Citations

Background— Although older patients frequently undergo percutaneous coronary interventions (PCI), frailty, comorbidity, and quality of life are seldom part of risk prediction approaches. We assessed their incremental prognostic value over and above the risk factors in the Mayo Clinic risk score. Methods and Results— Patients ≥65 years who underwent PCI were assessed for frailty (Fried criteria), comorbidity (Charlson index), and quality of life [SF-36]. Of the 628 discharged [median follow-up of 35.0 months (interquartile range, 22.7 to 42.9)], 78 died and 72 had a myocardial infarction (MI). Three-year mortality was 28% for frail patients, 6% for nonfrail patients. The respective 3-year rates of death or MI were 41% and 17%. After adjustment, frailty [hazard ratio (HR), 4.19 [95% confidence interval (CI), 1.85, 9.51], physical component score of the SF-36 (HR, 1.59; 95% CI, 1.24 to 2.02), and comorbidity, (HR, 1.10; 95% CI, 1.05, 1.16) were associated with mortality. Frailty was associated with mortality/MI (HR, 2.61, 1.52, 4.50). Models with conventional Mayo Clinic risk score had C-statistics of 0.628, 0.573 for mortality and mortality/MI, respectively. Adding frailty, quality of life, and comorbidity, the C-statistic was (0.675, 0.694, 0.671) for mortality and (0.607, 0.587, 0.576) for mortality/MI, respectively. Including frailty, comorbidities and SF-36, conferred a discernible improvement to predict death and death/MI (integrated discrimination improvement, 0.027 and 0.016, and net reclassification improvement of 43% and 18%, respectively). Conclusions— After PCI, frailty, comorbidity and poor quality of life are prevalent and are associated with adverse long-term outcomes. Their inclusion improves the discriminatory ability of the Mayo Clinic risk score derived from the routine cardiovascular risk factors.

Background— Existing models for outcome after percutaneous coronary interventions (PCIs) lack assessment of long-term prognosis. Our goal was to derive 1- and 5-year mortality and mortality/myocardial infarction (MI) risk models for PCI outcomes from simple, easily obtainable clinical and laboratory variables. Methods and Results— Using the Mayo Clinic registry, we analyzed long-term mortality and mortality/MI following PCIs on 9165 unique patients from January 1, 2001, through December 31, 2007. Cox proportional hazards regression was used to model the calculated risk score and major procedural complications. A total of 1243 patients died, and 696 had MI. Separate risk models derived from clinical, procedural, and laboratory characteristics were made for mortality and mortality/MI. Older age, comorbid conditions, low ejection fraction, acute MI, history of smoking, heart failure, hyperlipidemia, 3-vessel disease, procedural failure, ventricular arrhythmia during PCI, and low medication score were predictors of long-term mortality and mortality/MI. Simple integer scores stratified patients into low, moderate, high, and very high risk for subsequent events. Models had adequate goodness of fit, and areas under the receiver operating characteristic curve were 0.786 and 0.728 for mortality and mortality/MI, respectively, indicating good overall discrimination. Bootstrap analysis indicated that the model was not overfit to the available data set. Conclusions— Easily obtainable variables can be combined into a convenient risk scoring system at the time of patient dismissal following PCI to accurately predict long-term mortality and mortality/MI. This model may be useful for providing patients with individualized, evidence-based estimates of long-term risk.

Background— Temporal trends and contemporary data characterizing the impact of patient age on in-hospital outcomes of percutaneous coronary interventions are lacking. We sought to determine the importance of age by assessing the in-hospital mortality of stratified age groups in the National Cardiovascular Data Registry. Methods and Results— In-hospital mortality after percutaneous coronary intervention on 1 410 069 patients was age stratified into 4 groups—group 1 (age <40, n=25 679), group 2 (40 to 59, n=496 204), group 3 (60 to 79, n=732 574), and group 4 (≥80, n=155 612)—admitted from January 1, 2001, to December 31, 2006. Overall in-hospital mortality was 1.22%; in-hospital mortality was 0.60%, 0.59%, 1.26%, and 3.16% in groups 1 to 4, respectively, P <0.0001. Overall temporal improvement per calendar year in the adjusted in-hospital mortality after percutaneous coronary intervention was noted in most groups; however, this finding was significant only in the 2 older age groups, group 3 (odds ratio, 0.94; 95% CI, 0.92 to 0.96) and group 4 (odds ratio, 0.95; 95% CI, 0.92 to 0.97). The absolute mortality reduction was greatest in the most elderly group, those over the age of 80 years. Conclusions— In-hospital mortality after percutaneous coronary intervention has fallen for all age groups over the past 6 years. However, the largest absolute reduction was seen among patients 80 years of age or older.

Background— We sought to validate the recently developed Mayo Clinic Risk Score model for in-hospital mortality after percutaneous coronary intervention using an independent data set. The Mayo Clinic Risk Score has 7 simple clinical and noninvasive variables, available before coronary angiography, for prediction of in-hospital mortality. External validation using an independent data set would support broader applicability of the model. Methods and Results— In-hospital mortality after percutaneous coronary intervention on 309 351 patients from the National Cardiovascular Data Registry admitted from January 1, 2004, to March, 30, 2006, was studied. Using the Mayo Clinic Risk Score equation, we assigned predicted probabilities of death to each patient. The area under the receiver-operating characteristics curve was 0.884, indicating excellent discrimination overall as well as among subgroups, including gender, diabetes mellitus, renal failure, low ejection fraction, different age groups, and multivessel disease. Ninety-seven percent of patients undergoing percutaneous coronary intervention had a Mayo Clinic Risk Score <10, indicating low to intermediate risk. The Mayo Clinic Risk Score model initially slightly underpredicted event rates when applied in National Cardiovascular Data Registry data (observed 1.23% versus predicted 1.10%), but this underprediction was corrected after recalibration. The recalibrated risk score discriminated (c index=0.885) and calibrated well in an National Cardiovascular Data Registry validation data set consisting of procedures performed between April 1, 2006, and March 30, 2007. Conclusions— Seven variables can be combined into a convenient risk scoring system before coronary angiography is performed to predict in-hospital mortality after percutaneous coronary intervention. This model may be useful for providing patients with individualized, evidence-based estimates of procedural risk as part of the informed consent process before percutaneous coronary intervention.

Background— Myonecrosis after percutaneous coronary intervention (PCI) has been correlated with a worse prognosis, but controversy exists about the clinical significance and potential mechanisms for the association. The aim of this study was to evaluate the relative impact of preprocedural and postprocedural cardiac troponin T (cTnT) levels on survival rate after PCI. Methods and Results— We evaluated 5487 patients from the Mayo Clinic registry who required nonemergency PCI, and we examined the relationship between periprocedural cTnT levels, with the 99th percentile cutoff value used for normal (<0.01 ng/mL), and outcomes. The patients were divided into 3 groups: normal preprocedural and postprocedural cTnT levels (no myonecrosis), normal preprocedural but elevated postprocedural cTnT levels (PCI-related myonecrosis), and abnormal preprocedural cTnT. The 30-day death rates were 0.1%, 0.6%, and 2.3%, respectively, in the 3 groups. In a multivariable model, an abnormal pre-PCI cTnT level (hazard ratio 9.66 [2.30–40.57]; P =0.002), and PCI-related myonecrosis (4.71 [1.02–21.83]; P =0.048) were independent predictors of 30-day mortality. Over a median follow-up of 28 months, an abnormal pre-PCI cTnT level (hazard ratio 1.79 [1.35–2.39]; P <0.001) independently predicted death, but the occurrence of PCI-related myonecrosis did not. A postprocedural elevation in creatine kinase MB fraction was not an independent predictor of long-term risk of death (0.912 [0.70–1.19]; P =0.5). Conclusions— A preprocedural cTnT level >0.01 is a powerful independent predictor of prognosis after PCI and is of greater prognostic significance than the postprocedural biomarker levels. PCI-related myonecrosis occurs frequently and predicts short-term but not long-term risk of death.

Background— Current risk models predict in-hospital mortality after either coronary artery bypass graft surgery or percutaneous coronary interventions separately, yet the overlap suggests that the same variables can define the risks of alternative coronary reperfusion therapies. Our goal was to seek a preprocedure risk model that can predict in-hospital mortality after either percutaneous coronary intervention or coronary artery bypass graft surgery. Methods and Results— We tested the ability of the recently validated, integer-based Mayo Clinic Risk Score (MCRS) for percutaneous coronary intervention, which is based solely on preprocedure variables (age, creatinine, ejection fraction, myocardial infarction ≤24 hours, shock, congestive heart failure, and peripheral vascular disease), to predict in-hospital mortality among 370 793 patients in the Society of Thoracic Surgeons database undergoing isolated coronary artery bypass graft surgery from 2004 to 2006. For the Society of Thoracic Surgeons coronary artery bypass graft surgery population studied, the median age was 66 years (quartiles 1 to 3, 57 to 74 years), with 37.2% of patients ≥70 years old. A high prevalence of comorbid conditions, including diabetes mellitus (37.1%), hypertension (80.5%), peripheral vascular disease (15.3%), and renal disease (creatinine ≥1.4 mg/dL; 11.8%), was present. A strong association existed between the MCRS and the observed mortality in the Society of Thoracic Surgeons database. The in-hospital mortality ranged between 0.3% (95% confidence interval 0.3% to 0.4%) with a score of 0 on the MCRS and 33.8% (95% confidence interval 27.3% to 40.3%) with an MCRS score of 20 to 24. The discriminatory ability of the MCRS was moderate, as measured by the area under the receiver operating characteristic curve (C-statistic=0.715 to 0.784 among various subgroups); performance was inferior to the Society of Thoracic Surgeons model for most categories tested. Conclusions— This model, which is based on 7 preprocedure risk variables, may be useful for providing patients with individualized, evidence-based estimates of procedural risk as part of the informed consent process before percutaneous or surgical revascularization.

Background— Little is known about the impact of technological and pharmacological advances on long-term outcome after percutaneous coronary intervention in general clinical practice. Methods and Results— We analyzed in-hospital and long-term outcome of 24 410 percutaneous coronary interventions among 18 575 unique patients who underwent percutaneous coronary intervention at Mayo Clinic over 25 years. The study population was divided into group 1 (n=3708), coronary interventions from 1979 to 1989; group 2 (n=7020), interventions from 1990 to 1996; group 3 (n=10 952), interventions from 1996 to 2003; and group 4 (n=2730), interventions from 2003 to 2004. Despite the fact that patients in groups 3 and 4 were significantly older, sicker, and had greater prevalence of comorbid conditions, heart failure, and previous revascularization than those in groups 1 and 2, procedural success in groups 3 and 4 improved significantly (94%) versus groups 2 (89%) and 1 (78%) ( P <0.001). Significant reduction in in-hospital mortality (groups 4 to 1: 1.8%, 1.7%, 2.6%, 3.0%; P <0.001) and need for emergency bypass surgery (groups 4 to 1: 0.4%, 0.5%, 1.6%, 5%; P <0.001) was noted in groups 3 and 4 compared with groups 1 and 2. Better adherence to currently recommended evidence-based medications for secondary prevention was seen in the recent time periods. After adjustment, significant reduction in follow-up mortality (hazard ratio, 0.81 and 0.74 for groups 3 and 4, respectively); death or myocardial infarction (hazard ratio, 0.80 and 0.75 for groups 3 and 4, respectively); death, myocardial infarction, or revascularization (hazard ratio, 0.76 and 0.58 for groups 3 and 4, respectively) was noted in recent time periods. Conclusions— Despite higher-risk profiles of patients who underwent percutaneous coronary intervention in recent time periods, procedural success as well as in-hospital and long-term outcomes improved significantly over the last 25 years.

Background— Restenosis prediction from published studies is hampered by inadequate sample size and incomplete angiographic follow-up. The prediction of restenosis with the existing variables is poor. The aim of the present study was to include the clinical and angiographic variables commonly associated with angiographic restenosis and develop a prediction model for restenosis from the PRESTO database. Methods and Results— This study included 1312 patients with a single lesion enrolled in the angiographic substudy of the PRESTO trial. We constructed 2 risk scores. The first used preprocedural variables (female gender, vessel size [≤2.5 mm, 2.5 to 3 mm, 3 to 3.5 mm, 3.5 to 4 mm, >4 mm], lesion length >20 mm, diabetes, smoking status, type C lesion, any previous percutaneous coronary intervention [PCI], and unstable angina) derived from previous studies. Estimated restenosis rates and corresponding variability for each possible level of the resultant risk score were obtained via bootstrapping techniques. The area under the receiver-operator characteristic (ROC) curve was 0.63, indicating modest discriminatory ability to predict restenosis. The second approach constructed a multiple logistic regression model considering significant univariate clinical and angiographic predictors of restenosis identified from the PRESTO database (treated diabetes mellitus, nonsmoker, vessel size, lesion length, American College of Cardiology/American Heart Association type C lesion, ostial location, and previous PCI). The area under the ROC curve for this risk score was also 0.63. Conclusions— The preprocedural clinical and angiographic variables from available studies and from the PRESTO trial have only modest predictive ability for restenosis after PCI.

Background— Percutaneous coronary interventions (PCIs) in saphenous vein grafts (SVGs) with thrombus have a high frequency of distal embolization. Acolysis (therapeutic ultrasound) can break up thrombus in vitro in animal models and humans. Whether this is beneficial during percutaneous SVG interventions is unknown. Methods and Results— We performed a trial of coronary ultrasound thrombolysis in which patients with an acute coronary syndrome undergoing PCI in SVGs were randomly assigned to receive acolysis or abciximab. The primary end point was a successful procedure, defined as final luminal diameter stenosis 30% or less with Thrombolysis In Myocardial Infarction grade 3 flow and freedom from major adverse cardiac events (composite of death, Q-wave, and non–Q-wave myocardial infarction [MI], emergency bypass procedure, disabling stroke, and target lesion revascularization). Of 181 enrolled, 92 received acolysis and 89 abciximab. Angiographic procedural success was achieved in 63% of acolysis patients and 82% of abciximab patients ( P =0.008). Incidence of major adverse cardiac events at 30 days was 25% with acolysis and 12% with abciximab ( P =0.036), attributable mainly to a greater frequency of non–Q-wave MI with acolysis (19.6% versus 7.9%, P =0.03). The incidence of Q-wave MI was also higher with acolysis (5.4% versus 2.2%, P =nonsignificant). The primary end point was achieved in 53.8% of acolysis patients and 73.1% of abciximab patients ( P =0.014). Conclusions— Use of therapeutic ultrasound in vein graft lesions in patients with acute coronary syndrome had poor angiographic outcome and increased the incidence of acute ischemic complications.