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SECTION 3
General outcomes of coronary
artery bypass gra surgery
Section editors:Stephen E.Fremes and Michael E.Halkos
14. Perioperative risk scoring systems for coronary
artery bypass grafting 131
T. Bruce Ferguson and Samer A.M. Nashef
15. Quality metrics in coronary artery bypass
grafting 135
Mario Gaudino, Vipin Zamvar, and Richard L.Prager
16. Early and late outcomes after coronary artery
bypass grafting 139
Stephen E.Fremes, Joseph F.Sabik, III, David P.Taggart,
Derrick Y.Tam, and Reena Karkhanis
17. Evidence base for off- pump coronary artery
bypass grafting:pros and cons 147
Emmanuel Moss, Michael E.Halkos, and John D.Puskas
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14
Perioperative risk scoring systems
forcoronary artery bypassgraing
T. Bruce Ferguson and Samer A.M. Nashef
Rationale
From extensive and comprehensive observational and randomized
trial data, we know with relative certainty which patients with coronary heart disease will benet from coronary artery bypass graing
(CABG), the degree of any symptomatic improvement, and the likelihood of long- term relief of symptoms and avoidance of cardiac
events. Other data are suggestive of the probability of the long- term
prognostic advantage of CABG versus other therapies for stable ischaemic heart disease. We also know, with a degree of accuracy not
available in other medical elds, the risk that CABG poses to life and
to health, and this is thanks to risk models.
Risk models allow the prediction of mortality and morbidity aer
surgery. is is useful for at least three reasons. First, it allows truly
informed consent:a patient cannot agree to an intervention without
some idea of the expected risk to life. e second is surgical decision-
making:the surgeon should not oer an operation without some idea
of the risk to the patient’s life. e third is quality control:knowing
the predicted mortality of surgery in a group of patients allows robust statistical comparison with the actual mortality, and this helps
evaluate the clinical outcomes achieved by an institution, unit, or
individual surgeon.
Knowledge of who is likely to develop major morbidity has an
impact on consent, may provide guidance on the optimal uses of
resources, may allow for sensible planning, and may help clinicians
to determine when further eorts are futile. Despite these attributes,
however, the quest for the perfect predictor— a crystal ball to foresee
the future— has not yet been fully achieved.
Risk models or scoringsystems
Scoring systems allow reasonable prediction of outcome aer cardiac surgery. Many models have been devised to work out the likelihood of survival. ey and others have also been shown to predict
major morbidity, long- term survival, and resource use with some
accuracy. Models can be divided into two groups:
• Preoperative models, applied before the operation, with no know-
ledge of intraoperative events.
• Postoperative models, applied aer surgery on admission into the
critical care unit, taking some account of what the operation did
to the patient.
Since postoperative models in CABG are not available for aggregate
national level use in CABG, this chapter will address only preoperative models.
Preoperativemodels
ese are most useful for measuring the risk of surgery as an adjunct to decision- making on the basis of risk- to- benet assessment,
and they have been used extensively to monitor the quality of care.
However, because they take no account of unexpected events in the
operating room, they are less useful in predicting which postoperative patients are likely to emerge intact from the operating room and
thereaer from the critical care unit.
ere are more risk models in cardiac surgery than in any other
area of medicine. Most rely on a combination of risk factors, each of
which is given a numerical ‘weight’. Weights are added, multiplied,
or otherwise mathematically processed to produce a percentage
gure predicting mortality. In additive models, weights given to the
risk factors are simply summed to give the predicted risk. ese are
easy to use and can be calculated mentally or ‘on the back of an envelope’. ey are less accurate than more sophisticated systems and
have a tendency to overscore slightly in low- risk patients and to
underscore considerably in very high- risk patients. Examples are the
original Parsonnet (the pioneering heart surgery risk model) and
the additive European System for Cardiac Operative Risk Evaluation
(EuroSCORE) for cardiac surgery overall. Other models deal specifically with cardiac surgical subsets, such as CABG, valve surgery, and
combined surgery. More sophisticated procedure- based models use
Bayesian analysis, logistic regression, or computer neural networks.
Examples of such models are the Society of oracic Surgeons (STS)
model, the logistic EuroSCORE, and EuroSCORE II. ey are more
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stable than additive models across the risk range and slightly more
accurate.
e widespread application of scoring systems in heart surgery
has allowed robust performance measurement, which has contributed to the dramatic improvement in quality in CABG surgery seen
over the past 25years.
Preoperative model riskfactors
Standard variables common to all models include age, sex, clinical
presentation, le ventricular function, and indication for surgical
intervention. Other risk factors that may be included are comorbidity variables such as hypertension, diabetes, obesity, vascular
disease, smoking history, and renal failure. Models also dier
depending on whether they deal with all types of heart operations
or only with a specic subset, such as CABG. e most widely
used models in CABG worldwide are EuroSCORE II and the STS
models. ey share many risk factors but dier in several areas. e
models are easily accessible online where there are interactive calculators available (http:// www.euroscore.org and http:// riskcalc.sts.
org/ stswebriskcalc/ ). Both EuroSCORE II and the STS models oer
a smartphone ‘app’ for bedside use.
EuroSCOREII
e EuroSCORE II model was published in 2012, having been developed when the original model lost its calibration as surgical results
improved worldwide. It was based on prospectively collected risk
factor and survival outcome data from 22,381 consecutive patients
operated in 154 hospitals in 43 countries over a 12- week period
(May– July 2010). e model was designed for global major cardiac
surgery, but about half of the data came from CABG patients. Risk
factors included in EuroSCORE II can be classied into three broad
categories:those relating to the patient, the heart, or the procedure.
Patient- related factors include age and sex, with a progressively
higher risk above the age of 60years and with females having a
higher operative mortality for CABG than males, possibly because
of smaller coronary artery size. Renal dysfunction increases risk,
with outcomes progressively worse with falling creatinine clearance.
Interestingly though, patients on dialysis with virtually no renal
function do better than those with severely impaired renal function
but not on dialysis. Other risk factors are insulin- dependent diabetes, chronic lung disease, extracardiac arteriopathy, impaired mobility due to neurological or musculoskeletal disorder, prior heart
surgery, active endocarditis, and a critical preoperative state.
Heart- related factors include impaired le ventricular function,
as estimated by echocardiography, angiography, or magnetic resonance imaging. Determining the exact degree of impairment is
operator dependent and may vary with the timing and modality of
investigation. In EuroSCORE II, le ventricular function is classied
as ‘good’, ‘moderate’, ‘poor’, or ‘very poor’. Other heart- related factors
are recent infarction, angina severity, NewYork Heart Association
class, and pulmonary hypertension.
Operative factors include the degree of urgency (elective, urgent,
emergency or salvage).
e application of EuroSCORE II into clinical practice has demonstrated the overall benets and shortcomings of new model development and validation. Nevertheless, validation exercises have
shown that the model works well both in the general and isolated
CABG cardiac surgical populations. It has the additional advantage
of being easy to use in that the risk assessment can be obtained in a
couple of minutes.
STSmodels
e STS risk model for CABG is similar to the EuroSCORE II
model, both in concept and design. Also, the STS CABG model has
the same limitations at both the low end and high end of risk predictions as does EuroSCORE II. Rather than compare the two, this
discussion will focus on the substantial impact of STS risk model use
in cardiac surgery in the United States over three decades.
e STS CABG risk model development began in 1985, and has
grown to capture clinical outcome data from over 95% of hospitals
in the United States performing bypass surgery (>1000 centres with
>4million CABG records). is vast amount of clinical data has
been used to develop multiple versions and updates to the CABG
risk models for mortality, morbidity, and major adverse outcomes
of stroke, renal failure, prolonged ventilation, deep sternal infection,
reoperation, and short and long length of stay. e STS organization has maintained scientic objectivity over the database through
the partnership with the Duke Clinical Research Institute (DCRI;
Durham, NC, USA) spanning over 20years.
For participating sites, data are reported semi- annually back to
the sites, providing risk- adjusted outcomes analysed at institutional
level, with comparison to national, regional, and like- institution
benchmarks. Approximately 35% of STS sites voluntarily participate
in the Consumer Reports public reporting initiative. e risk model
data are reported as predicted risk of mortality and observed- toexpected ratio. At individual sites, local data may be analysed at both
group and individual surgeon levels, but individual surgeon data are
not reported nationally.
e current logistic regression 30- day CABG models for mortality,
morbidity, and combined have a total of 40 multivariate variables, as
seen at http:// riskcalc.sts.org/ stswebriskcalc/ calculate. Beginning
around 2010, individual STS sites combined their data with Social
Security Death Index data to link the 30- day STS outcomes to longterm outcomes. Investigators have published important and novel
ndings through this mechanism., In the ASCERT trial, the STS,
DCRI, and the American College of Cardiology’s national interventional registry have developed probabilistic matching algorithms for
comparative long- term analyses following percutaneous coronary
intervention and CABG.
Trends inoutcomes
Over 25 years, the inverse relationship between predicted risk of
mortality and national CABG mortality showed a sustained reduction in mortality despite worsening patient risk prole. Since 2010
this steady decline in national risk- adjusted CABG mortality has
levelled out at around 2%, prompting some to question whether a
national risk- adjusted mortality of less than 1% is realistic or achievable, and if not, why not.
Aggregate datause
One of the most important contributions of the national database
over 25years has been to address quality of CABG care in the United
States, a continuous quality improvement process that continues locally and nationally today. CABG was the rst procedure for which
quality metrics, based on STS data, were approved and endorsed as a
quality measure dataset by the National Quality Forum. roughout
14 Perioperative risk scoring systems forcoronary artery bypassgrafting 133
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these eorts, the rigorous analytical validation by DCRI has been
critically important.
National, regional, and local qualityimprovement
In 1999, the STS was among the rst specialty societies to receive
extramural grant funding for clinical research and, with DCRI, embarked on an ambitious national continuous quality improvement
trial in CABG, funded for 7 years by the Agency for Healthcare
Research and Quality and generating the two largest continuous
quality improvement trials in medicine. Multiple variables proven
to be of benet to patient outcomes were tested as process measures,
including preoperative beta blockade in the preoperative period, internal thoracic artery gra use within the operation itself, and secondary prevention post CABG. Both trials documented improved
adoption of these measures both locally and nationally, and these
improvements have been sustained over time, proving that a lowlevel continuous quality improvement intervention built on this national database markedly improves care.
e eectiveness of regional and state- wide group eorts focused
on quality improvement in CABG using this database infrastructure has been demonstrated as well during this 25- year span. e
Virginia Cardiac Surgery Quality Improvement Initiative eort has
perhaps been the most comprehensive, where combining clinical
and nancial outcomes data from these centres has linked clinical
quality improvement with healthcare value.
Site performanceevaluation
Risk- adjusted outcomes data have also been used by the STS to create
a ‘star rating’ system for unit performance. Based on preoperative
and postoperative variables and risk- adjusted outcomes, sites are
assigned a rating of one, two, or three stars, three being the best.
Approximately 10– 12% of sites in the STS network perform at the
three- star level and a similar proportion at the one- star level, with
some transition across star rating levels each monitoring interval.
In the United Kingdom, unit- specic and surgeon- specic riskadjusted outcome data based on a locally modied EuroSCORE
model have been made available in the public domain for several
years (http:// scts.org/ outcomes/ ). is high level of transparency
may have led to some adverse patient outcomes, with some surgeons
tending to avoid operating on high- risk patients purely because of
concern about named- surgeon outcome data publication.
1. Adaptation of risk models reliably to include physician- level
intraoperative data and decisions. Currently, only a small number
of intraoperative variables are captured, and we have minimal
understanding of the impact of individual surgeon technical skill
and intraoperative decision- making on outcomes. e oscillation of risk- adjusted mortality in the United States around 2%
for the past 7years might reect a limitation of hospital- level
analyses, and highlights the need to analyse practice at this more
granular surgeon- specic level.
2. Adaptation of risk models to include contemporary ischaemic
heart disease science. Our datasets remain procedure based,
and the technique of CABG is anatomy based. While SYNTAX
trial results validate this historical approach, they are now challenged by functional data from the major fractional ow reserve trials, and the data driving the primary hypothesis of the
$100million NHLBI ISCHEMIA trial (ClinicalTrials.gov identier: NCT01471522). Infrastructure and scientic changes to
our databases will be necessary as these and other developments
continue.
3. Adaptation of risk models and infrastructure to include real- time
intraoperative technical and outcomes data. In the spectrum of
the long- term patient journey, the intraoperative section remains a ‘black box’. Objective quality documentation in CABG
is lacking: worldwide, industry data document that less than
25% of CABG cases have any intraoperative documentation of
technical quality. Any alteration in patient risk prole during the
perioperative period can reect the quality of the surgery performed. In addition, objective intraoperative data from imaging
platforms and these diseased- based technical factors need to be
incorporated into the Ischemic Heart Disease continuum of care
(preoperative, procedural, and long- term outcome) for these
patients. All this information, when available and integrated,
would constitute a powerful tool for evaluating the scientic,
quality, and health value aspects of CABG in future, building on
excellence achieved to date.
4. e ability to directly and inexpensively link patient les in the
STS and other national databases with national death indices
would provide a powerful tool to correlate preoperative patient
risk factors, operative techniques, and longer- term clinical outcomes. is would require a change in legislation but would empower a new era in clinical research and quality improvement
in CABG.
Thefuture
Conclusion
Risk models help doctors and patients make decisions about care and
provide a benchmark to gauge the quality of medical services. Risk
models have come a long way but are not perfect; keeping up with
developments in surgical technology is a challenge, for example.
In practice, these models should complement rather than replace
sound clinical judgement. e unprecedented success of CABG in
ischaemic heart disease revascularization is partly based on these
25- year developments. What about the next 25years?
As our knowledge and understanding of ischaemic heart disease evolves, CABG and its ‘data infrastructure’ must evolve with
it. Future strategy will combine science, technology, and healthcare
value data, and new developments are likely to include:
Risk modelling is a new science that has transformed procedural
care worldwide. e outstanding results of CABG can never be uncoupled from the reporting, benchmarking, and quality inuences
of these datasets. Rigorous observational analyses have been validated by recent results of seminal randomized trials, and this cycle
holds scientic promise in the future. Continued scientic improvement in risk models based on these observational datasets, as evidenced by the EuroSCORE experience, and in their application, as
evidence by the STS experience, can be expected. For certain, these
national database eorts in Europe, the United States, and around
the world will continue to adapt to the evolution of the technical,
SECTION 3 General outcomes of coronary artery bypass graft surgery134
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medical, contextual, and the healthcare value aspects of CABG
revascularization.
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Goldstone AR, etal.EuroSCORE II. Eur J Cardiothorac Surg.
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JB, etal. 2008 Cardiac surgery risk models:part1— coronary
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FL, STS National Database Committee. Adecade of change— risk
proles and outcomes for isolated coronary artery bypass graing
procedures, 1990– 1999:a report from the STS National Database
Committee and the Duke Clinical Research institute. Society of
oracic Surgeons. Ann orac Surg. 2002;73(2):480– 9.
10. Ferguson TBJr, Coombs LP, Eiken MS, Carey M, Grover FL,
Levett JM, etal. Use of continuous quality improvement to
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mammary artery graing in patients undergoing coronary artery
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15
Quality metrics incoronary artery
bypassgraing
Mario Gaudino, Vipin Zamvar, and Richard L. Prager
The definition ofquality insurgery
Quality may be dened dierently by dierent individuals and the
objective measurement of quality is oen challenging. In the United
States Institute of Medicine’s 1990 report, Medicare:A Strategy for
Quality Assurance, the denition of quality included:‘the degree to
which health services for individuals and populations increase the
likelihood of desired health outcomes and are consistent with current professional knowledge’.
e foundational denition of quality in medicine, and certainly
in surgery comes from Avedis Donabedian’s 1966 article utilizing
the triad of structure, process, and outcome. Structure refers to the
inherent characteristics of the setting where care is provided, process
to the particulars and procedural details of the care, and outcome to
the end results of the care.
Structure
Structural variables for quality assessment are measures of the setting where care is provided. ey usually describe hospital size and
practice, type of resources, sta ratios and expertise, and coordination of care.
Procedural volume is probably the most studied structural
measure. Alarge body of evidence has correlated volume to outcome
in coronary artery bypass graing (CABG) with contradicting results. e strength of the association of CABG volume with outcome
has varied considerably in dierent studies.– Probable reasons for
the reported contradictions are the complex interactions between
surgeons and hospital volume, between individual operator experience and level of non- operative care, and methodological consideration on data sources and sample selection. Overall, the strength
of the volume/ outcome association for CABG can be considered
weak. Importantly, maximizing adherence to quality measures has
been shown to improve mortality rates for CABG independent of
hospital or surgeon volume.
In other elds of surgery, an important structural measure is
the level of subspecialty training. In oncology and general surgery,
there is evidence that subspecialty training is associated with better
outcomes. In cardiac surgery, CABG has not traditionally been
considered a subspecialty, like aortic or transplant surgery. However,
the increase in the complexity of the procedure (anaortic CABG,
use of multiple arterial gras) and preliminary evidence suggesting
improved clinical results with subspecialized coronary surgery
units have led some authors to advocate for the creation of a CABG
subspecialty. Of note, subspecialty training of intensive care unit
teams and nurses has also been associated with reduced mortality
aer cardiac surgery.
Nurse- to- bed- ratio, access to up- to- date technology, and level of
care coordination are structural variables oen considered in quality
measurement and assessment. Failure to rescue is another important indicator of the ability of the system to neutralize the negative impact of complications on outcome that could be considered
as a quality metric.
e use of structural measures has obvious advantages in
terms of expediency and availability. Most of these variables
are easily and inexpensively available and can be accessed using
administrative data.
However, evidence on the association between most of the
structural measures and outcomes is incomplete and preliminary.
Published data focus on a very small number of variables and outcomes. In addition, structural variables are not readily actionable
by providers and this may limit their utility in the process of quality
improvement. Finally, structural measures reect average results for
large groups and are unable to reect even large variability in care.
Process
Process describes the care that patients actually receive, and the
compliance with evidence- based recommendations.
Most of the process measures used for quality measurement (compliance with screening practice, secondary prevention strategies, or
desirable practice guidelines) have been validated in non- surgical
specialties. Consequently, most process variables used to evaluate
the quality of cardiac surgery in general and CABG, in particular,
are related to the medical, and not surgical, part of the procedure
and are now expanded into the pre- and postoperative time frames
(use of prophylactic antibiotics, beta blockers, antiplatelet agents,
and lipid- lowering drugs).
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e only notable exception is the use of at least one internal thoracic artery gra, due to the almost universally recognized clinical
benets associated with revascularization of the le anterior descending artery with this conduit. e use of additional arterial
gras has been advocated by some as a possible additional quality
measure. Other proposed (but not widely adopted) process quality
measures specic to CABG relate to the intraoperative assessment
of gra patency, the completeness of revascularization, and the
perioperative use of blood products. Markers of waiting times are
also a quality indicator in various health services (United Kingdom,
Canada).
e relation of process measures with outcome is usually supported by a higher level of evidence compared to structural variables. Also, process variables more closely reect the care that
patients actually receive and are usually perceived as ‘fairer’ measures of quality. Importantly, process measures are easily actionable
by providers.
On the other hand, the rewards of process measures may induce
Box 15.1 Quality measures adopted bythe Society ofThoracic
Surgeons forCABG
Perioperative medication domain, scored all- or- none and consisting
of:
• Preoperative beta blockade.
• Beta blockade at discharge.
• Antiplatelet medication at discharge.
• Anti- lipid treatment at discharge.
Operative care process domain:
• Use of an internal thoracic (mammary) artery in CABG.
Risk- adjusted operative mortality:
• Risk- adjusted operative mortality for CABG.
Risk- adjusted morbidity, scored any- or- none and consisting of:
• Stroke/ cerebrovascular accident .
• Surgical re- exploration.
• Deep sternal wound infection rate.
• Postoperative renal failure.
• Prolonged intubation (ventilation).
providers to focus on a few selected areas of the process of care with
the inherent risk of neglecting other equally important areas. An important area of controversy is the identication of patients eligible to
receive the measured therapy (the denominator).
It is noteworthy that most of the process variables used in surgery (and for CABG) focus on the medical management of patients
and do not reect the technical component of the procedure (gra
patency, completeness of revascularization). e most recent guidelines from the United States and Europe give clear recommendations
on the details of the process of the operation and it seems reasonable
that at least part of these evidence- based recommendations should
be used as quality variables.
Outcome
Outcomes are the most obvious and intuitive measures of quality.
Since the seminal works of Florence Nightingale and Ernest
Codman,, assessment of direct outcomes has been a staple in
measuring quality in surgery. Mortality is the most important and
used outcome but other measures (length of stay, incidence of complications, readmission rate, patient satisfaction, functional health
e use of outcomes as quality measures has important advantages:patient outcomes are the single most important result of surgical practice, and direct outcome measurement has obvious face
validity and appeal for surgeons and patients. Also, measurement
alone may lead to improvement in outcomes.
e major disadvantage of using outcome measurements is that
detection of outliers is heavily dependent on sample size, such that
statistical estimates for low- volume surgeons and/ or hospitals are
usually underpowered and with wide condence intervals. is
problem is particularly relevant in the current era of reduction of
the overall volume of CABG and increasing decentralization of care.
e adoption of volume cut- os or aggregation of data have been
used to circumvent this limitation, but their methodological validity is not unanimously accepted. Recognizing that focusing solely
on mortality rates for CABG had practical and statistical limitations, the Society of oracic Surgeons created a multidimensional
‘Composite Performance Measure’ for CABG measurement as summarized in Box 15.1.
status, and quality of life) are being increasingly used.
Due to its very low mortality rate, the use of alternative outcome
measures seems very relevant to CABG. Specic CABG compli-
Quality initiatives improvequality
cations usually adopted as outcome quality measures are postoperative stroke, postoperative acute kidney injury, need for surgical
re- exploration, prolonged ventilation, and deep sternal wound infections. Postoperative myocardial infarction and gra patency are
obvious potential candidates to be used for quality assessment, but
they suer from variability in denition and assessment.
Patient- reported outcome measures assess the quality of care
from the patient perspective using surveys administered before or
aer surgery.
e use of outcome measures to evaluate the quality of CABG
has led to many large clinical outcomes registries in NewYork,
Pennsylvania, northern New England, Michigan, and other states
in the United States. On a national level, the Society for oracic
Surgery Database is the largest national registry of cardiac and thoracic outcomes and collects data from 1117 hospitals and 2916 surgeons, nearly 95% of adult programmes in the United States.
It has been repeatedly noted that assessment and reporting of quality
measures can increase the quality of care. One of the best- known
examples is the signicant progressive decline in mortality rate for
CABG in the state of NewYork since the introduction of public
reporting of outcome data. e NewYork State Cardiac Surgery
Reporting System (CSRS) is the longest running and one of the rst
state- wide programmes to publicly report systematic data on cardiac surgery (and CABG in particular). e CSRS started in 1989
and since then, has published annual data on risk- adjusted mortality following CABG by hospital and individual surgeons. Since
the introduction of CSRS, the mortality for CABG in NewYork state
has progressively declined.
Another important example of improvement of cardiac surgery
outcome based on quality initiatives is the Northern New England
Cardiovascular Study Group (NNECVDSG). is interdisciplinary
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network of physicians and administrators founded in 1987 analyses
the outcomes of CABG patients operated in Maine, New Hampshire,
and Vermont. In 1990, the NNECVDSG initiated a regional intervention aimed at reducing CABG mortality. e three major
components of this programme were feedback on outcomes data,
training in quality improvement, and site visits aimed at optimizing
procedural aspects, processes, decision- making, and evaluation of
care. Aer the implementation of these interventions, CABG mortality was signicantly reduced in all patient categories. Following
this landmark eort, the NNECVDSG grew in size and aims and
has published several very important quality analyses on dierent
aspects of CABG.,
A very large randomized trial has shown how the use of continuous quality improvement measures can improve the adoption
of care process in CABG, although the eect was only modest for
the only surgical measure considered (use of the internal thoracic
artery). Although the clinical eect of the quality improvement was
modest, the trial was aimed at showing feasibility and targeted only a
few quality measures. Similar results have been reported at the single
institution level.
With a focus on ‘quality of care data’ using structure, process,
and outcome, feedback and review of these is associated with improved clinical outcomes, lower readmission rates, and improved
eciency of care aer CABG., Of note, in most of these studies,
the strongest association between quality measures and outcomes
was found when all of the quality measures were implemented, supporting an ‘all- or- none’ or ‘bundled measures’ approach to quality
improvement. Finally as another example, the Society of oracic
Surgeons quality programme with the National Database as the
foundation and using validated risk measures and yearly audits,
with quarterly feedback reports and voluntary public reporting
now approaching 70% of adult programmes, the mortality and
morbidity measures in Box 15.1 have shown improved outcomes in
all metrics over the last nearly two decades ranging from a mortality
decrease of 31% to a process compliance increase of discharge antilipid medications of 79% (David Shahian MD, Chair STS Council
on Quality, Research and Patient Safety, Donna McDonald, STS,
and Patricia eurer, MSTCVS, personal communication).
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