Spertus, John A.

Background— Post-percutaneous coronary intervention (PCI) bleeding complications are an important quality metric. We sought to characterize site-level variation in post-PCI bleeding and explore the influence of patient and procedural factors on hospital bleeding performance. Methods and Results— Hospital-level bleeding performance was compared pre- and postadjustment using the newly revised CathPCI Registry ® bleeding risk model (c-index, 0.77) among 1292 National Cardiovascular Data Registry ® hospitals performing >50 PCIs from 7/2009 to 9/2012 (n=1 984 998 procedures). Using random effects models, outlier sites were identified based on 95% confidence intervals around the hospital’s random intercept. Bleeding 72 hours post-PCI was defined as: arterial access site, retroperitoneal, gastrointestinal, or genitourinary bleeding; intracranial hemorrhage; cardiac tamponade; nonbypass surgery–related blood transfusion with preprocedure hemoglobin ≥8 g/dL; or absolute decrease in hemoglobin value ≥3 g/dL with preprocedure hemoglobin ≤16 g/dL. Overall, the median unadjusted post-PCI bleeding rate was 5.2% and varied among hospitals from 2.6% to 10.4% (5th, 95th percentiles). Center-level bleeding variation persisted after case-mix adjustment (2.8%–9.5%; 5th, 95th percentiles). Although hospitals’ observed and risk-adjusted bleeding ranks were correlated (Spearman ρ: 0.88), individual rankings shifted after risk-adjustment (median Δ rank order: ±91.5; interquartile range: 37.0, 185.5). Outlier classification changed postadjustment for 29.3%, 16.1%, and 26.5% of low-, non-, and high-outlier sites, respectively. Hospital use of bleeding avoidance strategies (bivalirudin, radial access, or vascular closure device) was associated with risk-adjusted bleeding rates. Conclusions— Despite adjustment for patient case-mix, there is wide variation in rates of hospital PCI-related bleeding in the United States. Opportunities may exist for best performers to share practices with other sites.

Background Assessing hospital quality in the performance of carotid endarterectomy ( CEA ) requires appropriate risk adjustment across hospitals with varying case mixes. The aim of this study was to develop and validate a prediction model to assess the risk of in‐hospital stroke or death after CEA that could aid in the assessment of hospital quality. Methods and Results Patients from National Cardiovascular Data Registry (NCDR)'s Carotid Artery Revascularization and Endarterectomy (CARE) Registry undergoing CEA without acute evolving stroke from 2005 to 2013 were included. In‐hospital stroke or death was modeled using hierarchical logistic regression with 20 candidate variables and accounting for hospital‐level clustering. Internal validation was achieved with bootstrapping; model discrimination and calibration were assessed. A total of 213 (1.7%) primary end point events occurred during 12 889 procedures. Independent predictors of stroke or death included age, prior peripheral artery disease, diabetes mellitus, prior coronary artery disease, having a symptomatic carotid lesion, having a contralateral carotid occlusion, or having New York Heart Association Class III or IV heart failure. The model was well calibrated and demonstrated moderate discriminative ability (c‐statistic 0.65). The NCDR CEA score was then developed to support simple, prospective risk quantification in the clinical setting. Conclusions The NCDR CEA score, comprising 7 clinical variables, predicts in‐hospital stroke or death after CEA . This model can be used to estimate hospital risk‐adjusted outcomes for CEA and to assist with the assessment of hospital quality.

Background Heart failure ( HF ) patients experience impaired functional status, diminished quality of life, high utilization of healthcare resources, and poor survival. Yet, the identification of patient‐centered factors that influence prognosis is lacking. Methods and Results We determined the association of 2 measures of self‐rated health with healthcare utilization and skilled nursing facility ( SNF ) admission in a community cohort of 417 HF patients prospectively enrolled between October 2007 and December 2010 from Olmsted County, MN . Patients completed a 12‐item Short Form Health Survey ( SF ‐12). Low self‐reported physical functioning was defined as a score ≤25 on the SF ‐12 physical component. The first question of the SF ‐12 was used as a measure of self‐rated general health. After 2 years, 1033 hospitalizations, 1407 emergency department ( ED ) visits, and 19,780 outpatient office visits were observed; 87 patients were admitted to a SNF . After adjustment for confounding factors, an increased risk of hospitalizations (1.52 [1.17 to 1.99]) and ED visits (1.48 [1.04 to 2.11]) was observed for those with low versus moderate‐high self‐reported physical functioning. Patients with poor and fair self‐rated general health also experienced an increased risk of hospitalizations (poor: 1.73 [1.29 to 2.32]; fair: 1.46 [1.14 to 1.87]) and ED visits (poor: 1.73 [1.16 to 2.56]; fair: 1.48 [1.13 to 1.93]) compared with good‐excellent self‐rated general health. No association between self‐reported physical functioning or self‐rated general health with outpatient visits and SNF admission was observed. Conclusion In community HF patients, self‐reported measures of physical functioning predict hospitalizations and ED visits, indicating that these patient‐reported measures may be useful in risk stratification and management in HF .

Background— Physical health status measures have been shown to predict death in heart failure (HF); however, few studies found significant associations after adjustment for confounders, and most were not representative of all HF patients. Methods and Results— HF patients from southeastern MN were prospectively enrolled between 10/2007 and 12/2010, completed a 12-item Short Form Health Survey (SF-12) and a 6-minute walk, and were followed through 2011 for death from any cause. Scores ≤25 on the SF-12 physical component indicated low self-reported physical functioning, and the first question of the SF-12 measured self-rated general health. Low functional exercise capacity was defined as ≤300 m walked during a 6-minute walk. Over a mean follow-up of 2.3 years, 86 deaths occurred among the 352 participants. A 1.6-fold (95% confidence interval, 1.0–2.7) and 1.8-fold (95% confidence interval, 1.1–2.9) increased risk of death was observed among patients with low self-reported physical functioning and low functional exercise capacity, respectively. Poor self-rated general health corresponded to a 2.7-fold (95% confidence interval, 1.5–4.9) increased risk of death compared with good to excellent general health. All measures equally discriminated between who would die and who would survive (C-statistics: 0.729, 0.750, and 0.740 for self-reported physical functioning, self-rated general health, and functional exercise capacity, respectively). Conclusions— Three physical health status measures, captured by the SF-12 and a 6-minute walk, equally predict death among community HF patients. Therefore, the first question of the SF-12, which is the least burdensome to administer, may be sufficient to identify HF patients at greatest risk of death.

Background— The increasing prevalence of heart failure (HF) and high associated costs have spurred investigation of factors leading to adverse outcomes in patients with HF. Studies to date report inconsistent evidence on the link between depression and outcomes with only limited data on emergency department and outpatient visits. Methods and Results— Olmsted, Dodge, and Fillmore county, Minnesota residents with HF were prospectively recruited between October 2007 and December 2010 and completed a 1-time 9-item Patient Health Questionnaire for depression categorized as: none to minimal (Patient Health Questionnaire score, 0–4), mild (5–9), or moderate to severe (≥10). Andersen-Gill models were used to determine whether depression predicted hospitalizations and emergency department visits, whereas negative binomial regression models explored the association of depression with outpatient visits. Cox proportional hazards regression characterized the relationship between depression and all-cause mortality. Among 402 patients with HF (mean age, 73±13 years; 58% men), 15% had moderate to severe depression, 26% mild, and 59% none to minimal depression. During a mean follow-up of 1.6 years, 781 hospitalizations, 1000 emergency department visits, 15 515 outpatient visits, and 74 deaths occurred. After adjustment, moderate to severe depression was associated with nearly a 2-fold increased risk of hospitalization (hazard ratio, 1.79; 95% confidence interval, 1.30–2.47) and emergency department visits (hazard ratio, 1.83; 95% confidence interval, 1.34–2.50), a modest increase in outpatient visits (rate ratio, 1.20; 95% confidence interval, 1.00–1.45), and a 4-fold increase in all-cause mortality (hazard ratio, 4.06; 95% confidence interval, 2.35–7.01). Conclusions— In this prospective cohort study, depression independently predicted an increase in the use of healthcare resources and mortality. Greater recognition and management of depression in HF may optimize clinical outcomes and resource utilization.

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.