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26. Diabetes Mellitus Forecasting Using Population Health Data in Ontario, Canada

Author

Ravaut, Mathieu, Sadeghi, Hamed, Leung, Kin Kwan, Volkovs, Maksims, and Rosella, Laura C.

Subjects
Statistics - Applications, Computer Science - Machine Learning
Abstract

Leveraging health administrative data (HAD) datasets for predicting the risk of chronic diseases including diabetes has gained a lot of attention in the machine learning community recently. In this paper, we use the largest health records datasets of patients in Ontario,Canada. Provided by the Institute of Clinical Evaluative Sciences (ICES), this database is age, gender and ethnicity-diverse. The datasets include demographics, lab measurements,drug benefits, healthcare system interactions, ambulatory and hospitalizations records. We perform one of the first large-scale machine learning studies with this data to study the task of predicting diabetes in a range of 1-10 years ahead, which requires no additional screening of individuals.In the best setup, we reach a test AUC of 80.3 with a single-model trained on an observation window of 5 years with a one-year buffer using all datasets. A subset of top 15 features alone (out of a total of 963) could provide a test AUC of 79.1. In this paper, we provide extensive machine learning model performance and feature contribution analysis, which enables us to narrow down to the most important features useful for diabetes forecasting. Examples include chronic conditions such as asthma and hypertension, lab results, diagnostic codes in insurance claims, age and geographical information., Comment: 18 pages, 3 figures, 8 Tables, Submitted to 2019 ML for Healthcare conference

Published
2019

33. Sepsis hospitalization and risk of subsequent cardiovascular events in adults: a population-based matched cohort study

Author

Angriman, Federico, Rosella, Laura C., Lawler, Patrick R., Ko, Dennis T., Wunsch, Hannah, and Scales, Damon C.

Subjects
Ontario. Ministry of Health and Long-Term Care, Diseases, Complications and side effects, Risk factors, Heart attack -- Complications and side effects -- Risk factors, Thromboembolism -- Risk factors -- Complications and side effects, Infection -- Risk factors -- Complications and side effects, Cardiovascular diseases -- Risk factors -- Complications and side effects, Adults
Abstract

Author(s): Federico Angriman [sup.1] [sup.2] [sup.3], Laura C. Rosella [sup.4] [sup.5] [sup.8] [sup.9], Patrick R. Lawler [sup.2] [sup.6], Dennis T. Ko [sup.5] [sup.7], Hannah Wunsch [sup.1] [sup.2] [sup.3] [sup.5], Damon [...], Purpose To determine whether surviving a first sepsis hospitalization is associated with long-term cardiovascular events. Methods Population-based matched cohort study conducted in Ontario, Canada (2008-2017). Adult survivors (older than 18 years) of a first sepsis hospitalization were matched to adult survivors of a non-sepsis hospitalization using hard-matching and propensity score methods. Patients with pre-existing cardiovascular disease were excluded. The primary composite outcome was myocardial infarction, stroke, or cardiovascular death up to 5 years of follow-up. Secondary outcomes included venous thromboembolism and all-cause death. Cox proportional hazards models with robust standard errors were used to estimate the association of sepsis with all outcomes of interest; hazard ratios (HR) and 95% confidence intervals (CI) were calculated. Sensitivity analyses included Fine and Gray models to account for the competing risk of all-cause death and probabilistic bias analyses. Results 254,241 adult sepsis survivors were matched to adult survivors of non-sepsis hospitalization episodes. Sepsis survivors experienced an increased hazard of major cardiovascular events compared to non-sepsis survivors (HR 1.30; 95% CI 1.27-1.32), which was more pronounced in younger patients (HR 1.66; 95% CI 1.36-2.02 for patients aged 40 or younger; HR 1.21; 95% CI 1.18-1.24 for patients older than 80 years). Sepsis survivors also faced an increased hazard of venous thromboembolism (HR 1.61; 95% CI 1.55-1.67) and all-cause death (HR 1.26; 95% CI 1.25-1.27). Sensitivity analyses yielded consistent results. Conclusions Adult sepsis survivors experience an increased hazard of major cardiovascular events compared to survivors of a non-sepsis hospitalization.

Published
2022
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34. Au Canada, la nouvelle normalite necessitera un systeme de detection ameliore des pathogenes respiratoires emergents et reemergents

Author

Berry, Isha, Brown, Kevin A., Buchan, Sarah A., Hohenadel, Karin, Kwong, Jeffrey C., Patel, Samir, Rosella, Laura C., Mishra, Sharmistha, and Sander, Beate

Subjects
Care and treatment, Communicable diseases -- Care and treatment, COVID-19
Abstract

La surveillance des maladies infectieuses est essentielle aux systemes de sante publique (1). Cependant, les mesures de lutte contre la pandemie de COVID-19 au Canada reposaient sur des plateformes de [...]

Published
2022
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35. A better normal in Canada will need a better detection system for emerging and re-emerging respiratory pathogens

Author

Berry, Isha, Brown, Kevin A., Buchan, Sarah A., Hohenadel, Karin, Kwong, Jeffrey C., Patel, Samir, Rosella, Laura C., Mishra, Sharmistha, and Sander, Beate

Subjects
Control, Identification and classification, Methods, Environmental aspects, Health aspects, Respiratory tract infections -- Control, Pathogenic microorganisms -- Identification and classification -- Environmental aspects, Sentinel surveillance -- Methods, Emerging communicable diseases -- Control, Wastewater -- Health aspects, Sentinel health events -- Methods
Abstract

Infectious disease surveillance is fundamental to public health systems. (1) However, Canada's COVID-19 pandemic response relied on clinical and outbreak management (COM) platforms; i.e., public health institutions tracking case counts [...]

Published
2022
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