Report of STS Quality Measurement Task ForceThe Society of Thoracic Surgeons 2008 Cardiac Surgery Risk Models: Part 3—Valve Plus Coronary Artery Bypass Grafting Surgery
Section snippets
Study Population and Endpoints
Our general approaches to variable selection and risk model development have been described in the companion articles on isolated CABG (Part 1) and isolated valve surgery (Part 2). Details specific to the valve plus CABG models are included in this report.
Separate Versus Combined Models
Given the variety of approaches used in previous models by STS and other developers, we investigated the option of developing separate models for the AVR plus CABG and MVR plus CABG populations, and we also studied how best to subdivide the mitral plus CABG population into repair versus replacement. Although we had a large study population available, many of the individual outcomes were relatively rare. We were concerned that the number of events would be too small to permit reliable estimation
Selection of Candidate Predictor Variables
The candidate variables for the STS valve plus CABG models were identical to those in the STS isolated valve models, described in Part 2 of this series. They differed from the isolated CABG model variables in the following specific areas: (1) Percutaneous coronary intervention (PCI) occurring 6 hours or less before surgery was present in only 315 patients (0.3%) in the valve plus CABG study population, and was not included as a candidate variable. (2) Infectious endocarditis was not included in
Missing Data
Missing data are uncommon in the STS NCD, with a frequency of less than 1% missing for most variables. Model variables with more than 1% missing were ejection fraction (5.9%), New York Heart Association functional class (3.8%), tricuspid insufficiency (2.6%), aortic insufficiency (2.1%), mitral insufficiency (1.5%), and creatinine/dialysis (1.2%).
To make full use of the available data, binary risk factors were modeled as yes versus no or missing. Thus, missing values were analyzed as if the
Final Variable Selection Procedure
Variables were initially selected using an automated stepwise model selection algorithm. The stepwise procedure began with a model that included all of the candidate variables except for interaction terms. Age, body surface area, and month of surgery were forced into each model. As in the isolated CABG and isolated valve models described in Parts 1 and 2 of this series, month of surgery was used only to adjust for time trends in the frequency of adverse outcomes over the 5-year study period. We
Risk Factors, Outcomes, and Predictor Variables
Table 1 presents the distribution of risk factors and endpoints in the overall 2002 to 2006 study population. Because there are three valve plus CABG categories, space limitations prevent display of the bivariate relationships for each predictor variable, endpoint, and valve plus CABG group. These are available upon request from STS.
Table 2 summarizes the overall frequency of adverse outcomes as well as the outcomes for the three major valve groups. Table 3 lists the candidate predictor
Limitations
The limitations of the STS valve plus CABG models are similar to those discussed in Part 1 of this series.
Conclusion
A new STS model has been developed for valve surgery combined with CABG. This model includes specific indicator variables for each major type of valve plus CABG procedure (AVR plus CABG, MVR plus CABG, MVRepair plus CABG). Models have been developed for operative mortality, individual morbidity endpoints, a composite morbidity or mortality endpoint, and short and prolonged postoperative length of stay. Overall model performance is excellent.
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This author is deceased. Former Chair, Quality, Research and Patient Safety Council, The Society of Thoracic Surgeons, Chicago, IL.