Cholinesterase inhibitors (ChEIs) are a mainstay treatment for individuals with dementia. ChEIs may worsen airflow obstruction because of their pro-cholinergic properties.
The objective of this study was to evaluate the risk of serious pulmonary complications in the elderly with concomitant chronic obstructive pulmonary disease (COPD) and dementia who were receiving ChEIs.
This was a population-based, cohort study conducted between 2003 and 2010 in residents of Ontario, Canada. Subjects were over the age of 66 years and had concomitant dementia and COPD, identified using linked administrative databases. Exposure to ChEIs was determined using a drug benefits database. The primary outcome was an emergency room (ER) visit or hospitalization for COPD. The risk difference at 60 days and the relative risk (RR) for study outcomes were estimated in the propensity score-matched sample.
Of 266,840 individuals with COPD, 45,503 had a concomitant diagnosis of dementia. A total of 7166 unexposed subjects were matched to subjects newly exposed to ChEIs. New users of ChEIs were not at significantly higher risk of ER visits or hospitalizations for COPD (RR 0.90; 95% CI 0.76, 1.07) or COPD exacerbations (RR 1.02; 95% CI 0.91, 1.15). Furthermore, ER visits for any respiratory diagnoses were not increased among new users of ChEIs (RR 1.02; 95% CI 0.87, 1.19) when compared with non-users. Sub-group analyses were consistent with the main analysis.
In a large cohort of elderly individuals with COPD and dementia, new users of ChEIs had a similar risk for adverse pulmonary outcomes as those who were not receiving ChEIs.
Comparing hierarchical modeling with traditional logistic regression analysis among patients hospitalized with acute myocardial infarction: should we be analyzing cardiovascular outcomes data differently?
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.
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.
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.
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.
Comment In: Am Heart J. 2003 Jan;145(1):16-812514649
Critics of "scorecard medicine" often highlight the incompleteness of risk-adjustment methods used when accounting for baseline patient differences. Although socioeconomic status is a highly important determinant of adverse outcome for patients admitted to the hospital with acute myocardial infarction, it has not been used in most risk-adjustment models for cardiovascular report cards.
To determine the incremental impact of socioeconomic status adjustments on age, sex, and illness severity for hospital-specific 30-day mortality rates after acute myocardial infarction.
The authors compared the absolute and relative hospital-specific 30-day acute myocardial infarction mortality rates in 169 hospitals throughout Ontario between April 1, 1994 and March 31, 1997. Patient socioeconomic status was characterized by median neighborhood income using postal codes and 1996 Canadian census data. They examined two risk-adjustment models: the first adjusted for age, sex, and illness severity (standard), whereas the second adjusted for age, sex, illness severity, and median neighborhood income level (socioeconomic status).
There was an extremely strong correlation between 'standard' and 'socioeconomic status' risk-adjusted mortality rates (r = 0.99). Absolute differences in 30-day risk-adjusted mortality rates between the socioeconomic status and standard risk-adjustment models were small (median, 0.1%; 25th-75th percentile, 0.1-0.2). The agreement in the quintile rankings of hospitals between the socioeconomic status and standard risk-adjustment models was high (weighted kappa = 0.93).
Despite its importance as a determinant of patient outcomes, the effect of socioeconomic status on hospital-specific mortality rates over and above standard risk-adjustment methods for acute myocardial infarction hospital profiling in Ontario was negligible.
Persons with cystic fibrosis (CF) who tend to be hospitalized have poorer overall survival and quality of life. Whether differences exist in hospitalization rates between males and females with CF is unknown. The objective was to assess sex-specific differences in hospitalization rates after adjusting for clinically important factors within a universal health care system.
A provincial-based longitudinal study using national CF registry data linked to health administrative databases examined differences in annual hospitalization rates estimated by Poisson regression using generalized estimating equations with adjustment for markers of CF disease severity.
Among those aged 7 to 19 years, the RR of respiratory-related annual hospitalizations among females vs. males was 1.38 (95% CI 1.11-1.73). Among those over 19 years, the corresponding RR was 1.30 (95% CI 1.06-1.59).
Females affected by CF are at a higher risk of respiratory-related hospitalization, which may extend beyond classic clinical measures of disease severity.
Hospital report cards usually are based on administrative discharge abstracts. However, cardiac severity and comorbidities generally are under-reported in administrative data.
We sought to determine how undercoding of cardiac severity and comorbidities affects the determination that some hospitals are high-mortality outliers.
Simulations using retrospective data on 18,795 patients admitted with an acute myocardial infarction (AMI) to 109 acute care hospitals in Ontario.
Change in the number of hospitals that remained high-mortality outliers after adjusting for potentially increased prevalence of as many as 9 separate measures of cardiac severity and comorbid conditions, individually or together.
For most measures of cardiac severity and comorbidities, increasing the prevalence of each factor to the highest observed hospital-specific prevalence seldom altered the status of high-mortality outlier hospitals. Increases in the prevalence of cardiogenic shock or acute renal failure to even the median level led to reclassification of up to 4 of the 12 high-mortality outlier hospitals to nonoutlier status. Most high-mortality outlier hospitals were reclassified if the maximum prevalence was imputed for these 2 factors. Simultaneously increasing the prevalence of all comorbidities to the median level typically converted the status of about half the outlier hospitals. Not until the prevalence of all measures of cardiac severity and comorbidities were simultaneously increased to the maximum observed hospital-specific prevalence, did all hospitals initially classified as high-mortality outliers revert to nonoutlier status.
Undercoding of severity and comorbidities in administrative data in itself is very unlikely to account for the outlier status of most hospitals. However, some potential for misclassification of individual institutions exists if influential factors are variably coded.
Survival after acute myocardial infarction (AMI) varies with socioeconomic status. It is unknown whether these differences can be attributed, in part, to variations in the prevalence of atherogenic risk factors preceding the index AMI event.
To examine how cardiovascular risk factors varied according to person-level indicators of income and education among a cohort of younger patients (younger than 65 years of age) hospitalized with AMI in Ontario.
The Socio-Economic and Acute Myocardial Infarction study (SESAMI) prospectively assembled a cohort of 3335 patients hospitalized with AMI who consented to participate (75% consent rate) from 53 of 57 large-volume institutions (100 AMI cases per year or more) throughout Ontario between December 1, 1999, and June 1, 2002. Given the known challenges inherent in characterizing the socioeconomic status in elderly patients and the ubiquity of atherosclerosis in elderly persons, the study focused on 1635 nonelderly participants. The relationship between income or education and cardiovascular risk factors, after adjustment for age, sex, ethnoracial factors and geography (urban-rural status) was examined.
The prevalence of diabetes, hypertension, smoking and pre-existing heart disease was higher among poorer, less educated patients, as were the total number of cardiovascular risk factors. After adjusting for baseline factors, both income (adjusted OR 0.50, 95% CI 0.31 to 0.82, P=0.006) and education (adjusted OR 0.52, 95% CI 0.31 to 0.87, P=0.01) were independently associated with cardiovascular risk factors or pre-existing heart disease. There were no significant interactions between income, education and baseline cardiovascular risk.
Outcome differences across socioeconomic strata following AMI may reflect major income- and education-related differences in atherogenic risk profile.
Stroke Outcomes Research Centre, Stroke Outcome Research Canada Working Group, Department of Medicine, St. Michael's Hospital, University of Toronto, 55 Queen St. E, Toronto, Ontario, Canada. email@example.com
A predictive model of stroke mortality may be useful for clinicians to improve communication with and care of hospitalized patients. Our aim was to identify predictors of mortality and to develop and validate a risk score model using information available at hospital presentation.
This retrospective study included 12 262 community-based patients presenting with an acute ischemic stroke at multiple hospitals in Ontario, Canada, between 2003 and 2008 who had been identified from the Registry of the Canadian Stroke Network (8223 patients in the derivation cohort, 4039 in the internal validation cohort) and the Ontario Stroke Audit (3720 for the external validation cohort). The mortality rates for the derivation and internal validation cohorts were 12.2% and 12.6%, respectively, at 30 days and 22.5% and 22.9% at 1 year. Multivariable predictors of 30-day and 1-year mortality included older age, male sex, severe stroke, nonlacunar stroke subtype, glucose =7.5 mmol/L (135 mg/dL), history of atrial fibrillation, coronary artery disease, congestive heart failure, cancer, dementia, kidney disease on dialysis, and dependency before the stroke. A risk score index stratified the risk of death and identified low- and high- risk individuals. The c statistic was 0.850 for 30-day mortality and 0.823 for 1-year mortality for the derivation cohort, 0.851 for the 30-day model and 0.840 for the 1-year mortality model in the internal validation set, and 0.790 for the 30-day model and 0.782 for the 1-year model in the external validation set.
Among patients with ischemic stroke, factors identifiable within hours of hospital presentation predicted mortality risk at 30 days and 1 year. The predictive score may assist clinicians in estimating stroke mortality risk and policymakers in providing a quantitative tool to compare facilities.
Comment In: Circulation. 2011 Feb 22;123(7):712-321300950
Little information is available on recent population-based trends in the outcomes of patients who have had an acute myocardial infarction (AMI) in Canada.
Data were analyzed from the Discharge Abstract Database and Hospital Morbidity Database of the Canadian Institute for Health Information. All new cases of AMI in Canada between fiscal 1997/98 and fiscal 1999/2000 of patients at least 20 years old were examined. Data were also analyzed from these databases for hospital readmissions for a second AMI, angina and congestive heart failure (CHF).
There were 139,523 new AMI cases. The overall crude in-hospital AMI mortality rate in Canada was 12.3%. In-hospital mortality rate after an AMI was worse for women than for men in Canada (16.7% and 9.9%, respectively). The age- and sex-standardized in-hospital mortality rate varied from a low of 10.5% (95% CI 8.4% to 12.6%) in Prince Edward Island to a high of 13.1% (95% CI 12.8% to 13.5%) in Quebec. Among AMI survivors, 12.5% were readmitted within one year for angina, 7.7% for a second AMI and 7.5% for CHF. There were wide interregional differences in age- and sex-standardized mortality rates and one-year readmission rates.
AMI is associated with a substantial acute mortality rate in Canada, especially in the elderly and female patients. Identifying the causes of interregional differences in patient outcomes should be a priority for future research.
Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada; Division of Emergency Medicine, Department of Medicine, University of Toronto, Toronto, Ontario, Canada; Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada. Electronic address: firstname.lastname@example.org.
We aimed to describe the demographics, care, and outcomes of patients with atrial fibrillation in the emergency department (ED), as well as temporal changes over time.
In this retrospective cohort study, we used a province-wide database to identify all adult patients who were treated in a nonpediatric ED in the province of Ontario with a primary diagnosis of atrial fibrillation, April 2002 to March 2010. We determined the frequency and rate of ED visits and assessed patient demographics, ED care, and outcomes, both overall and by year.
During the 8-year study period, 113,786 patients made 143,003 ED visits for atrial fibrillation, accounting for 0.5% of all ED visits. The annual number of ED visits increased from 15,931 to 20,168 (29.4%; 95% confidence interval [CI] 28.7% to 30.1%) between 2002 and 2010, whereas the crude rate increased from 172 per 100,000 to 195 per 100,000 persons. Median age was 72.0 years (Interquartile range 61.0 to 80.0 years) and 50.8% were women, which did not change significantly during the study period. The percentage of index ED visits with a physician billing for cardioversion increased from 6.3% (95% CI 5.9% to 6.7%) to 11.8% (95% CI 11.3% to 12.3%). Although the percentage of patients with a CHADS2 score greater than or equal to 2 increased from 49.3% (95% CI 48.4% to 50.2%) to 53.6% (95% CI 52.9% to 54.4%) and high-acuity ED triage scores increased from 41.1% (95% CI 40.2% to 42.0%) to 62.5% (95% CI 61.7% to 63.2%), hospital admissions decreased from 48.1% (95% CI 47.3% to 49.0%) to 38.4% (95% CI 37.6% to 39.2%). Thirty-day mortality was 3.3% (95% CI 3.2% to 3.4%) and showed a slight downward trend during the study period (P=.05), whereas subsequent hospitalizations within 30 days for atrial fibrillation or stroke (2.8%; 95% CI 2.7% to 2.9%) and repeated ED visits (7.3%; 95% CI 7.1% to 7.4%) remained unchanged.
The number of ED visits for atrial fibrillation increased markedly during an 8-year period. Although it appears that slightly higher-risk patients are being treated in the province's EDs, fewer patients are being admitted to the hospital, and mortality rates have not increased.
Comment In: Ann Emerg Med. 2013 Dec;62(6):578-923948746
An abdominal aortic aneurysm (AAA) that is identified when the abdomen is imaged for some other reason is known as an incidental AAA. No population-based studies have assessed the management of incidental AAAs. The objective of this study was to measure the completeness of radiographic monitoring of incidental AAAs by means of a population-based analysis.
We linked a cohort of patients with incidental AAA (defined as a previously unidentified aortic enlargement exceeding 30 mm in diameter found in an imaging study performed for another reason) to various population-based databases. We followed the patients to elective repair or rupture of the aneurysm, death or 31 Mar. 2009. We used evidence-based monitoring guidelines to calculate the proportion of observation time during which each incidental AAA was incompletely monitored. We used negative binomial regression to determine the association of patient-related factors with this outcome.
For the period between January 1996 and September 2008, we identified 191 patients with incidental AAA (mean diameter 37.6 mm, 95% confidence interval [CI] 36.6-38.6 mm; median follow-up 4.4 [range 0.6-12.7] years). Fifty-six of these patients (29.3%) had no radiographic monitoring of the aneurysm. Overall, patients spent one-fifth of their time with incomplete monitoring of the AAA (median 19.4%, interquartile range 0.3%-44.0%). Factors independently associated with incomplete monitoring included older age (relative rate [change in proportion of time with incomplete monitoring] [RR] 1.27, 95% CI 1.10-1.47, per decade), larger size (RR 1.65, 95% CI 1.38-2.01, per 10-mm increase) and detection of the aneurysm while the patient was in hospital or the emergency department (RR 1.34, 95% CI 1.00-1.79). Comorbidities were not associated with monitoring.
Radiographic monitoring of incidental AAAs was incomplete, and almost one-third of patients underwent no monitoring at all. Incomplete monitoring did not appear to be related to patients' comorbidity.