Search

Background: Although the burden of aortic stenosis (AS) on our health care system is expected to rise, little is known regarding its epidemiology at the population level. Our primary objective was to evaluate trends in AS hospitalization, treatment and outcomes., Methods: We performed a population-based observational study including 37,970 patients newly hospitalized with AS from 2004 and 2013 in Ontario, Canada. We calculated age- and sex-standardized rate of AS hospitalization through direct standardization. The independent association between year of the hospitalization, and 30-day and 1-year mortality rate was evaluated using logistic regression models to account for temporal changes in patient characteristics., Results: The overall age- and sex-standardized AS hospitalization rate increased slightly from 36 per 100,000 in 2004 to 39 per 100,000 in 2013. A substantial increase was seen in patients ≥85years, where hospitalization rates increased 29% from 400 to 516 per 100,000 from 2004 to 2013 (P<.001). In this study period, 36.2% of patients received aortic valve interventions within 30days of hospitalization. Among treated patients, an improving mortality trend was observed in which the adjusted odds ratio (OR) was significantly lower in 2013 as compared to 2004 (OR 0.55 for 30-day mortality, 0.74 for 1-year morality). In contrast, no significant temporal change in mortality was seen among patients without aortic valve intervention., Conclusion: AS hospitalizations in the elderly increased significantly beyond that was expected from population growth. Many AS patients did not receive aortic valve intervention after hospitalization. Mortality among the treated patients improved significantly over time., (Copyright © 2018. Published by Elsevier Inc.)

Background: An understanding of the life expectancy of patients with heart failure (HF) may assist in difficult treatment decisions such as placement of an implantable cardioverter-defibrillator or initiation of end-of-life care. However, previous studies have focused on predicting shorter-term mortality and limited data currently exist to predict expected survival among hospitalized patients with HF., Methods: We studied 9943 patients who were newly hospitalized with HF between 1999 and 2001 in Ontario, Canada. Median survival was calculated using survival analysis and stratified by baseline characteristics and the EFFECT HF risk score. These analyses were repeated for the 1467 patients who had left ventricular ejection fraction of < or = 30%., Results: The average age of our HF cohort was 75.8 years and 50.4% of the patients were female. After a median follow-up of 6 years, hospitalized patients with HF had a 5-year mortality rate of 68.7% and a median survival of 2.4 years. Mortality varied substantially across risk groups such that median survival was only 8 months for patients in the high-risk group and only 3 months in the very high risk group. Similarly, among patients with depressed left ventricular ejection fraction, median survival was only 6 and 3 months in the high- and very high risk groups, respectively., Conclusions: Prognostic estimations using median survival may improve the ability of physicians to identify subgroups of patients with HF who have limited life expectancy. This information may assist in communicating prognostic information and guiding difficult treatment decisions among hospitalized patients with HF.

Background: Troponin level elevations are common in patients with acute decompensated heart failure (ADHF), yet their prognostic value above and beyond traditional predictors of outcomes in heart failure is uncertain., Methods: In the EFFECT study, we determined the association between cardiac troponin I and all-cause mortality in 2025 patients hospitalized for heart failure in Ontario, Canada, between April 1, 1999, and March 31, 2001., Results: Cardiac troponin I levels >0.5 microg/L (median 1.7 microg/L, interquartile range 0.9-4.8 microg/L) occurred in 699 (34.5%) patients and was an independent predictor of mortality (adjusted hazard ratio 1.49, 95% CI 1.25-1.77, P < .001). Furthermore, we observed a dose-response relationship between cardiac troponin I and mortality that persisted after adjustment for potential confounding factors (adjusted hazard ratio 1.10 per 1 microg/L increase, 95% CI 1.05-1.15, P < .001). The association between cardiac troponin I and mortality was similar for patients with and without other features of acute ischemia on presentation (P > .05 for interaction)., Conclusions: In patients hospitalized for ADHF who had cardiac troponin levels measured during the course of clinical practice, cardiac troponin I was an independent predictor of all-cause mortality. Cardiac troponin testing is easily accessible, has predictive value above and beyond traditional clinical predictors of mortality, and may help guide medical decision making in patients with ADHF.

Background: The benefits of statins for the secondary prevention of coronary heart disease are well established. Previous research indicates that patients at the greatest risk of cardiovascular events are the least likely to receive statins. We explored the potential reduction in mortality at the population level that could result from improving statin prescribing among patients least likely to be prescribed a statin after acute myocardial infarction (AMI)., Methods: Simulation analysis of detailed clinical data for a population-based sample of 7285 AMI survivors discharged from 102 hospitals between April 1, 1999, and March 31, 2001 in Ontario, Canada, was done. Using estimates obtained from randomized controlled trials, we estimated the reduction in 3-year all-cause mortality associated with improved statin prescribing at hospital discharge., Results: Overall, 35.6% of patients received a statin prescription at hospital discharge. We estimate that increasing statin prescribing among patients least likely to receive them (ie, the lowest quintile of propensity to receive a prescription at discharge) from the current rate of 7.8% to the rate among all patients (35.6%) could decrease AMI mortality by 83 deaths in Ontario per year (2.1% of all post-AMI deaths within 3 years of discharge). Increasing statin prescribing to 70% among all patients with AMI could avert 312 deaths per year in Ontario. Factoring in low rates of adherence to statin therapy would reduce these estimates to 33 and 126, respectively., Conclusions: Modest increases in statin prescribing for patients least likely to receive one could decrease post-AMI mortality at the population level.

Background: Cardiac risk-adjustment indices for acute coronary syndromes have important clinical and research applications, especially if proven to be valid and robust across heterogeneous socioeconomically diverse populations. The objective of this study was to validate the Global Registry of Acute Coronary Events (GRACE) risk-adjustment index for 6-month all-cause mortality across socioeconomic strata., Methods: The study cohort consisted of patients who were enrolled in the SESAMI study and discharged alive from the hospital between December 1, 1999, and February 28, 2003. Socioeconomic information was obtained through self-report. Hospital chart abstraction was used to ascertain clinical detail required for the derivation of the GRACE risk index. Six-month mortality rates were obtained through data linkage using encrypted health card numbers. The accuracy (c-statistic) and calibration (Hosmer-Lemeshow) characteristics of the GRACE risk index were generated using logistic regression across income and education strata., Results: Predicted and observed mortality rates were significantly higher among patients of lower incomes and education (ie, observed 6-month mortality: 5.1% vs 1.8% among low income vs high income patients, respectively, P < .0001; 4.6% vs 2.9% among low-educated vs highly educated patients, respectively, P = .02). The predicted 6-month mortality as derived using GRACE closely mirrored observed mortality rates with strong accuracy and precision (c-statistic = 0.80 for the overall cohort and within each income and education strata; Hosmer-Lemeshow goodness-of-fit test was not significant within each income and education strata)., Conclusion: The GRACE risk score for 6-month all-cause mortality is an accurate, well-calibrated, and robust predictor across socioeconomic strata and can be used as a valid risk-adjustment index when examining socioeconomic-mortality differences after acute MI.

Background: Clinical guidelines recommend lipid testing in all hospitalized acute myocardial infarction (AMI) patients. Inhospital lipid testing has also been proposed as a quality indicator for AMI care, but little is known about its use or importance. We sought to examine rates of inhospital lipid testing and its association with statin therapy at hospital discharge., Methods: We performed an analysis using medical chart abstraction data that included demographic and comprehensive clinical information for patients hospitalized in Ontario, Canada, with an AMI from 1999 to 2001., Results: Among 11,468 patients, inhospital lipid testing was performed in 6,019 (52.5%) patients and in 4,169 (36.4%) patients within 24 hours of admission. Patients who had lipid testing were significantly more likely to be discharged on statin therapy compared with patients not tested (41.4% vs 23.0%, P < .001). In addition, inhospital lipid testing was strongly associated (odds ratio 3.61, 95% CI 3.15-4.14) with statin therapy prescription at hospital discharge after adjusting for other clinical, physician, and hospital factors., Conclusions: Despite endorsements from practice guidelines, less than half of all admitted AMI patients received lipid testing within 24 hours of hospital admission. Because inhospital lipid testing was strongly associated with the initiation of statin therapy at discharge, many opportunities to initiate statin therapy were lost. Efforts to increase the use of lipid testing in hospitalized AMI patients may translate into higher rates of lipid-lowering therapy and improved patient outcomes.

Background: Hospital report cards for outcomes following acute myocardial infarction (AMI) are being produced with increasing frequency. Implicit in the statistical methods used is the fact that hospitals are being compared with an average hospital. Prior research has demonstrated that institutional characteristics such as a high annual volume of AMI patients and academic status are associated with improved outcomes. This raises the important issue of what is an appropriate benchmark against which hospitals should be compared. The objective of the current study was to determine whether the number of hospitals identified as mortality outliers depended upon the benchmark against which hospitals are compared., Methods: We examined all patients discharged with a diagnosis of AMI from 163 Ontario hospitals between April 1, 2000, and March 30, 2001. Logistic regression models that incorporated random provider effects were used to identify hospitals with a mortality rate significantly higher than average. The initial model included only patient characteristics, whereas additional models incorporated both patient and hospital characteristics., Results: After adjusting for patient characteristics only, 3 hospitals had significantly higher mortality compared to an average-mortality hospital, while 4 hospitals had significantly lower mortality than an average-mortality hospital. However, after further adjusting for peer group, only 1 hospital was identified as having significantly lower mortality than an average-mortality institution in its peer group., Conclusions: The use of peer-group-defined rather than overall benchmarks has a substantial impact on the identification of mortality outliers. The choice of the appropriate benchmark is related to the underlying purpose of the comparison.

Background: Data in health research are frequently structured hierarchically. For example, data may consist of patients treated by physicians who in turn practice in hospitals. Traditional statistical techniques ignore the possible correlation of outcomes within a given practice or hospital. Furthermore, imputing characteristics measured at higher levels of the hierarchy to the patient-level artificially inflates the amount of available information on the effect of higher-level characteristics on outcomes., Methods: Conventional logistic regression models and multilevel logistic regression models were fit to a cross-sectional cohort of patients hospitalized with a diagnosis of acute myocardial infarction. The statistical significance of the effect of patient, physician, and hospital characteristics on patient outcomes was compared between the 2 modeling strategies., Results: The 2 analytic strategies agreed well on the effect of patient characteristics on outcomes. According to the traditional analysis, teaching status was statistically significantly associated with 5 of the 9 outcomes, whereas the multilevel models did not find a statistically significant association between teaching status and any patient outcomes. Similarly, the traditional and multilevel models disagreed on the statistical significance of the effect of being treated at a revascularization hospital and 3 patient outcomes., Conclusions: In comparing the resultant models, we see that false inferences can be drawn by ignoring the structure of the data. Conventional logistic regression tended to increase the statistical significance for the effects of variables measured at the hospital-level compared to the level of significance indicated by the multilevel model.