Spertus, John A.

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 < 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.