Introduction: Severe acute renal failure (sARF) is associated with considerable morbidity, mortality and use of healthcare resources; however, its precise epidemiology and long-term outcomes have not been well described in a non-specified population. Methods: Population-based surveillance was conducted among all adult residents of the Calgary Health Region (population 1 million) admitted to multidisciplinary and cardiovascular surgical intensive care units between May 1 1999 and April 30 2002. Clinical records were reviewed and outcome at 1 year was assessed. Results: sARF occurred in 240 patients (11.0 per 100,000 population/year). Rates were highest in males and older patients (≥65 years of age). Risk factors for development of sARF included previous heart disease, stroke, pulmonary disease, diabetes mellitus, cancer, connective tissue disease, chronic renal dysfunction, and alcoholism. The annual mortality rate was 7.3 per 100,000 population with rates highest in males and those ≥65 years. The 28-day, 90-day, and 1-year case-fatality rates were 51%, 60%, and 64%, respectively. Increased Charlson co-morbidity index, presence of liver disease, higher APACHE II score, septic shock, and need for continuous renal replacement therapy were independently associated with death at 1 year. Renal recovery occurred in 78% (68/87) of survivors at 1 year. Conclusion: sARF is common and males, older patients, and those with underlying medical conditions are at greatest risk. Although the majority of patients with sARF will die, most survivors will become independent from renal replacement therapy within a year.

Background: The risk of stroke is elevated in the first 48 hours after TIA. Previous prognostic models suggest that diabetes mellitus, age, and clinical symptomatology predict stroke. The authors evaluated the magnitude of risk of stroke and predictors of stroke after TIA in an entire population over time. Methods: Administrative data from four different databases were used to define TIA and stroke for the entire province of Alberta for the fiscal year (April 1999–March 2000). The age-adjusted incidence of TIA was estimated using direct standardization to the 1996 Canadian population. The risk of stroke after a diagnosis of TIA in an Alberta emergency room was defined using a Kaplan-Meier survival function. Cox proportional hazards modeling was used to develop adjusted risk estimates. Risk assessment began 24 hours after presentation and therefore the risk of stroke in the first few hours after TIA is not captured by our approach. Results: TIA was reported among 2,285 patients for an emergency room diagnosed, age-adjusted incidence of 68.2 per 100,000 population (95% CI 65.3 to 70.9). The risk of stroke after TIA was 9.5% (95% CI 8.3 to 10.7) at 90 days and 14.5% (95% CI 12.8 to 16.2) at 1 year. The risk of combined stroke, myocardial infarction, or death was 21.8% (95% CI 20.0 to 23.6) at 1 year. Hypertension, diabetes mellitus, and older age predicted stroke at 1 year but not earlier. Conclusions: Although stroke is common after TIA, the early risk is not predicted by clinical and demographic factors. Validated models to identify which patients require urgent intervention are needed.

Study design: Cohort study with 6-years follow-up. Objective: To describe the utilization of health services by persons with spinal cord injury (SCI) and compare it with that of the general population. Setting: Alberta, Canada. Methods: All persons who sustained an SCI in Alberta between April 1992 and March 1994 were followed from date of injury to 6 years postinjury. Cases were matched (1:5) with controls randomly selected from the general population and matched for age, gender, and region of residence. Administrative data from centralized health care databases were compiled to provide a complete picture of health care use, including hospitalizations, physician contacts, long-term care admissions, home care services, and the occurrence of secondary complications. Results: In all, 233 individuals with SCI and 1165 matched controls were followed for 6 years. Compared with the control group, persons with SCI were rehospitalized 2.6 times more often, spent 3.3 more days in hospital, were 2.7 times more likely to have a physician contact, and required 30 times more hours of home care services. Of those with SCI, 47.6% were treated for a urinary tract infection, 33.8% for pneumonia, 27.5% for depression, and 19.7% for decubitus ulcer. Conclusion: SCI places a heavy burden on the health care system. Persons with SCI have greater rates of contact with the health system compared with the general population. Secondary complications continue to affect persons with SCI long after the acute trauma.

Background: Low income appears to be associated with a higher prevalence of diabetes and diabetes related complications, however, little is known about how income influences access to diabetes care. The objective of the present study was to determine whether income is associated with referral to a diabetes centre within a universal health care system. Methods: Data on referral for diabetes care, diabetes prevalence and median household income were obtained from a regional Diabetes Education Centre (DEC) database, the Canadian National Diabetes Surveillance System (NDSS) and the 2001 Canadian Census respectively. Diabetes rate per capita, referral rate per capita and proportion with diabetes referred was determined for census dissemination areas. We used Chi square analyses to determine if diabetes prevalence or population rates of referral differed across income quintiles, and Poisson regression to model diabetes rate and referral rate in relation to income while controlling for education and age. Results: There was a significant gradient in both diabetes prevalence (χ² = 743.72, p < 0.0005) and population rates of referral (χ² = 168.435, p < 0.0005) across income quintiles, with the lowest income quintiles having the highest rates of diabetes and referral to the DEC. Referral rate among those with diabetes, however, was uniform across income quintiles. Controlling for age and education, Poisson regression models confirmed a significant socio-economic gradient in diabetes prevalence and population rates of referral. Conclusion: Low income is associated with a higher prevalence of diabetes and a higher population rate of referral to this regional DEC. After accounting for diabetes prevalence, however, the equal proportions referred to the DEC across income groups suggest that there is no access bias based on income.