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Abstract Background The fit between an intervention and its local context may affect its implementation and effectiveness. Researchers have stated that both fidelity (the degree to which an intervention is delivered, enacted, and received as intended) and adaptation to the local context are necessary for high-quality implementation. This study describes the implementation of an audit and feedback (AF)-based intervention to improve transition to type 1 diabetes adult care, at five sites, in terms of adaptation and fidelity. Methods An audit and feedback (AF)-based intervention for healthcare teams to improve transition to adult care for patients with type 1 diabetes was studied at five pediatric sites. The Framework for Reporting Adaptations and Modifications to Evidence-based Implementation Strategies (FRAME-IS) was used to document the adaptations made during the study. Fidelity was determined on three different levels: delivery, enactment, and receipt. Results Fidelity of delivery, receipt, and enactment were preserved during the implementation of the intervention. Of the five sites, three changed their chosen quality improvement initiative, however, within the parameters of the study protocol; therefore, fidelity was preserved while still enabling participants to adapt accordingly. Conclusions We describe implementing a multi-center AF-based intervention across five sites in Ontario to improve the transition from pediatric to adult diabetes care for youth with type 1 diabetes. This intervention adopted a balanced approach considering both adaptation and fidelity to foster a community of practice to facilitate implementing quality improvement initiatives for improving transition to adult diabetes care. This approach may be adapted for improving transition care for youth with other chronic conditions and to other complex AF-based interventions. Trial registration ClinicalTrials.gov NCT03781973. Registered 13 December 2018. Date of enrolment of the first participant to the trial: June 1, 2019.

OBJECTIVES:. We assessed the association of preexisting diabetes mellitus with all-cause mortality and organ support receipt in adult patients with sepsis. DESIGN:. Population-based cohort study. SETTING:. Ontario, Canada (2008–2019). POPULATION:. Adult patients (18 yr old or older) with a first sepsis-related hospitalization episode. INTERVENTIONS:. None. MEASUREMENTS AND MAIN RESULTS:. The main exposure of interest was preexisting diabetes (either type 1 or 2). The primary outcome was all-cause mortality by 90 days; secondary outcomes included receipt of invasive mechanical ventilation and new renal replacement therapy. We report adjusted (for baseline characteristics using standardization) risk ratios (RRs) alongside 95% CIs. A main secondary analysis evaluated the potential mediation by prior metformin use of the association between preexisting diabetes and all-cause mortality following sepsis. Overall, 503,455 adults with a first sepsis-related hospitalization episode were included; 36% had preexisting diabetes. Mean age was 73 years, and 54% of the cohort were females. Preexisting diabetes was associated with a lower adjusted risk of all-cause mortality at 90 days (RR, 0.81; 95% CI, 0.80–0.82). Preexisting diabetes was associated with an increased risk of new renal replacement therapy (RR, 1.53; 95% CI, 1.46–1.60) but not invasive mechanical ventilation (RR, 1.03; 95% CI, 1.00–1.05). Overall, 21% (95% CI, 19–28) of the association between preexisting diabetes and reduced risk of all-cause mortality was mediated by prior metformin use. CONCLUSIONS:. Preexisting diabetes is associated with a lower risk of all-cause mortality and higher risk of new renal replacement therapy among adult patients with sepsis. Future studies should evaluate the underlying mechanisms of these associations.

Abstract Background We examined ethnic differences in the association between age at diagnosis of diabetes and the risk of cardiovascular complications. Methods We conducted a population-based cohort study in Ontario, Canada among individuals with diabetes and matched individuals without diabetes (2002-18). We fit Cox proportional hazards models to determine the associations of age at diagnosis and ethnicity (Chinese, South Asian, general population) with cardiovascular complications. We tested for an interaction between age at diagnosis and ethnicity. Results There were 453,433 individuals with diabetes (49.7% women) and 453,433 matches. There was a significant interaction between age at diagnosis and ethnicity (P

Abstract Background Outcomes of diabetes screening in contemporary, multi-ethnic populations are unknown. We examined the association of prior outpatient diabetes screening with the risks of cardiovascular events and mortality in Ontario, Canada. Methods We conducted a population-based cohort study using administrative databases among adults aged ≥ 20 years with incident diabetes diagnosed during 2014–2016. The exposure was outpatient diabetes screening performed within 3 years prior to diabetes diagnosis. The co-primary outcomes were (1) a composite of all-cause mortality and hospitalization for myocardial infarction, stroke, coronary revascularization, and (2) all-cause mortality (followed up until 2018). We calculated standardized rates of each outcome and conducted cause-specific hazard modelling to determine the adjusted hazard ratio (HR) of the outcomes, adjusting for prespecified confounders and accounting for the competing risk of death. Results We included 178,753 Ontarians with incident diabetes (70.2% previously screened). Individuals receiving prior screening were older (58.3 versus 53.4 years) and more likely to be women (49.6% versus 40.0%) than previously unscreened individuals. Individuals receiving prior screening had relatively lower standardized event rates than those without prior screening across all outcomes (composite: 12.8 versus 18.1, mortality: 8.2 versus 11.1 per 1000 patient-years). After multivariable adjustment, prior screening was associated with 34% and 32% lower risks of the composite (HR 0.66, 0.63–0.69) and mortality (0.68, 0.64–0.72) outcomes. Among those receiving prior screening, a result in the prediabetes range was associated with lower risks of the composite (0.82, 0.77–0.88) and mortality (0.71, 0.66–0.78) outcomes than a result in the normoglycemic range. Conclusions Previously screened individuals with diabetes had lower risks of cardiovascular events and mortality versus previously unscreened individuals. Better risk assessment tools are needed to support wider and more appropriate uptake of diabetes screening, especially among young adults.

Abstract Background Sepsis survivors are at elevated risk for cardiovascular disease during long-term follow-up. Whether diabetes influences cardiovascular risk after sepsis survival remains unknown. We sought to describe the association of diabetes with long-term cardiovascular outcomes in adult sepsis survivors. Methods Population-based cohort study in the province of Ontario, Canada (2008–2017). Adult survivors of a first sepsis-associated hospitalization, without pre-existing cardiovascular disease, were included. Main exposure was pre-existing diabetes (any type). The primary outcome was the composite of myocardial infarction, stroke, and cardiovascular death. Patients were followed up to 5 years from discharge date until outcome occurrence or end of study period (March 2018). We used propensity score matching (i.e., 1:1 to patients with sepsis but no pre-existing diabetes) to adjust for measured confounding at baseline. Cause-specific Cox proportional hazards models with robust standard errors were used to estimate hazard ratios (HR) alongside 95% confidence intervals (CI). A main secondary analysis evaluated the modification of the association between sepsis and cardiovascular disease by pre-existing diabetes. Results 78,638 patients with pre-existing diabetes who had a sepsis-associated hospitalization were matched to patients hospitalized for sepsis but without diabetes. Mean age of patients was 71 years, and 55% were female. Median duration from diabetes diagnosis was 9.8 years; mean HbA1c was 7.1%. Adult sepsis survivors with pre-existing diabetes experienced a higher hazard of major cardiovascular disease (HR 1.25; 95% CI 1.22–1.29)—including myocardial infarction (HR 1.40; 95% CI 1.34–1.47) and stroke (HR 1.24; 95% CI 1.18–1.29)—during long-term follow-up compared to sepsis survivors without diabetes. Pre-existing diabetes modified the association between sepsis and cardiovascular disease (risk difference: 2.3%; 95% CI 2.0–2.6 and risk difference: 1.8%; 95% CI 1.6–2.0 for the effect of sepsis—compared to no sepsis—among patients with and without diabetes, respectively). Conclusions Sepsis survivors with pre-existing diabetes experience a higher long-term hazard of major cardiovascular events when compared to sepsis survivors without diabetes. Compared to patients without sepsis, the absolute risk increase of cardiovascular events after sepsis is higher in patients with diabetes (i.e., diabetes intensified the higher cardiovascular risk induced by sepsis).

Background The relation between age at diagnosis of type 2 diabetes (T2D) and hospitalization for heart failure (HHF) is unclear. We assessed the association between age at diagnosis of T2D and HHF. Methods and Results We conducted a population‐based cohort study using administrative health databases from the Canadian province of Ontario, including participants without prior heart failure. We identified people with new‐onset T2D between April 1, 2005 and March 31, 2015, and matched each person with 3 diabetes‐free adults, according to birth year and sex. We estimated adjusted hazard ratios (HRs) and rate ratios (RRs) for the association between age at T2D diagnosis and incident HHF, which was assessed until March 31, 2020. Among 743 053 individuals with T2D and 2 199 539 matched individuals without T2D, 126 241 incident HHF events occurred over 8.9 years. T2D was associated with a greater adjusted hazard of HHF at younger ages (eg, HR at age 30 years: 6.94 [95% CI, 6.54–7.36]) than at older ages (eg, HR at age 60 years: 2.50 [95% CI, 2.45–2.56]) relative to matched individuals. Additional adjustment for mediators (hypertension, coronary artery disease, and chronic kidney disease) marginally attenuated this relationship. Age at T2D diagnosis was associated with a greater number of HHF events relative to matched individuals at younger ages (eg, RR at age 30 years: 6.39 [95% CI, 5.76–7.08]) than at older ages (eg, RR at age 60 years: 2.65 [95% CI, 2.54–2.76]). Conclusions Younger age at T2D diagnosis is associated with a disproportionately elevated HHF risk relative to age‐matched individuals without T2D.

Abstract Background Heterogeneous studies have demonstrated ethnic inequalities in the risk of SARS-CoV-2 infection and adverse COVID-19 outcomes. This study evaluates the association between ethnicity and COVID-19 outcomes in two large population-based cohorts from England and Canada and investigates potential explanatory factors for ethnic patterning of severe outcomes. Methods We identified adults aged 18 to 99 years in the QResearch primary care (England) and Ontario (Canada) healthcare administrative population-based datasets (start of follow-up: 24th and 25th Jan 2020 in England and Canada, respectively; end of follow-up: 31st Oct and 30th Sept 2020, respectively). We harmonised the definitions and the design of two cohorts to investigate associations between ethnicity and COVID-19-related death, hospitalisation, and intensive care (ICU) admission, adjusted for confounders, and combined the estimates obtained from survival analyses. We calculated the ‘percentage of excess risk mediated’ by these risk factors in the QResearch cohort. Results There were 9.83 million adults in the QResearch cohort (11,597 deaths; 21,917 hospitalisations; 2932 ICU admissions) and 10.27 million adults in the Ontario cohort (951 deaths; 5132 hospitalisations; 1191 ICU admissions). Compared to the general population, pooled random-effects estimates showed that South Asian ethnicity was associated with an increased risk of COVID-19 death (hazard ratio: 1.63, 95% CI: 1.09-2.44), hospitalisation (1.53; 1.32-1.76), and ICU admission (1.67; 1.23-2.28). Associations with ethnic groups were consistent across levels of deprivation. In QResearch, sociodemographic, lifestyle, and clinical factors accounted for 42.9% (South Asian) and 39.4% (Black) of the excess risk of COVID-19 death. Conclusion International population-level analyses demonstrate clear ethnic inequalities in COVID-19 risks. Policymakers should be cognisant of the increased risks in some ethnic populations and design equitable health policy as the pandemic continues.

Abstract Background Women with gestational diabetes (GDM) have an elevated lifetime incidence of cardiovascular disease (CVD), but the basis of this excess risk remains to be established. In this context, we hypothesized that chronic exposure to adverse cardiovascular risk factors may contribute to their elevated risk of CVD. We thus sought to quantify the determinants of CVD risk in women with a history of GDM by performing mediation analyses. Methods Women in Ontario, Canada, with a live-birth pregnancy between Jan 1998 and Dec 2017 (n=757,541) were followed for a median of 13.2 years and stratified into the following 4 groups: women with GDM who developed CVD (GDM+/CVD+); women without GDM who developed CVD (GDM−/CVD+); those with GDM but no CVD (GDM+/CVD−); and those with neither GDM nor CVD (GDM−/CVD−). Lipids (total cholesterol, LDL, HDL, triglycerides) and glycemic variables (A1c, fasting glucose) were measured between 4.3±3.0 and 4.8±3.4 times over follow-up. Results On successive measurements at a median of 4.8, 7.1, and 8.7 years postpartum, respectively, each lipid and glycemic measure progressively worsened from GDM−/CVD− to GDM+/CVD− to GDM−/CVD+ to GDM+/CVD+ (all p

Type 2 diabetes mellitus (T2DM) increases the risk of cognitive decline and dementia. Disruptions in the cytochrome P450-soluble epoxide hydrolase (CYP450-sEH) pathway have been reported in T2DM, obesity and cognitive impairment. We examine linoleic acid (LA)-derived CYP450-sEH oxylipins and cognition in T2DM and explore potential differences between obese and nonobese individuals. The study included 51 obese and 57 nonobese participants (mean age 63.0 ± 9.9, 49% women) with T2DM. Executive function was assessed using the Stroop Color-Word Interference Test, FAS-Verbal Fluency Test, Digit Symbol Substitution Test, and Trails Making Test-Part B. Verbal memory was assessed using the California Verbal Learning Test, second Edition. Four LA-derived oxylipins were analyzed by ultra-high-pressure–LC/MS, and the 12,13-dihydroxyoctadecamonoenoic acid (12,13-DiHOME) considered the main species of interest. Models controlled for age, sex, BMI, glycosylated hemoglobin A1c, diabetes duration, depression, hypertension, and education. The sEH-derived 12,13-DiHOME was associated with poorer executive function scores (F1,98 = 7.513, P = 0.007). The CYP450-derived 12(13)-epoxyoctadecamonoenoic acid (12(13)-EpOME) was associated with poorer executive function and verbal memory scores (F1,98 = 7.222, P = 0.008 and F1,98 = 4.621, P = 0.034, respectively). There were interactions between obesity and the 12,13-DiHOME/12(13)-EpOME ratio (F1,97 = 5.498, P = 0.021) and between obesity and 9(10)-epoxyoctadecamonoenoic acid (9(10)-EpOME) concentrations (F1,97 = 4.126, P = 0.045), predicting executive function such that relationships were stronger in obese individuals. These findings suggest that the CYP450-sEH pathway as a potential therapeutic target for cognitive decline in T2DM. For some markers, relationships may be obesity dependent.

Abstract Background Characteristics of patients using newer 2nd and 3rd line antidiabetic drugs in a real-world setting are poorly understood. We described the characteristics of new users of sodium-glucose co-transporter-2 inhibitors (SGLT-2i), dipeptidyl peptidase-4 inhibitors (DPP-4i), and glucagon-like peptide-1 receptor agonists (GLP-1 RA) in Canada and the United Kingdom (UK) between 2016 and 2018. Methods We conducted a multi-database cohort study using administrative health databases from 7 Canadian provinces and the UK Clinical Practice Research Datalink. We assembled a base cohort of antidiabetic drug users between 2006 and 2018, from which we constructed 3 cohorts of new users of SGLT-2i, DPP-4i, and GLP-1 RA between 2016 and 2018. Results Our cohorts included 194,070 new users of DPP-4i, 166,722 new users of SGLT-2i, and 27,719 new users of GLP-1 RA. New users of GLP-1 RA were more likely to be younger (mean ± SD: 56.7 ± 12.2 years) than new users of DPP-4i (67.8 ± 12.3 years) or SGLT-2i (64.4 ± 11.1 years). In Canada, new users of DPP-4i were more likely to have a history of coronary artery disease (22%) than new users of SGLT-2i (20%) or GLP-1 RA (15%). Conclusion Although SGLT-2i, DPP-4i, and GLP-1 RAs are recommended as 2nd or 3rd line therapy for type 2 diabetes, important differences exist in the characteristics of users of these drugs. Contrary to existing guidelines, new users of DPP-4i had a higher prevalence of cardiovascular disease at baseline than new users of SGLT2i or GLP-1RA.

Abstract Background Cardiovascular death is a common outcome in population-based studies about new healthcare interventions or treatments, such as new prescription medications. Vital statistics registration systems are often the preferred source of information about cause-specific mortality because they capture verified information about the deceased, but they may not always be accessible for linkage with other sources of population-based data. We assessed the validity of an algorithm applied to administrative health records for identifying cardiovascular deaths in population-based data. Methods Administrative health records were from an existing multi-database cohort study about sodium-glucose cotransporter-2 (SGLT2) inhibitors, a new class of antidiabetic medications. Data were from 2013 to 2018 for five Canadian provinces (Alberta, British Columbia, Manitoba, Ontario, Quebec) and the United Kingdom (UK) Clinical Practice Research Datalink (CPRD). The cardiovascular mortality algorithm was based on in-hospital cardiovascular deaths identified from diagnosis codes and select out-of-hospital deaths. Sensitivity, specificity, and positive and negative predictive values (PPV, NPV) were calculated for the cardiovascular mortality algorithm using vital statistics registrations as the reference standard. Overall and stratified estimates and 95% confidence intervals (CIs) were computed; the latter were produced by site, location of death, sex, and age. Results The cohort included 20,607 individuals (58.3% male; 77.2% ≥70 years). When compared to vital statistics registrations, the cardiovascular mortality algorithm had overall sensitivity of 64.8% (95% CI 63.6, 66.0); site-specific estimates ranged from 54.8 to 87.3%. Overall specificity was 74.9% (95% CI 74.1, 75.6) and overall PPV was 54.5% (95% CI 53.7, 55.3), while site-specific PPV ranged from 33.9 to 72.8%. The cardiovascular mortality algorithm had sensitivity of 57.1% (95% CI 55.4, 58.8) for in-hospital deaths and 72.3% (95% CI 70.8, 73.9) for out-of-hospital deaths; specificity was 88.8% (95% CI 88.1, 89.5) for in-hospital deaths and 58.5% (95% CI 57.3, 59.7) for out-of-hospital deaths. Conclusions A cardiovascular mortality algorithm applied to administrative health records had moderate validity when compared to vital statistics data. Substantial variation existed across study sites representing different geographic locations and two healthcare systems. These variations may reflect different diagnostic coding practices and healthcare utilization patterns.

Abstract Background Pregnancy offers a unique opportunity to identify women at higher future risk of type 2 diabetes mellitus (DM). In pregnancy, a woman has greater engagement with the healthcare system, and certain conditions are more apt to manifest, such as gestational DM (GDM) that are important markers for future DM risk. This study protocol describes the development and validation of a risk prediction model (RPM) for estimating a woman’s 5-year risk of developing type 2 DM after pregnancy. Methods Data will be obtained from existing Ontario population-based administrative datasets. The derivation cohort will consist of all women who gave birth in Ontario, Canada between April 2006 and March 2014. Pre-specified predictors will include socio-demographic factors (age at delivery, ethnicity), maternal clinical factors (e.g., body mass index), pregnancy-related events (gestational DM, hypertensive disorders of pregnancy), and newborn factors (birthweight percentile). Incident type 2 DM will be identified by linkage to the Ontario Diabetes Database. Weibull accelerated failure time models will be developed to predict 5-year risk of type 2 DM. Measures of predictive accuracy (Nagelkerke’s R 2), discrimination (C-statistics), and calibration plots will be generated. Internal validation will be conducted using a bootstrapping approach in 500 samples with replacement, and an optimism-corrected C-statistic will be calculated. External validation of the RPM will be conducted by applying the model in a large population-based pregnancy cohort in Alberta, and estimating the above measures of model performance. The model will be re-calibrated by adjusting baseline hazards and coefficients where appropriate. Discussion The derived RPM may help identify women at high risk of developing DM in a 5-year period after pregnancy, thus facilitate lifestyle changes for women at higher risk, as well as more frequent screening for type 2 DM after pregnancy.

Abstract Background Diabetes is a highly prevalent chronic disease that places a large burden on individuals and health care systems. Models predicting the risk (also called predictive models) of other conditions often compare people with and without diabetes, which is of little to no relevance for people already living with diabetes (called patients). This review aims to identify and synthesize findings from existing predictive models of physical and mental health diabetes-related conditions. Methods We will use the scoping review frameworks developed by the Joanna Briggs Institute and Levac and colleagues. We will perform a comprehensive search for studies from Ovid MEDLINE and Embase databases. Studies involving patients with prediabetes and all types of diabetes will be considered, regardless of age and gender. We will limit the search to studies published between 2000 and 2018. There will be no restriction of studies based on country or publication language. Abstracts, full-text screening, and data extraction will be done independently by two individuals. Data abstraction will be conducted using a standard methodology. We will undertake a narrative synthesis of findings while considering the quality of the selected models according to validated and well-recognized tools and reporting standards. Discussion Predictive models are increasingly being recommended for risk assessment in treatment decision-making and clinical guidelines. This scoping review will provide an overview of existing predictive models of diabetes complications and how to apply them. By presenting people at higher risk of specific complications, this overview may help to enhance shared decision-making and preventive strategies concerning diabetes complications. Our anticipated limitation is potentially missing models because we will not search grey literature.

Abstract Background To evaluate the impact of integrating diabetes education teams in primary care on glycemic control, lipid, and blood-pressure management in type 2 diabetes patients. Methods A historical cohort design was used to assess the integration of teams comprising nurse and dietitian educators in 11 Ontario primary-care sites, which delivered individualized self-management education. Of the 771 adult patients with A1C ≥ 7% recruited, 487 patients attended appointments with the diabetes teams, while the remaining 284 patients did not. The intervention’s primary goal was to increase the proportion of patients with A1C ≤7%. Secondary goals were to reduce mean A1C, low-density lipoprotein, total cholesterol-high density lipoprotein, and diastolic and systolic blood pressure, as recommended by clinical-practice guidelines. Results After 12 months, a higher proportion of intervention-group patients reached the target for A1C, compared with the control group. Mean A1C levels fell significantly among all patients, but the mean reduction was larger for the intervention group than the control group. Although more intervention-group patients reached targets for all clinical outcomes, the between-group differences were not statistically significant, except for A1C. Conclusions Nurse and dietitian diabetes-education teams can have a clinically meaningful impact on patients’ ability to meet recommended A1C targets. Given the study’s historical cohort design, results are generalizable and applicable to day-to-day primary-care practice. Longer follow-up studies are needed to investigate whether the positive outcomes of the intervention are sustainable.

Abstract Background Validated algorithms to classify type 1 and 2 diabetes (T1D, T2D) are mostly limited to white pediatric populations. We conducted a large study in Hong Kong among children and adults with diabetes to develop and validate algorithms using electronic health records (EHRs) to classify diabetes type against clinical assessment as the reference standard, and to evaluate performance by age at diagnosis. Methods We included all people with diabetes (age at diagnosis 1.5–100 years during 2002–15) in the Hong Kong Diabetes Register and randomized them to derivation and validation cohorts. We developed candidate algorithms to identify diabetes types using encounter codes, prescriptions, and combinations of these criteria (“combination algorithms”). We identified 3 algorithms with the highest sensitivity, positive predictive value (PPV), and kappa coefficient, and evaluated performance by age at diagnosis in the validation cohort. Results There were 10,196 (T1D n = 60, T2D n = 10,136) and 5101 (T1D n = 43, T2D n = 5058) people in the derivation and validation cohorts (mean age at diagnosis 22.7, 55.9 years; 53.3, 43.9% female; for T1D and T2D respectively). Algorithms using codes or prescriptions classified T1D well for age at diagnosis

Background: The cardiovascular outcomes of hypertension and diabetes in India have never been studied at the national level. Objectives: We conducted a nationally-representative proportional mortality study to measure the associations of hypertension and diabetes with premature mortality due to ischemic heart disease (IHD) and stroke among Indian adults. Methods: We determined causes of death by verbal autopsy from 2001–14 among 2.4 million households. We defined cases as those who died of the study outcomes and controls as those who died of injuries, respiratory causes, or cancer. We used multivariable logistic regression models to compute adjusted odds ratios (OR) measuring the association of hypertension and diabetes with IHD or stroke mortality, population-attributable fractions (PAF), and time trends. Results: The mean age at death was 55.6 (standard deviation 9.9) years for IHD, 58.2 (9.0) years for stroke, and 46.8 (injury) to 59.8 (respiratory) years for controls. There were more men among both the cases (IHD: 70.1%; stroke: 59.0%) and controls (injury: 76.6%; cancer: 55.4%; respiratory: 59.8%). Hypertension was associated with six- to eight-fold increases in the odds of IHD (OR 5.9, 99% CI 5.6–6.2) and stroke mortality (7.9, 7.4–8.5). Diabetes was associated with double the odds (1.9, 1.7–2.0) of IHD mortality and increased odds of stroke mortality (1.6, 1.4–1.7). Hypertension accounted for an increasing PAF of IHD mortality and decreasing PAF of stroke mortality. Diabetes was associated with relatively lower PAFs and variable time trends. Conclusions: Hypertension is associated with an unexpectedly high burden of cardiovascular mortality, and contributes to an increasing proportion of IHD deaths and a decreasing proportion of stroke deaths. Better management of hypertension and diabetes is urgently required to reduce premature cardiovascular mortality.

Abstract Background When young adults transfer from pediatric to adult diabetes care they are at risk for deterioration of glycemic control, putting them at an increased risk of developing both acute and chronic complications. Despite increased awareness of these risks, there are gaps in care delivery during this vulnerable time and variability in the implementation of recommended transition practice. Audit and feedback (AF) interventions have a positive but variable effect on implementation of best practices. An expert group identified specific suggestions for optimizing the effectiveness of AF interventions. We aim to test an AF-based intervention incorporating these specific suggestions to improve transition practices and glycemic control in the first year after transfer from pediatric to adult diabetes care. Methods This is a pragmatic quasi-experimental study; a series of three cohort studies (pre-implementation, early-implementation, and post-implementation) to compare the baseline adjusted hemoglobin A1c (HbA1c) in the 12 months after the final pediatric visit in five pediatric diabetes centres within the Ontario Pediatric Diabetes Network in Ontario, Canada. The intervention includes three components: 1) centre-level feedback reports compiling data from chart abstraction, linked provincial administrative datasets, and patient-reported experience measures; 2) webinars for facilitated conversations/coaching about the feedback; and 3) online repository of curated transition resources for providers. The primary outcome will be analyzed using a multivariable linear regression model. We will conduct a qualitative process evaluation to understand intervention fidelity and to provide insight into the mechanisms of action of our results. Discussion There is a need to develop an innovative system-level approach to improve outcomes and the quality of care for young adults with type 1 diabetes during the vulnerable time when they transfer to adult care. Our research team, a collaboration of health services, implementation science, and quality improvement researchers, are designing, implementing, and evaluating an AF-based intervention using recommendations about how to optimize effectiveness. This knowledge will be generalizable to other care networks that aim to deliver uniformly high-quality care in diverse care settings. Trial registration ClinicalTrials.gov NCT03781973. Registered 13 December 2018. Date of enrolment of the first participant to the trial: June 1, 2019.

South Asians (SAs), originating from the Indian subcontinent (India, Pakistan, Sri Lanka, Bangladesh, Nepal, and Bhutan), represent one quarter of the global population and are the largest visible minority in Canada. SAs experience the highest rates of coronary artery disease in Canada. Although conventional cardiovascular risk factors remain predictive in SA, the excess risk is not fully explained by these risk factors alone. Abdominal obesity, metabolic syndrome, and insulin resistance likely contribute a greater risk in SAs than in other populations. The South Asian Heart Alliance has been recently formed to investigate and recommend the best strategies for the prevention of cardiometabolic disease in SAs in Canada. This topic review represents a comprehensive overview of the magnitude of cardiovascular disease in SAs in Canada, with a review of conventional and novel risk markers in the SA population. Both primary and secondary prevention strategies are suggested and when possible, adapted specifically for the SA population. The need for SAs and their healthcare professionals to be more aware of the problem and potential solutions, along with the need for population-specific research, is highlighted. Résumé: Les Asiatiques du sud originaires du sous-continent indien (Inde, Pakistan, Sri Lanka, Bangladesh, Népal et Bhoutan) représentent le quart de la population mondiale et constituent la plus importante minorité visible au Canada. C’est aussi au sein de cette population qu’on observe les taux de coronaropathie les plus élevés au Canada. Bien que les facteurs de risque cardiovasculaire classiques conservent leur valeur prédictive chez les Asiatiques du sud, ils n’expliquent pas à eux seuls le risque excédentaire observé. L’obésité abdominale, le syndrome métabolique et l’insulinorésistance constituent vraisemblablement des facteurs de risque plus importants chez les Asiatiques du sud que dans les autres populations. La South Asian Heart Alliance a récemment été mise sur pied afin d’explorer les stratégies exemplaires pour la prévention des maladies cardiométaboliques chez les Asiatiques du sud au Canada et de formuler des recommandations à cet égard. Cette revue thématique présente un aperçu de l’importance des maladies cardiovasculaires au sein de la population des Asiatiques du sud du Canada, ainsi qu’un résumé des marqueurs de risque classiques et nouveaux dans cette population. Les auteurs proposent des stratégies de prévention primaire et secondaire adaptées, dans la mesure du possible, à la population des Asiatiques du sud. Ils font également ressortir l’importance de sensibiliser davantage les Asiatiques du sud et les professionnels de la santé aux risques et aux solutions possibles, ainsi que la nécessité de mener des recherches axées sur cette population particulière.

Background Women with either preterm or small‐for‐gestational‐age (SGA) delivery have an elevated lifetime risk of cardiovascular disease that has been attributed to the accrual of vascular risk factors over time. We sought to determine whether an adverse cardiovascular risk factor profile develops in the years before pregnancies complicated by preterm delivery or SGA. Methods and Results Using administrative databases, we identified all 156 278 nulliparous women in Ontario, Canada, who had singleton pregnancies between January 2011 and December 2018 and ≥2 measurements of the following analytes between January 2008 and the start of pregnancy: glycosylated hemoglobin, glucose, lipids, and alanine aminotransferase. There were 11 078 women with preterm delivery and 19 367 with SGA. The 2 most recent pregravid tests were performed at median 0.6 (interquartile range, 0.3–1.4) and 1.9 (interquartile range, 1.1–3.3) years before pregnancy, respectively. Women with preterm delivery had higher pregravid glycosylated hemoglobin, glucose, low‐density lipoprotein cholesterol, triglycerides, and alanine aminotransferase, and lower high‐density lipoprotein cholesterol, than those without preterm delivery. In contrast, women with SGA had lower pregravid fasting glucose, random glucose, and triglycerides than those without SGA. In the years before pregnancy, women with preterm delivery had higher annual increases than their peers in glycosylated hemoglobin (0.7‐times higher), triglycerides (7.9‐times higher), and alanine aminotransferase (2.2‐times higher). During this time, fasting glucose increased in women who developed preterm delivery but decreased in their peers. Conclusions An adverse cardiovascular risk factor profile evolves over time in the years before pregnancy complicated by preterm delivery, but does not necessarily precede SGA.

Abstract Objectives For patients with type 2 diabetes, newer antihyperglycaemic agents (AHA), including the dipeptidyl peptidase IV inhibitors (DPP4i), glucagon‐like peptide‐1 receptor agonists (GLP1RA) and sodium glucose co‐transporter 2 inhibitors (SGLT2i) offer a lower risk of hypoglycaemia relative to sulfonylurea or insulin. However, it is not clear how AHA compare to placebo on risk of any hypoglycaemia. This study evaluates the risk of any and severe hypoglycaemia with AHA and metformin relative to placebo. Design A systematic review and meta‐analysis was conducted of randomized, placebo‐controlled trials ≥12 weeks in duration. MEDLINE, Embase and the Cochrane Library were searched up to April 16, 2019. Studies allowing use of other diabetes medications were excluded. Mantel‐Haenszel risk ratio with 95% confidence intervals were used to pool estimates based on class of AHA and number of concomitant therapies used. Patients Eligible studies enrolled patients with type 2 diabetes ≥18 years of age. Results 144 studies met our inclusion criteria. Any hypoglycaemia was not increased with AHA when used as monotherapy (DPP4i (RR 1.12; 95% CI 0.81‐1.56), GLP1RA (1.77; 0.91‐3.46), SGLT2i (1.34; 0.83‐2.15)), or as add‐on to metformin (DPP4i (0.95; 0.67‐1.35), GLP1RA (1.24; 0.80‐1.91), SGLT2i (1.29; 0.91‐1.83)) or as triple therapy (1.13; 0.67‐1.91). However, metformin monotherapy (1.73; 1.02‐2.94) and dual therapy initiation (3.56; 1.79‐7.10) was associated with an increased risk of any hypoglycaemia. Severe hypoglycaemia was rare not increased for any comparisons. Conclusions Metformin and the simultaneous initiation of dual therapy, but not AHA used alone or as single add‐on combination therapy, was associated with an increased risk of any hypoglycaemia relative to placebo.

Abstract Background Health care data allow for the study and surveillance of chronic diseases such as diabetes. The objective of this study was to identify and validate optimal algorithms for diabetes cases within health care administrative databases for different research purposes, populations, and data sources. Methods We linked health care administrative databases from Ontario, Canada to a reference standard of primary care electronic medical records (EMRs). We then identified and calculated the performance characteristics of multiple adult diabetes case definitions, using combinations of data sources and time windows. Results The best algorithm to identify diabetes cases was the presence at any time of one hospitalization or physician claim for diabetes AND either one prescription for an anti-diabetic medication or one physician claim with a diabetes-specific fee code [sensitivity 84.2%, specificity 99.2%, positive predictive value (PPV) 92.5%]. Use of physician claims alone performed almost as well: three physician claims for diabetes within one year was highly specific (sensitivity 79.9%, specificity 99.1%, PPV 91.4%) and one physician claim at any time was highly sensitive (sensitivity 93.6%, specificity 91.9%, PPV 58.5%). Conclusions This study identifies validated algorithms to capture diabetes cases within health care administrative databases for a range of purposes, populations and data availability. These findings are useful to study trends and outcomes of diabetes using routinely-collected health care data.