Singh, Mandeep

Background— The impact of changing demographics on causes of long-term death after percutaneous coronary intervention (PCI) remains incompletely defined. Methods and Results— We evaluated trends in cause-specific long-term mortality after index PCI performed at a single center from 1991 to 2008. Deaths were ascertained by scheduled prospective surveillance. Cause was determined via telephone interviews, medical records, autopsy reports, and death certificates. Competing-risks analysis of cause-specific mortality was performed using 3 time periods of PCI (1991–1996, 1997–2002, and 2003–2008). Final follow-up was December 31, 2012. A total of 19 077 patients survived index PCI hospitalization, of whom 6988 subsequently died (37%, 4.48 per 100 person-years). Cause was determined in 6857 (98.1%). Across 3 time periods, there was a 33% decline in cardiac deaths at 5 years after PCI (incidence: 9.8%, 7.4%, and 6.6%) but a 57% increase in noncardiac deaths (7.1%, 8.5%, and 11.2%). Only 36.8% of deaths in the recent era were cardiac. Similar trends were observed regardless of age, extent of coronary disease, or PCI indication. After adjustment for baseline variables, there was a 50% temporal decline in cardiac mortality but no change in noncardiac mortality. The decline in cardiac mortality was driven by fewer deaths from myocardial infarction/sudden death ( P <0.001) but not heart failure ( P =0.85). The increase in noncardiac mortality was primarily attributable to cancer and chronic diseases ( P <0.001). Conclusions— This study found a marked temporal switch from predominantly cardiac to predominantly noncardiac causes of death after PCI over 2 decades. The decline in cardiac mortality was independent of changes in baseline clinical characteristics. These findings have implications for patient care and clinical trial design.

Objectives: To determine the prevalence and relationship of frailty and health-related quality of life (HRQOL) among residents of long-term care [nursing homes (NH) and assisted living (AL)] facilities. Methods: Residents of NH and AL facilities in La Crosse County, Wisconsin, were recruited 1/2009-6/2010 and assessed for frailty (gait speed, unintended weight loss, grip strength), comorbidity (Charlson index), and HRQOL [Short Form (SF)-36]. Results: Among 137 participants, 85% were frail. Frail residents were older, had more comorbidities (2.0 vs. 0, p < .001) and lower mean SF-36 Physical Component Score (PCS, 32 vs. 48, p < .001). Following adjustments for age, sex, and comorbidities, compared to nonfrail residents, frail residents had lower SF-36 PCS (mean difference −14.7, 95% CI. −19.3,−10.1, p < .001). Frailty, comorbidity, and HRQOL did not differ between NH and AL facilities. Discussion: Frail residents had lower HRQOL, suggesting that preventing frailty may lead to better HRQOL among residents of long-term care facilities.

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.