Spertus, John A

Background Despite guideline recommendations, a significant number of patients with non– ST elevation myocardial infarction ( NSTEMI ) do not receive dual antiplatelet therapy ( DAPT ) before angiography “pretreatment.” While there may be valid clinical reasons to not pretreat, such as concern for bleeding or multivessel disease warranting coronary artery bypass graft surgery, the degree of variability and factors associated with DAPT pretreatment are unknown. Methods and Results From the multicenter TRIUMPH registry, 1632 NSTEMI patients were not taking DAPT on admission and were included in the study cohort. Among the study patients, only 22% patients received DAPT pretreatment. A multivariable logistic regression model showed that race other than white or black (odds ratio [ OR] 0.41, 95% CI 0.21–0.83), hemoglobin level ( OR 1.18, 95% CI 1.08–1.29), patients’ bleeding risk (assessed with NCDR Cath PCI Bleeding Risk Score) ( OR 0.85, 95% CI 0.74–0.99), and severe left ventricular dysfunction ( OR 0.3, 95% CI 0.13–0.65) were the main predictors of pretreatment with DAPT , whereas likelihood of needing coronary artery bypass graft surgery ( GRACE prediction model) was not ( OR 1.09, 95% CI 0.88–1.35). Median ORs were calculated to assess variability of receiving DAPT pretreatment across sites after adjustment for patient characteristics. Receiving DAPT pretreatment varied substantially across sites (range 0–100%, mean OR 3.94, P <0.0001). Conclusions While deviating from guideline‐recommended DAPT pretreatment in patients with NSTEMI was associated with patient factors (eg, bleeding risk), marked variation was present across sites after accounting for patient‐level characteristics. This suggests that site‐level interventions are needed to improve concordance with current guidelines.

Background— Instruments to assess symptom burden and quality of life among patients with atrial fibrillation (AF) have not been well evaluated in community practice or associated with patient outcomes. Methods and Results— Using data from 10 087 AF patients in the Outcomes Registry for Better Informed Treatment of AF (ORBIT-AF), symptom severity was evaluated using the European Heart Rhythm Association (EHRA) classification system, and quality of life was assessed using the Atrial Fibrillation Effect on Quality-of-Life (AFEQT) questionnaire. The association between AF-related symptoms, quality of life, and outcomes was assessed using Cox regression. The majority of AF patients (61.8%) were symptomatic (EHRA >2) and 16.5% had severe or disabling symptoms (EHRA 3–4). EHRA symptom class was well correlated with the AFEQT score (Spearman correlation coefficient −0.39). Over 1.8 years of follow-up, AF symptoms were associated with a higher risk of hospitalization (adjusted hazard ratio for EHRA ≥2 versus EHRA 1 1.23, 95% confidence interval, 1.15–1.31) and a borderline higher risk of major bleeding. Lower quality of life was associated with a higher risk of hospitalization (adjusted hazard ratio for lowest quartile of AFEQT versus highest 1.49, 95% confidence interval, 1.2–1.84), but not other major adverse events, including death. Conclusions— In a community-based study, most patients with AF were symptomatic and had impaired quality of life. Quality of life measured by the AFEQT correlated closely with symptom severity measured by the EHRA class. AF symptoms and lower quality of life were associated with higher risk of hospitalization but not mortality during follow-up.

Background— After left ventricular assist device (LVAD) placement for advanced heart failure, increased cerebral perfusion should result in improved cognitive function. However, stroke (a well-known LVAD complication) and subclinical cerebral ischemia may result in transient or permanent cognitive decline. We sought to describe the incidence and predictors of cognitive decline after LVAD using a valid, sensitive assessment tool. Methods and Results— Among 4419 patients in the Interagency Registry for Mechanically Assisted Circulatory Support who underwent LVAD implantation between May 2012 and December 2013, cognitive function was assessed in 1173 patients with the Trail Making B Test before LVAD and at 3, 6, and 12 months. The test detects several forms of cognitive impairment, including subclinical stroke. Cognitive decline was defined as a clinically important increase during follow-up using a moderate Cohen d effect size of 0.5×baseline SD (32 s). The cumulative incidence of cognitive decline in the year after LVAD implantation, treating death and transplantation as competing risks, was 29.2%. In adjusted analysis, older age (≥70 versus <50 years; hazard ratio, 2.24; 95% confidence interval 1.46–3.44; P trend <0.001) and destination therapy (hazard ratio, 1.42; 95% confidence interval, 1.05–1.92) were significantly associated with greater risk of cognitive decline. Conclusions— Cognitive decline occurs commonly in patients in the year after LVAD and is associated with older age and destination therapy. These results could have important implications for patient selection and improved communication of risks before LVAD implantation. Additional studies are needed to explore the association between cognitive decline and subsequent stroke, health status, and mortality in patients after LVAD.

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.