Project description:Encephalitis, a brain inflammation leading to severe illness and often death, is caused by >100 pathogens. To assess the incidence and trends of encephalitis in Ontario, Canada, we obtained data on 6,463 Ontario encephalitis hospitalizations from the hospital Discharge Abstract Database for April 2002-December 2013 and analyzed these data using multiple negative binomial regression. The estimated crude incidence of all-cause encephalitis in Ontario was ≈4.3 cases/100,000 persons/year. Incidence rates for infants <1 year of age and adults >65 years were 3.9 and 3.0 times that of adults 20-44 years of age, respectively. Incidence peaks during August-September in 2002 and 2012 resulted primarily from encephalitis of unknown cause and viral encephalitis. Encephalitis occurred more frequently in older age groups and less frequently in women in Ontario when compared to England, but despite differences in population, vector-borne diseases, climate, and geography, the epidemiology was overall remarkably similar in the two regions.
Project description:Survival implications of nontuberculous mycobacterial pulmonary disease (NTM-PD) and NTM pulmonary isolation without disease (NTM-PI) are unclear. To study deaths associated with NTM-PD and NTM-PI and differences in survival between them, we conducted a population-based cohort study of persons with microbiologically defined NTM-PD or NTM-PI diagnosed during 2001-2013 in Ontario, Canada. We used propensity score matching and Cox proportional hazards models to compare survival. Among 9,681 NTM-PD patients and 10,936 NTM-PI patients, 87% and 91%, respectively, were successfully matched with unexposed controls. Both NTM-PD and NTM-PI were associated with higher rates of death for all species combined and for most individual species. Compared with NTM-PI, NTM-PD was associated with higher death rates for all species combined, Mycobacterium avium complex, and M. xenopi. NTM-PD and NTM-PI were significantly associated with death, NTM-PD more so than NTM-PI.
Project description:PurposeThe Canadian Addiction Treatment Centre (CATC) cohort was established during a period of increased provision of opioid agonist treatment (OAT), to study patient outcomes and trends related to the treatment of opioid use disorder (OUD) in Canada. The CATC cohort's strengths lie in its unique physician network, shared care model and event-level data, making it valuable for validation and integration studies. The CATC cohort is a valuable resource for examining OAT outcomes, providing insights into substance use trends and the impact of service-level factors.ParticipantsThe CATC cohort comprises 32 246 people who received OAT prescriptions between April 2014 and February 2021, with ongoing tri-annual updates planned until 2027. The cohort includes data from all CATC clinics' electronic medical records and includes demographic information and OAT clinical indicators.Findings to dateThis cohort profile describes the demographic and clinical characteristics of patients being treated in a large OAT physician network. As well, we report the longitudinal OAT retention by treatment type during a time of increasing exposure to a contaminated dangerous drug supply. Notable findings also include retention differences between methadone (32% of patients at 1 year) and buprenorphine (20% at 1 year). Previously published research from this cohort indicated that patient-level factors associated with retention include geographic location, concurrent substance use and prior treatment attempts. Service-level factors such as telemedicine delivery and frequency of urine drug screenings also influence retention. Additionally, the cohort identified rising OAT participation and a substantial increase in fentanyl use during the COVID-19 pandemic.Future plansFuture research objectives are the longitudinal evaluation of retention and flexible modelling techniques that account for the changes as patients are treated with OAT. Furthermore, future research aims are the use of conditional models, and linkage with provincial-level administrative datasets.