Determining Mortality in High Risk Patients Undergoing Isolated Aortic Valve Replacement Ann. Thorac. Surg., August 1, 2009; 88(2): 468 - 475. [Abstract] [Full Text] [PDF]
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D. Himbert, F. Descoutures, N. Al-Attar, B. Iung, G. Ducrocq, D. Detaint, E. Brochet, D. Messika-Zeitoun, F. Francis, H. Ibrahim, et al. Results of Transfemoral or Transapical Aortic Valve Implantation Following a Uniform Assessment in High-Risk Patients With Aortic Stenosis J. Am. Coll. Cardiol., July 21, 2009; 54(4): 303 - 311. [Abstract] [Full Text] [PDF]
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N. Al-Attar, W. Ghodbane, D. Himbert, C. Rau, R. Raffoul, D. Messika-Zeitoun, E. Brochet, A. Vahanian, and P. Nataf Unexpected Complications of Transapical Aortic Valve Implantation Ann. Thorac. Surg., July 1, 2009; 88(1): 90 - 94. [Abstract] [Full Text] [PDF]
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N. Al-Attar, D. Himbert, F. Descoutures, B. Iung, R. Raffoul, D. Messika-Zeitoun, E. Brochet, F. Francis, H. Ibrahim, A. Vahanian, et al. Transcatheter Aortic Valve Implantation: Selection Strategy Is Crucial for Outcome Ann. Thorac. Surg., June 1, 2009; 87(6): 1757 - 1763. [Abstract] [Full Text] [PDF]
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M. W. A. van Geldorp, M. van Gameren, A. P. Kappetein, B. Arabkhani, L. E. de Groot-de Laat, J. J. M. Takkenberg, and A. J. J. C. Bogers Therapeutic decisions for patients with symptomatic severe aortic stenosis: room for improvement? Eur J Cardiothorac Surg, June 1, 2009; 35(6): 953 - 957. [Abstract] [Full Text] [PDF]
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A. Zajarias and A. G. Cribier Outcomes and Safety of Percutaneous Aortic Valve Replacement J. Am. Coll. Cardiol., May 19, 2009; 53(20): 1829 - 1836. [Abstract] [Full Text] [PDF]
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S. Leontyev, T. Walther, M. A. Borger, S. Lehmann, A. K. Funkat, A. Rastan, J. Kempfert, V. Falk, and F. W. Mohr Aortic Valve Replacement in Octogenarians: Utility of Risk Stratification With EuroSCORE Ann. Thorac. Surg., May 1, 2009; 87(5): 1440 - 1445. [Abstract] [Full Text] [PDF]
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F. T. Billings IV, S. K. Kodali, and J. S. Shanewise Transcatheter Aortic Valve Implantation: Anesthetic Considerations Anesth. Analg., May 1, 2009; 108(5): 1453 - 1462. [Abstract] [Full Text] [PDF]
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C. Diez, P. Mohr, O. Kuss, B. Osten, R.-E. Silber, and H.-S. Hofmann Impact of Preoperative Renal Dysfunction on In-hospital Mortality After Solitary Valve and Combined Valve and Coronary Procedures Ann. Thorac. Surg., March 1, 2009; 87(3): 731 - 736. [Abstract] [Full Text] [PDF]
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N. Khaladj, M. Shrestha, S. Peterss, I. Kutschka, M. Strueber, L. Hoy, A. Haverich, and C. Hagl Isolated surgical aortic valve replacement after previous coronary artery bypass grafting with patent grafts: is this old-fashioned technique obsolete? Eur J Cardiothorac Surg, February 1, 2009; 35(2): 260 - 264. [Abstract] [Full Text] [PDF]
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B. Zingone, G. Gatti, E. Rauber, P. Tiziani, L. Dreas, A. Pappalardo, B. Benussi, and A. Spina Early and Late Outcomes of Cardiac Surgery in Octogenarians Ann. Thorac. Surg., January 1, 2009; 87(1): 71 - 78. [Abstract] [Full Text] [PDF]
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 A. Vahanian, B. Iung, L. Pierard, R. Dion, and J. Pepper CHAPTER 21 Valvular Heart Disease ESC Textbook of Cardiovascular Medicine, January 1, 2009; 2(1): med-9780199566990-chapter - med-9780199566990-chapter. [Abstract] [Full Text] [PDF]
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 L. G. SVENSSON Evolution and results of aortic valve surgery, and a 'disruptive' technology Cleveland Clinic Journal of Medicine, November 1, 2008; 75(11): 802 - 804. [Full Text] [PDF]
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P. T.L. Chiam and C. E. Ruiz Percutaneous Transcatheter Aortic Valve Implantation: Assessing Results, Judging Outcomes, and Planning Trials: The Interventionalist Perspective J. Am. Coll. Cardiol. Intv., August 1, 2008; 1(4): 341 - 350. [Abstract] [Full Text] [PDF]
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A. Vahanian, O. R. Alfieri, N. Al-Attar, M. J. Antunes, J. Bax, B. Cormier, A. Cribier, P. De Jaegere, G. Fournial, A. P. Kappetein, et al. Transcatheter valve implantation for patients with aortic stenosis: a position statement from the European Association of Cardio-Thoracic Surgery (EACTS) and the European Society of Cardiology (ESC), in collaboration with the European Association of Percutaneous Cardiovascular Interventions (EAPCI) Eur J Cardiothorac Surg, July 1, 2008; 34(1): 1 - 8. [Abstract] [Full Text] [PDF]
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F. Descoutures, D. Himbert, L. Lepage, B. Iung, D. Detaint, D. Tchetche, E. Brochet, Y. Castier, J.-P. Depoix, P. Nataf, et al. Contemporary surgical or percutaneous management of severe aortic stenosis in the elderly Eur. Heart J., June 1, 2008; 29(11): 1410 - 1417. [Abstract] [Full Text] [PDF]
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M. J. Antunes Percutaneous aortic valve implantation. The demise of classical aortic valve replacement? Eur. Heart J., June 1, 2008; 29(11): 1339 - 1341. [Full Text] [PDF]
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A. Vahanian, O. Alfieri, N. Al-Attar, M. Antunes, J. Bax, B. Cormier, A. Cribier, P. De Jaegere, G. Fournial, A. P. Kappetein, et al. Transcatheter valve implantation for patients with aortic stenosis: a position statement from the European Association of Cardio-Thoracic Surgery (EACTS) and the European Society of Cardiology (ESC), in collaboration with the European Association of Percutaneous Cardiovascular Interventions (EAPCI) Eur. Heart J., June 1, 2008; 29(11): 1463 - 1470. [Abstract] [Full Text] [PDF]
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