Spertus, John A

Background— Measurement of hospital quality has traditionally focused on processes of care and postprocedure outcomes. Appropriateness measures for percutaneous coronary intervention (PCI) assess quality as it relates to patient selection and the decision to perform PCI. The association between patient selection for PCI and processes of care and postprocedural outcomes is unknown. Methods and Results— We included 203 531 patients undergoing nonacute (elective) PCI from 779 hospitals participating in the National Cardiovascular Data Registry (NCDR) CathPCI Registry between July 2009 and April 2011. We examined the association between a hospital's proportion of nonacute PCIs categorized as inappropriate by the 2009 Appropriate Use Criteria (AUC) for Coronary Revascularization and in-hospital mortality, bleeding complications, and use of optimal guideline-directed medical therapy at discharge (ie, aspirin, thienopyridines, and statins). When categorized as hospital tertiles, the range of inappropriate PCI was 0.0% to 8.1% in the lowest tertile, 8.1% to 15.2% in the middle tertile, and 15.2% to 58.6% in the highest tertile. Compared with lowest-tertile hospitals, mortality was not significantly different at middle-tertile (adjusted odds ratio [OR], 0.93; 95% confidence interval [CI], 0.73–1.19) or highest-tertile hospitals (OR, 1.12; 95% CI, 0.88–1.43; P =0.35 for differences between tertiles). Similarly, risk-adjusted bleeding did not vary significantly (middle-tertile OR, 1.13; 95% CI, 1.02–1.16; highest-tertile OR, 1.02; 95% CI, 0.91–1.16; P =0.07 for differences between tertiles) nor did use of optimal medical therapy at discharge (85.3% versus 85.7% versus 85.2%; P =0.58). Conclusions— In a national cohort of nonacute PCIs, a hospital's proportion of inappropriate PCIs was not associated with in-hospital mortality, bleeding, or medical therapy at discharge. This suggests PCI appropriateness measures aspects of hospital PCI quality that are independent of how well the procedure is performed. Therefore, PCI appropriateness and postprocedural outcomes are both important metrics to inform PCI quality.

Background— Clinical trials have shown that statin therapy reduces cardiovascular morbidity and mortality in patients with coronary artery disease (CAD), even among patients with low-density lipoprotein cholesterol levels <100 mg/dL. We sought to determine the extent to which patients with obstructive CAD in routine outpatient care are treated with statins, nonstatins, or no lipid-lowering therapy. Methods and Results— Within the American College of Cardiology's Practice Innovation and Clinical Excellence (PINNACLE) outpatient registry, we examined rates of treatment with statin and nonstatin medications in 38 775 outpatients with obstructive CAD (history of myocardial infarction or coronary revascularization) and without documented contraindications to statin therapy. Among these patients, 30 160 (77.8%) were prescribed statins, 2042 (5.3%) were treated only with nonstatin lipid-lowering medications, and 6573 (17.0%) were untreated. Lack of medical insurance was associated with no statin treatment, and male sex, coexisting hypertension, and a recent coronary revascularization were associated with statin treatment. Among those not on any lipid-lowering therapy, low-density lipoprotein cholesterol levels were available for 51.2% (3365/6573). Among these untreated patients, low-density lipoprotein cholesterol levels were <100 mg/dL in 1794 patients (53.3%) and ≥100 mg/dL in 1571 patients (46.7%). Conclusions— Despite robust clinical trial evidence, a substantial number of patients with obstructive CAD remain untreated with statins. A small proportion were treated with nonstatin therapy, and 1 in 6 patients was simply untreated; half of the untreated patients had low-density lipoprotein cholesterol values <100 mg/dL. These findings illustrate important opportunities to improve lipid management in outpatients with obstructive CAD.

Background— Coronary artery disease (CAD) is the major cause of death in patients with type 2 diabetes mellitus. Although demographic and clinical factors associated with extent of CAD in patients with diabetes mellitus have been described, genetic factors have not. We hypothesized that genetic variation in peroxisome proliferator-activated receptor (PPAR) pathway genes, important in diabetes mellitus and atherosclerosis, would be associated with extent of CAD in patients with diabetes mellitus. Methods and Results— We genotyped 1043 patients (702 white, 175 blacks) from the Bypass Angioplasty Revascularization Investigation 2 Diabetes (BARI 2D) genetic cohort for 3351 variants in 223 PPAR pathway genes using a custom targeted-genotyping array. Angiographic end points were determined by a core laboratory. In whites, a single variant (rs1503298) in TLL1 was significantly ( P =5.5×10 −6 ) associated with extent of CAD, defined as number of lesions with percent diameter stenosis ≥20%, after stringent Bonferroni correction for all 3351 single nucleotide polymorphisms. This association was validated in the diabetic subgroups of 2 independent cohorts, the Translational Research Investigating Underlying Disparities in Acute Myocardial Infarction Patients' Health Status (TRIUMPH) post–myocardial infarction registry and the prospective Family Heart Study (FHS) of individuals at risk for CAD. TLL1 rs1503298 was also significantly associated with extent of severe CAD (≥70% diameter stenosis; P =3.7×10 −2 ) and myocardial jeopardy index ( P =8.7×10 −4 ). In general linear regression modeling, TLL1 rs1503298 explained more variance of extent of CAD than the previously determined clinical factors. Conclusions— We identified a variant in a single PPAR pathway gene, TLL1 , that is associated with the extent of CAD independently of clinical predictors, specifically in patients with type 2 diabetes mellitus and CAD. Clinical Trial Registration— URL: http://www.clinicaltrials.gov . Unique identifier: NCT00006305.

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— Communicating prognosis to enable shared decision-making is strongly endorsed by heart failure (HF) guidelines. Patients are concerned with both their quantity and quality of life (QoL). To facilitate the recognition of patients at high risk for unfavorable future QoL or death, we created a simple prognostic tool to estimate this combined outcome. Methods and Results— We identified factors associated with 6-month mortality or persistently unfavorable QoL, defined by Kansas City Cardiomyopathy Questionnaire (KCCQ) scores <45 at 1 and 24 weeks after hospital discharge, among 1458 patients from the Efficacy of Vasopressin Antagonism in HF Outcome Study with Tolvaptan (EVEREST). Within 24 weeks of discharge, 478 (32.8%) patients had died and 192 (13.2%) patients had serial KCCQ scores <45. After adjusting for 23 predischarge covariates, independent predictors of the combined end point included low admission KCCQ score, high B-type natriuretic peptide, hyponatremia, tachycardia, hypotension, absence of β-blocker therapy, and history of diabetes mellitus and arrhythmia. A simplified predischarge HF score for subsequent death or unfavorable QoL had moderate discrimination ( c -statistic 0.72). Predischarge clinical covariates were substantially different in predicting the QoL end point as compared with traditional death or rehospitalization end points. Conclusions— At the time of hospital discharge, readily available clinical characteristics are associated with HF patients at high risk for persistently unfavorable QoL or death over the next 6 months. Such information can target patients for whom aggressive treatment options (eg, devices or transplantation) and/or end-of-life discussions should be strongly considered before hospital discharge. Clinical Trial Registration— URL: http://www.clinicaltrials.gov . Unique identifier: NCT00071331.

Abstract Aims Hospitalized heart failure (HF) patients are at high risk for death and readmission. We examined the incremental value of data obtained 1 week after HF hospital discharge in predicting mortality and readmission. Methods and results In the Efficacy of Vasopressin Antagonism in Heart Failure Outcome Study with tolvaptan, 1528 hospitalized patients (ejection fraction ≤40%) with a physical examination, laboratories, and health status [Kansas City Cardiomyopathy Questionnaire (KCCQ)] assessments 1 week after discharge were included. The ability to predict 1 year cardiovascular rehospitalization and mortality was assessed with Cox models, c-statistics, and the integrated discrimination improvement (IDI). Not using a beta-blocker, rales, pedal oedema, hyponatraemia, lower creatinine clearance, higher brain natriuretic peptide, and worse health status were independent risk factors for rehospitalization and death. The c-statistic for the base model (history and medications) was 0.657. The model improved with physical examination, laboratory, and KCCQ results, with IDI increases of 4.9, 7.0, and 3.2%, respectively (P &lt; 0.001 each). The combination of all three offered the greatest incremental gain (c-statistic 0.749; IDI increase 10.8%). Conclusion Physical examination, laboratories, and KCCQ assessed 1 week after discharge offer important prognostic information, suggesting that all are critical components of outpatient evaluation after HF hospitalization.

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— 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.