Patterns of metformin use and glycated haemoglobin trends among patients with newly diagnosed type 2 diabetes in Alberta, Canada.

AIM: Canadian guidelines recommend metformin as first-line therapy for incident uncomplicated type 2 diabetes and the vast majority of patients are treated accordingly. However, only 54% 65% remain on treatment after 1 year, with the highest discontinuation rates within the first 3 months. The purpose of this study was: (a) to identify individual and clinical factors associated with metformin discontinuation among patients with newly diagnosed uncomplicated type 2 diabetes in Alberta, Canada, and (b) describe glycated haemoglobin (HbA1c) trajectories in the first 12 months after initiation of pharmacotherapy, stratified by metformin usage pattern. MATERIALS AND METHODS: We conducted a retrospective cohort study using linked administrative datasets from 2012 to 2017 to define a cohort of individuals with uncomplicated incident type 2 diabetes. Using logistic regression, we determined individual and clinical characteristics associated with metformin discontinuation. We categorized individuals based on patterns of metformin use and then used mean HbA1c measurements over a 12-month follow-up period to determine glycaemic trajectories for each pattern. RESULTS: Characteristics associated with metformin discontinuation were younger age, lower baseline HbA1c and having fewer comorbidities. Sex, income and location (urban/rural) were not significantly associated with metformin discontinuation. Individuals who continued metformin with higher adherence and individuals who discontinued metformin entirely had lowest HbA1c values at 12 months from treatment initiation. Those who changed therapy or had additional therapies added had higher HbA1c values at 12 months. CONCLUSION: Identifying characteristics associated with discontinuation of metformin and individuals' medication usage patterns provide an opportunity for targeted interventions to support patients' glycaemic management.

Association between sodium-glucose cotransporter-2 inhibitors and arrhythmic outcomes in patients with diabetes and pre-existing atrial fibrillation.

AIMS: Prior studies suggest that sodium-glucose cotransporter-2 inhibitors (SGLT2is) may decrease the incidence of atrial fibrillation (AF). However, it is unknown whether SGLT2i can attenuate the disease course of AF among patients with pre-existing AF and Type II diabetes mellitus (DM). In this study, our objective was to examine the association between SGLT2i prescription and arrhythmic outcomes among patients with DM and pre-existing AF. METHODS AND RESULTS: We conducted a population-based cohort study of adults with DM and AF between 2014 and 2019. Using a prevalent new-user design, individuals prescribed SGLT2i were matched 1:1 to those prescribed dipeptidyl peptidase-4 inhibitors (DPP4is) based on time-conditional propensity scores. The primary endpoint was a composite of AF-related healthcare utilization (i.e. hospitalization, emergency department visits, electrical cardioversion, or catheter ablation). Secondary outcome measures included all-cause mortality, heart failure (HF) hospitalization, and ischaemic stroke or transient ischaemic attack (TIA). Cox proportional hazard models were used to examine the association of SGLT2i with the study endpoint. Among 2242 patients with DM and AF followed for an average of 3.0 years, the primary endpoint occurred in 8.7% (n = 97) of patients in the SGLT2i group vs. 10.0% (n = 112) of patients in the DPP4i group [adjusted hazard ratio 0.73 (95% confidence interval 0.55-0.96; P = 0.03)]. Sodium-glucose cotransporter-2 inhibitors were associated with significant reductions in all-cause mortality and HF hospitalization, but there was no difference in the risk of ischaemic stroke/TIA. CONCLUSION: Among patients with DM and pre-existing AF, SGLT2is are associated with decreased AF-related health resource utilization and improved arrhythmic outcomes compared with DPP4is.

Evaluating the coding accuracy of type 2 diabetes mellitus among patients with non-alcoholic fatty liver disease.

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) describes a spectrum of chronic fattening of liver that can lead to fibrosis and cirrhosis. Diabetes has been identified as a major comorbidity that contributes to NAFLD progression. Health systems around the world make use of administrative data to conduct population-based prevalence studies. To that end, we sought to assess the accuracy of diabetes International Classification of Diseases (ICD) coding in administrative databases among a cohort of confirmed NAFLD patients in Calgary, Alberta, Canada. METHODS: The Calgary NAFLD Pathway Database was linked to the following databases: Physician Claims, Discharge Abstract Database, National Ambulatory Care Reporting System, Pharmaceutical Information Network database, Laboratory, and Electronic Medical Records. Hemoglobin A1c and diabetes medication details were used to classify diabetes groups into absent, prediabetes, meeting glycemic targets, and not meeting glycemic targets. The performance of ICD codes among these groups was compared to this standard. Within each group, the total numbers of true positives, false positives, false negatives, and true negatives were calculated. Descriptive statistics and bivariate analysis were conducted on identified covariates, including demographics and types of interacted physicians. RESULTS: A total of 12,012 NAFLD patients were registered through the Calgary NAFLD Pathway Database and 100% were successfully linked to the administrative databases. Overall, diabetes coding showed a sensitivity of 0.81 and a positive predictive value of 0.87. False negative rates in the absent and not meeting glycemic control groups were 4.5% and 6.4%, respectively, whereas the meeting glycemic control group had a 42.2% coding error. Visits to primary and outpatient services were associated with most encounters. CONCLUSION: Diabetes ICD coding in administrative databases can accurately detect true diabetic cases. However, patients with diabetes who meets glycemic control targets are less likely to be coded in administrative databases. A detailed understanding of the clinical context will require additional data linkage from primary care settings.

[Mobile cardiovascular screening and prevention in the population : useful in Switzerland?] / Dépistage et prévention cardiovasculaire mobile dans la population : utile en Suisse ?

Mobile cardiovascular prevention interventions are still uncommon in Switzerland. Mobile clinics improve access to prevention and enable new diagnoses of hypertension or hypercholesterolemia to be identified in a cost-effective way and has shown benefits in health behaviors such as physical activity, smoking cessation and medication compliance. The Unisanté Bus Santé is a mobile clinic run by nurses that offers screening for cardiovascular risk factors, health advice and, if necessary, referral to medical care. Mobile health initiatives such as the Bus Santé could play a more important role in the Swiss healthcare system, bringing personalized preventive care closer to the population.

Les interventions mobiles de promotion de la santé et de prévention sont encore peu fréquentes en Suisse. Elles permettent pourtant, par exemple, l'identification de nouveaux diagnostics d'hypertension ou d'hypercholestérolémie avec un rapport coût-efficacité favorable et ont également montré des bénéfices sur les comportements de santé comme l'activité physique, le sevrage tabagique et l'observance médicamenteuse. Le Bus santé d'Unisanté est une clinique mobile gérée par des infirmières proposant un dépistage des facteurs de risque cardiovasculaire, des conseils de santé et, si nécessaire, une orientation vers des soins médicaux. Ces interventions mobiles pourraient jouer un rôle plus important dans le système de santé suisse en amenant une offre de prévention personnalisée au plus proche de la population.

Estimating the Rates of Undiagnosed Prediabetes and Diabetes Among People Experiencing Homelessness.

OBJECTIVES: The rising prevalence of type 2 diabetes in Canada poses a significant health challenge. Despite the convenience of screening for diabetes with glycated hemoglobin (A1C) concentration, people experiencing homelessness (PEH) often face barriers to accessing diabetes screening, potentially leading to underdiagnosis. In this study, we aim to assess the prevalence of undiagnosed diabetes among PEH in Calgary, Alberta, and contribute insights for planning health-care services and public health initiatives. METHODS: Four screening clinics were held, and participants were recruited through posters and word of mouth. Participants underwent point-of-care A1C testing using the Siemens DCA Vantage point-of-care analyzer. Descriptive statistics were used to identify the proportions of prediabetes and diabetes, whereas CANRISK survey scores were used to identify the pre-test probability of diabetes. RESULTS: The mean age of participants (n=102) was 47.6 years, and the self-reported causes of homelessness among the participants were diverse, including housing and financial issues (n=53), interpersonal and family issues (n=35), and health- or corrections-related factors (n=27). The average A1C was 5.60% (standard deviation 0.57%), with 5 values in the diabetes range and 12 in the prediabetes range, for a total of 17 participants found to have previously undiagnosed dysglycemia. CONCLUSIONS: The high rate of undiagnosed prediabetes and diabetes among PEH reflects at least what is already seen in the general population in Canada. More resources are required to reduce the barriers to screening for diabetes among this population.

Disparities in diabetes processes of care among people experiencing homelessness: An opportunity for intervention.

AIMS: To compare processes of diabetes care by homeless status. METHODS: A population-based propensity matched cohort study was conducted in Ontario, Canada. People with diabetes were identified in administrative healthcare data between April 2006 and March 2019. Those with a documented history of homelessness were matched to non-homeless controls. Data on processes of care measures included glucose monitoring tests, screening for microvascular complications, and physician follow-up. Differences in processes of care were compared by homeless status using proportions, risk ratios, and rate ratios. RESULTS: Of the 1,076,437 people with diabetes, 5219 matched pairs were identified. Homelessness was associated with fewer tests for glycated hemoglobin (RR = 0.63; 95 %CI: 0.60-0.67), LDL cholesterol (RR = 0.80; 95 %CI: 0.78-0.82), serum creatinine (RR = 0.94; 95 %CI: 0.92-0.97), urine protein quantification (RR = 0.62; 95 %CI: 0.59-0.66), and eye examinations (RR = 0.74; 95 %CI: 0.71-0.77). People with a history of homelessness were less likely to use primary care for diabetes management (RR = 0.62; 95 %CI: 0.59-0.66) or specialist care (RR = 0.87; 95 %CI: 0.83-0.91) compared to non-homeless controls. CONCLUSIONS: Disparities in diabetes care are evident for people with a history of homelessness and contribute to excess morbidity in this population. These data provide an impetus for investment in tailored interventions to improve healthcare equity and prevent long-term complications.

Managing Medications During "Sick Days" in Patients With Diabetes, Kidney, and Cardiovascular Conditions: A Theory-informed Approach to Intervention Design and Implementation.

OBJECTIVES: Our aim in this work was to 1) explore barriers and enablers to patient and health-care provider (HCP) behaviours related to sick-day medication guidance (SDMG), 2) identify theory-informed strategies to advise SDMG intervention design, and 3) obtain perspectives on an eHealth tool for this purpose. METHODS: A qualitative descriptive study using qualitative conventional content analysis was undertaken. Interviews and focus groups were held with patients and HCPs from January 2021 to April 2022. Data were analyzed using the Behaviour Change Wheel and Theoretical Domains Framework to inform intervention design. RESULTS: Forty-eight people (20 patients, 13 pharmacists, 12 family physicians, and 3 nurse practitioners) participated in this study. Three interventions were designed to address the identified barriers and enablers: 1) prescriptions provided by a community-based care provider, 2) pharmacists adding a label to at-risk medications, and 3) built-in prompts for prescribing and dispensing software. Most participants accepted the concept of an eHealth tool and identified pharmacists as the ideal point-of-care provider. Challenges for an eHealth tool were raised, including credibility, privacy of data, medical liability, clinician remuneration and workload impact, and equitable access to use of the tool. CONCLUSIONS: Patients and HCPs endorsed non-technology and eHealth innovations as strategies to aid in the delivery of SDMG. These findings can guide the design of future theory-informed SDMG interventions.

The effect of preprandial versus postprandial physical activity on glycaemia: Meta-analysis of human intervention studies.

This meta-analysis aims to investigate the effect of preprandial physical activity (PA) versus postprandial PA on glycaemia in human intervention studies. Medline and Embase.com were searched until February 2023 for intervention studies in adults, directly comparing preprandial PA versus postprandial PA on glycaemia. Studies were screened using ASReview (34,837) and full texts were read by two independent reviewers (42 full text, 28 included). Results were analysed using pooled mean differences in random-effects models. Studies were either acute response studies (n = 21) or Randomized Controlled Trials (RCTs) over multiple weeks (n = 7). In acute response studies, postprandial outcomes followed the expected physiological patterns, and outcomes measured over 24 h showed no significant differences. For the RCTs, glucose area under the curve during a glucose tolerance test was slightly, but not significantly lower in preprandial PA vs postprandial PA (-0.29 [95 %CI:-0.66, 0.08] mmol/L, I2 = 64.36 %). Subgroup analyses (quality, health status, etc.) did not significantly change the outcomes. In conclusion, we found no differences between preprandial PA versus postprandial PA on glycaemia both after one PA bout as well as after multiple weeks of PA. The studies were of low to moderate quality of evidence as assessed by GRADE, showed contradictive results, included no long-term studies and used various designs and populations. We therefore need better RCTs, with more similar designs, in larger populations and longer follow-up periods (≥12 weeks) to have a final answer on the questions eat first, then exercise, or the reverse?

Exploring the reliability of inpatient EMR algorithms for diabetes identification.

INTRODUCTION: Accurate identification of medical conditions within a real-time inpatient setting is crucial for health systems. Current inpatient comorbidity algorithms rely on integrating various sources of administrative data, but at times, there is a considerable lag in obtaining and linking these data. Our study objective was to develop electronic medical records (EMR) data-based inpatient diabetes phenotyping algorithms. MATERIALS AND METHODS: A chart review on 3040 individuals was completed, and 583 had diabetes. We linked EMR data on these individuals to the International Classification of Disease (ICD) administrative databases. The following EMR-data-based diabetes algorithms were developed: (1) laboratory data, (2) medication data, (3) laboratory and medications data, (4) diabetes concept keywords and (5) diabetes free-text algorithm. Combined algorithms used or statements between the above algorithms. Algorithm performances were measured using chart review as a gold standard. We determined the best-performing algorithm as the one that showed the high performance of sensitivity (SN), and positive predictive value (PPV). RESULTS: The algorithms tested generally performed well: ICD-coded data, SN 0.84, specificity (SP) 0.98, PPV 0.93 and negative predictive value (NPV) 0.96; medication and laboratory algorithm, SN 0.90, SP 0.95, PPV 0.80 and NPV 0.97; all document types algorithm, SN 0.95, SP 0.98, PPV 0.94 and NPV 0.99. DISCUSSION: Free-text data-based diabetes algorithm can yield comparable or superior performance to a commonly used ICD-coded algorithm and could supplement existing methods. These types of inpatient EMR-based algorithms for case identification may become a key method for timely resource planning and care delivery.