Original ArticleTwo Long-Term Mortality Risk Models For Coronary Artery Bypass Graft Surgery Produced in American Populations Validated in an Australian Population
Introduction
There is an important role for accurate risk prediction models for long-term mortality in current cardiac surgical practice. Risk models aim to identify and weigh patient demographic characteristics and risk factors that influence specific patient outcomes. In cardiac surgery, risk models can be used in the performance profiling of surgeons, hospitals or countries where they can retrospectively adjust for case-mix differences between groups. They can also be used prospectively for patient counselling, informed consent and the identification of low- or high-risk patient subgroups that may require closer follow-up. Most of the interest in such models has centred on those that predict short-term outcomes.
Long-term mortality risk models are a relatively recent addition to cardiac surgery. Historically, short-term mortality risk factors were studied and then developed into short-term mortality risk models [1], [2], [3], [4], [5], [6], [7], [8], [9]. These were subsequently implemented into clinical decision-making and provider profiling worldwide. More recently, however, there has been a greater emphasis on long-term mortality risk factors. These are vastly published throughout the literature and have subsequently been developed into long-term mortality risk models and prediction tools [10], [11], [12]. Two of the currently available long-term risk models for coronary artery bypass graft (CABG) surgery, developed in the United States of America, include:
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New York State’s Cardiac Surgery Reporting System (NYSCSRS) risk model [10]
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Northern New England Cardiovascular Disease Study Group (NNECDSG) risk model [12]
Risk scoring systems are most applicable when the preoperative patient characteristics and treatment profiles are comparable with those on which the system was originated. For this reason any risk scoring system can only be used reliably when its validity has been tested in the local patient population [13]. Therefore, without validation within an Australian dataset, the long-term risk models listed above have limited use for cardiac surgery within Australia.
The NYSCSRS risk model is reported to predict mortality up to seven years following surgery whilst the NNECDSG risk model is reported to predict mortality up to eight years following surgery. The formulae from these two risk-models was applied within the Australian and New Zealand Society of Cardiac and Thoracic Surgeons (ANZSCTS) database to study its ability to stratify risk within this population.
Section snippets
Database
The ANZSCTS National Cardiac Surgery Database Program has prospectively collected information on adult patients undergoing cardiac surgery in Australia since 2001. Currently, 28 hospitals across Australia are contributing data to the registry. The registry collects 287 preoperative, intraoperative and postoperative variables using internationally standardised data definitions [7], [14]. The data collection and its audit methods were discussed previously [1], [7]. The registry was used to
NYSCSRS x ANZSCTS
The two populations (ANZSCTS and NYSCSRS) were very similar. The only significant difference was in the prevalence of left main coronary artery stenosis of greater than 50%. The demographic data and the frequency of risk factors are shown in Table 2.
Of the 34,961 patients studied, there were 792, 1402, 2015 and 2458 deaths observed at one, three, five and seven years following surgery, respectively. These figures correlate to observed mortality rates of 2.3%, 4.0%, 5.8% and 7.0%, respectively.
Discussion
Long-term mortality risk prediction tools for CABG surgery can play an important role in cardiac surgery practice. They can be used to meaningfully compare the outcomes between surgeons, hospitals or even countries by adjusting for the variable case-mix that is typically present. Furthermore, they can be used in the decision-making process for surgeons who are deciding whether or not to undertake CABG surgery on a particular patient. In order for surgeons to use an accurate risk prediction
Conclusions
The NYSCSRS and NNECDSG long-term mortality risk models for CABG surgery could not be validated within the ANZSCTS population.
The NYSCSRS risk model showed poor statistical precision at all time points (one, three, five and seven years following surgery), however, showed good statistical accuracy with C-statistics between 0.741 and 0.779 across the four time points. Therefore, the NYSCSRS risk model can stratify risk within the ANZSCTS population quite well, however, if the risk model were to
Acknowledgements
ANZSCTS Data Management Centre, CCRE, Monash University: Prof Chris Reid, Dr Lavinia Tran, Ms Dhenisha Dahya, Mrs Angela Brennan.
ANZSCTS Database Program Steering Committee: Mr Gil Shardey (Chair), Mr Peter Skillington, Mr Julian Smith, Mr Andrew Newcomb, Mr Siven Seevanayagam, Mr Bo Zhang, Mr Hugh Wolfenden, Mr Adrian Pick, Mr Jurgen Passage, A/Prof Rob Baker, Prof Chris Reid, Dr Lavinia Tran, Mrs Angela Brennan, Mr Andrew Clarke.
The Australian and New Zealand Society of Cardiac and Thoracic
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