Measuring the Influence of Side Effect Expectations, Beliefs, and Incident Side Effects on the Risk for Drug Discontinuation Among Individuals Starting New Medications, a Cross-sectional Study.

Purpose: To measure the impact of beliefs, expectations, side effects, and their combined effects on the risk for medication nonpersistence. Patients and methods: Using a cross-sectional design, individuals from Saskatchewan, Canada who started a new antihypertensive, cholesterol-lowering, or antihyperglycemic medication were surveyed about risk factors for nonpersistence including: (a) beliefs measured by a composite score of three questions asking about the threat of the condition, importance of the drug, and harm of the drug; (b) incident side effects attributed to treatment; and (c) expectations for side effects before starting treatment. Descriptive statistics and logistic regression models were used to quantify the influence of these risk factors on the outcome of nonpersistence. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated. Results: Among 3,029 respondents, 5.8% (n=177) reported nonpersistence within four months after starting the new drug. After adjustment for numerous covariates representing sociodemographics, health-care providers, medication experiences and beliefs, both negative beliefs (OR: 7.26, 95%CI: 4.98-10.59) and incident side effects (OR: 8.00, 95%CI: 5.49-11.68) were associated with the highest odds of nonpersistence with no evidence of interaction. In contrast, expectations for side effects before starting treatment exhibited an important interaction with incident side effects following treatment initiation. Among respondents with incident side effects (n=741, 24.5%), the risk for early nonpersistence was 11.5% if they indicated an expectation for side effects before starting the medication compared to 23.6% if they did not (adjusted OR: 0.38, 95%CI: 0.25-0.60). Conclusion: Expectations for side effects may be a previously unrecognized but important marker of the probability to persist with treatment. A high percentage of new medication users appeared unprepared for the possibility of side effects from their new medication making them less resilient if side effects occur.

Are Guideline-concordant Processes of Care Consistent Across the Rural-Urban Continuum? A Retrospective Cohort Study of Adults Newly Treated for Type 2 Diabetes.

OBJECTIVES: Our aim in this study was to identify the association between place of residence (metropolitan, urban, rural) and guideline-concordant processes of care in the first year of type 2 diabetes management. METHODS: We conducted a retrospective cohort study of new metformin users between April 2015 and March 2020 in Alberta, Canada. Outcomes were identified as guideline-concordant processes of care through the review of clinical practice guidelines and published literature. Using multivariable logistic regression, the following outcomes were examined by place of residence: dispensation of a statin, angiotensin-converting enzyme inhibitor (ACEi) or angiotensin II receptor blocker (ARB), eye examination, glycated hemoglobin (A1C), cholesterol, and kidney function testing. RESULTS: Of 60,222 new metformin users, 67% resided in a metropolitan area, 10% in an urban area, and 23% in a rural area. After confounder adjustment, rural residents were less likely to have a statin dispensed (adjusted odds ratio [aOR] 0.83, 95% confidence interval [CI] 0.79 to 0.87) or undergo cholesterol testing (aOR 0.86, 95% CI 0.83 to 0.90) when compared with metropolitan residents. In contrast, rural residents were more likely to receive A1C and kidney function testing (aOR 1.14, 95% CI 1.08 to 1.21 and aOR 1.17, 95% CI 1.11 to 1.24, respectively). ACEi/ARB use and eye examinations were similar across place of residence. CONCLUSIONS: Processes of care varied by place of residence. Limited cholesterol management in rural areas is concerning because this may lead to increased cardiovascular outcomes.

Association Between Hemoglobin A1c and Development of Cardiovascular Disease in Canadian Men and Women Without Diabetes at Baseline: A Population-Based Study of 608 474 Adults.

BACKGROUND: We examined the association between hemoglobin A1c (HbA1c) and the development of cardiovascular disease (CVD) in men and women, without diabetes or CVD at baseline. METHODS AND RESULTS: This retrospective cohort study included adults aged 40 to <80 years in Alberta, Canada. Men and women were divided into categories based on a random HbA1c during a 3-year enrollment period. The primary outcome of CVD hospitalization and secondary outcome of combined CVD hospitalization/mortality were examined during a 5-year follow-up period until March 31, 2021. A total of 608 474 individuals (55.2% women) were included. Compared with HbA1c 5.0% to 5.4%, men with HbA1c of 5.5% to 5.9% had an increased risk of CVD hospitalization (adjusted hazard ratio [aHR], 1.12 [95% CI, 1.07-1.19]) whereas women did not (aHR, 1.01 [95% CI, 0.95-1.08]). Men and women with HbA1c of 6.0% to 6.4% had a 38% and 17% higher risk and men and women with HbA1c ≥6.5% had a 79% and 51% higher risk of CVD hospitalization, respectively. In addition, HbA1c of 6.0% to 6.4% and HbA1c ≥6.5% were associated with a higher risk (14% and 41%, respectively) of CVD hospitalization/death in men, but HbA1c ≥6.5% was associated with a 24% higher risk only among women. CONCLUSIONS: In both men and women, HbA1c ≥6.0% was associated with an increased risk of CVD and mortality outcomes. The association between CVD and HbA1c levels of 5.5% to 5.9%, considered to be in the "normal" range, highlights the importance of optimizing cardiovascular risk profiles at all levels of glycemia, especially in men.

Rurality is associated with lower likelihood of dipeptidyl peptidase 4 inhibitor use for treatment intensification.

Background: Antihyperglycemic drug utilization studies are conducted frequently and describe the uptake of new drug therapies across may jurisdictions. An increasingly important, yet often absent, aspect of these studies is the impact of rurality on drug utilization. Objectives: The objective of this study was to explore the association between place of residence (rural, urban, metropolitan) and the use of dipeptidyl peptidase 4 inhibitors (DPP-4i) for first treatment intensification of type 2 diabetes. Methods: A retrospective cohort study was conducted from April 1, 2008 to March 31, 2019 of new metformin users. A multivariable logistic regression analysis was performed to determine the association between place of residence (using postal codes) and likelihood of DPP-4i dispensing. Results: After adjusting for confounders, analysis revealed that rural-dwellers are less likely to have a DPP-4i dispensed, compared with metropolitan-dwellers (aOR:0.64; 95%CI:0.61-0.67) and over-time, the uptake in rural areas was slower. Conclusions: This study demonstrates that rurality can have an impact on drug therapy decisions at first treatment intensification, with respect to the utilization of new therapies.

Benzodiazepine use in medical cannabis authorization adult patients from 2013 to 2021: Alberta, Canada.

BACKGROUND: Benzodiazepines are a class of medications that are being frequently prescribed in Canada but carry significant risk of harm. There has been increasing clinical interest on the potential "sparing effects" of medical cannabis as one strategy to reduce benzodiazepine use. The objective of this study as to examine the association of medical cannabis authorization with benzodiazepine usage between 2013 and 2021 in Alberta, Canada. METHODS: A propensity score matched cohort study with patients on regular benzodiazepine treatment authorized to use medical cannabis compared to controls who do not have authorization for medical cannabis. A total of 9690 medically authorized cannabis patients were matched to controls. To assess the effect of medical cannabis use on daily average diazepam equivalence (DDE), interrupted time series (ITS) analysis was used to assess the change in the trend of DDE in the 12 months before and 12 months after the authorization of medical cannabis. RESULTS: Over the follow-up period after medical cannabis authorization, there was no overall change in the DDE use in authorized medical cannabis patients compared to matched controls (- 0.08 DDE, 95% CI: - 0.41 to 0.24). Likewise, the sensitivity analysis showed that, among patients consuming ≤5 mg baseline DDE, there was no change immediately after medical cannabis authorization compared to controls (level change, - 0.04 DDE, 95% CI: - 0.12 to 0.03) per patient as well as in the month-to-month trend change (0.002 DDE, 95% CI: - 0.009 to 0.12) per patient was noted. CONCLUSIONS: This short-term study found that medical cannabis authorization had minimal effects on benzodiazepine use. Our findings may contribute ongoing evidence for clinicians regarding the potential impact of medical cannabis to reduce benzodiazepine use. HIGHLIGHTS: • Medical cannabis authorization had little to no effect on benzodiazepine usage among patients prescribed regular benzodiazepine treatment in Alberta, Canada. • Further clinical research is needed to investigate the potential impact of medical cannabis as an alternative to benzodiazepine medication.

Medical cannabis authorization and risk of emergency department visits and hospitalization due to psychotic disorders: A propensity score-matched cohort study.

Despite evidence showing that recreational cannabis use is associated with a higher risk of psychotic disorders, this risk has not been well characterized for patients using medical cannabis. Therefore, this study assessed the risk of emergency department (ED) visits and hospitalization for psychotic disorders (the study outcome) among adult patients authorized to use medical cannabis. We performed a retrospective cohort study on patients authorized to use medical cannabis in a group of Ontario cannabis clinics between 2014 and 2019. Using clinical and health administrative data, each patient was matched by propensity scores to up to 3 population-based controls. Conditional Cox proportional hazards regressions were used to assess the risk. Among 54,006 cannabis patients matched to 161,265 controls, 39 % were aged ≤50 years, and 54 % were female. Incidence rates for psychotic disorders were 3.00/1000 person-years (95%CI: 2.72-3.32) in the cannabis group and 1.88/1000 person-years (1.75-2.03) in the control group. A significant association was observed, with an adjusted hazard ratio of 1.38 (95%CI: 1.19-1.60) in the total sample and 1.63 (1.40-1.91) in patients without previous psychotic disorders. The results suggest that cannabis authorization should include a benefit-risk assessment of psychotic disorders to minimize the risk of events requiring emergency attention.

Effectiveness of RADAR on diabetes processes of care for First Nations communities in Alberta, Canada.

The epidemic of type-2 diabetes in First Nations communities is tragic. Culturally-appropriate approaches addressing multiple components, focusing beyond glycemic control, are urgently needed. Using an intention-to-treat framework, 13 processes of care indicators were assessed to compare proportions of patients who received care at baseline relative to 2-year follow-up. Clinical improvements were demonstrated across major process of care indicators (e.g. screening, education, and vaccination activities). We found RADAR improved reporting for most diabetes processes of care across seven FN communities and was effective in supporting diabetes care for FN communities, in Alberta Canada.

Defining opioid naïve and implications for monitoring opioid use: A population-based study in Alberta, Canada.

PURPOSE: Reducing initial exposure of "opioid naïve" patients to opioids is a public health priority. Identifying opioid naïve patients is difficult, as numerous definitions are used. The objective is to summarize current definitions and evaluate their impact on opioid naïve measures in Alberta. METHODS: An exploratory data analysis of the literature was conducted over the last 10 years to identify definitions commonly used in the literature to define opioid naïve. Then, using these definitions as a guide, we descriptively report the proportion of patients in Alberta between 2017 and 2021 who would be considered as opioid naïve using these definitions and all opioid dispensing data. RESULTS: Three categories of definitions were broadly identified: (1) no opioid use within the previous 30 days/6 months/1 year, based on dispensation date; (2) no opioid use based on dispensation date plus days of supply; and, (3) exclusion of codeine from Definitions 1 and 2. Applying these definitions to the Alberta population showed a very wide range in the proportion who would be considered as opioid naïve. Overall, 36.4% of Albertans (n = 1 551 075) had an opioid dispensation in 2017-2021. The average age was 46.6 ± 18.8 and 52.8% were female. The proportion of opioid naïve were most affected by the "opioid free" period, with 97.4%, 83.2%, and 65.6% being classified as opioid naïve using time windows from Definition 1 (30 days, 6 months, 1 year of no prior opioid use). Definitions 2 and 3 did not materially change the results. Further extending the "opioid free" period to 2 years showed only 35% were opioid naïve. CONCLUSIONS: The most convenient definition for "opioid naïve" was the use of an "opioid free" period. The choice of window would depend on how the information may be used to assistant in clinical decisions with longer windows more likely to reflect true opioid naïve patients. Irrespective of definition used, a large proportion of opioid users would be considered opioid naïve in Alberta.

Reduced incidence of diabetes during the COVID-19 pandemic in Alberta: A time-segmented longitudinal study of Alberta's Tomorrow Project.

AIM: To characterize the impact of the COVID-19 pandemic on diabetes diagnosis using data from Alberta's Tomorrow Project (ATP), a population-based cohort study of chronic diseases in Alberta, Canada. MATERIALS AND METHODS: The ATP participants who were free of diabetes on 1 April 2018 were included in the study. A time-segmented regression model was used to compare incidence rates of diabetes before the COVID-19 pandemic, during the first two COVID-19 states of emergency, and in the period when the state of emergency was relaxed, after adjusting for seasonality, sociodemographic factors, socioeconomic status, and lifestyle behaviours. RESULTS: Among 43 705 ATP participants free of diabetes (65.5% females, age 60.4 ± 9.5 years in 2018), the rate of diabetes was 4.75 per 1000 person-year (PY) during the COVID-19 pandemic (up to 31 March 2021), which was 32% lower (95% confidence interval [CI] 21%, 42%; p < 0.001) than pre-pandemic (6.98 per 1000 PY for the period 1 April 2018 to 16 March 2020). In multivariable regression analysis, the first COVID-19 state of emergency (first wave) was associated with an 87.3% (95% CI -98.6%, 13.9%; p = 0.07) reduction in diabetes diagnosis; this decreasing trend was sustained to the second COVID-19 state of emergency and no substantial rebound (increase) was observed when the COVID-19 state of emergency was relaxed. CONCLUSIONS: The COVID-19 public health emergencies had a negative impact on diabetes diagnosis in Alberta. The reduction in diabetes diagnosis was likely due to province-wide health service disruptions during the COVID-19 pandemic. Systematic plans to close the post-COVID-19 diagnostic gap are required in diabetes to avoid substantial downstream sequelae of undiagnosed disease.

Medical Cannabis and Its Efficacy/Effectiveness for the Treatment of Low-Back Pain: a Systematic Review.

PURPOSE OF REVIEW: This systematic review aims to inform the current state of evidence about the efficacy and effectiveness of medical cannabis use for the treatment of LBP, specifically on pain levels and overall opioid use for LBP. Searches were conducted in MEDLINE (PubMed), Embase, and CINAHL. The search was limited to the past 10 years (2011-2021). Study inclusion was determined by the critical appraisal process using the Joanna Briggs Institute framework. Only English language articles were included. Participant demographics included all adult individuals with LBP who were prescribed medical cannabis for LBP and may be concurrently using opioids for their LBP. Study quality and the risk of bias were both evaluated. A narrative synthesis approach was used. RECENT FINDINGS: A total of twelve studies were included in the synthesis: one randomized controlled trial (RCT), six observational studies (one prospective, four retrospective, and one cross-over), and five case studies. All study results, except for the RCT, indicated a decrease in LBP levels or opioid use over time after medical cannabis use. The RCT reported no statistically significant difference in LBP between cannabis and placebo groups. Low back pain (LBP) affects 568 million people worldwide. In the United States, LBP treatment represents more than half of regular opioid users. With the opioid epidemic, alternative methods, particularly medical cannabis, is now increasingly sought by practicing physicians and patients. Due to its infancy, there is minimal high-quality evidence to support medical cannabis use as a first line treatment for LBP.

Post-initiation predictors of discontinuation of the sodium-glucose cotransporter-2 inhibitors: A comparative cohort study from the United Kingdom.

AIMS: To assess post-initiation predictors of discontinuation of sodium-glucose cotransporter-2 (SGLT2) inhibitors compared to dipeptidyl-peptidase-4 (DPP-4) inhibitors in the United Kingdom. MATERIALS AND METHODS: We conducted a comparative population-based retrospective cohort study using primary care data from the UK Clinical Practice Research Datalink (CPRD) with linked data to hospital and death records. We included new metformin users who initiated either SGLT2 inhibitors or DPP-4 inhibitors between January 2013 and October 2019. The main outcome was treatment discontinuation, defined as the first 90-day gap after the estimated treatment end date. We used a series of extended Cox models to assess which time-dependent predictors were associated with treatment discontinuation. To test if the hazard ratio of discontinuation for each predictor was statistically different between SGLT2 and DPP-4 inhibitors, an exposure-predictor interaction term was added to each model. RESULTS: There were 2550 new users of SGLT2 inhibitors and 8195 new users of DPP-4 inhibitors. Approximately 69% of SGLT2 inhibitor and 74% of DPP-4 inhibitor users had discontinued treatment by the end of follow-up. Occurrence of fractures after treatment initiation was a significant predictor of discontinuation of SGLT2 inhibitors (hazard ratio [HR] 4.13, 95% confidence interval [CI] 2.12-8.06) but not DPP-4 inhibitors (HR 0.93, 95% CI 0.79-1.11). The rate of treatment discontinuation was significantly higher for those with low estimated glomerular filtration rate and minimal contact with the healthcare system. Efficacy endpoints, such as heart failure and glycated haemoglobin level, were not associated with treatment discontinuation. CONCLUSIONS: Our findings reflect some discrepancy between the available evidence and prescribing behaviour for SGLT2 inhibitors.

Predicting falls-related admissions in older adults in Alberta, Canada: a machine-learning falls prevention tool developed using population administrative health data.

OBJECTIVE: To construct a machine-learning (ML) model for health systems with organised falls prevention programmes to identify older adults at risk for fall-related admissions. DESIGN: This prognostic study used population-level administrative health data to develop an ML prediction model. SETTING: This study took place in Alberta, Canada during 2018-2019. PARTICIPANTS: Albertans aged 65 and older with at least one prior admission. Those with palliative conditions or emigrated out of Alberta were excluded. EXPOSURE: Unit of analysis was the individual person. MAIN OUTCOMES/MEASURES: We identified fall-related admissions. A CatBoost model was developed on 2018 data to predict risk of fall-related emergency department visits or hospitalisations. Temporal validation was done using 2019 data to evaluate model performance. We reported discrimination, calibration and other relevant metrics measured at the end of 2019 on both ranked predictions and predicted probability thresholds. A cost-savings simulation was performed using 2019 data. RESULTS: Final number of study participants was 224 445. The validation set had 203 584 participants with 19 389 fall-related events (9.5% pretest probability) and an ML model c-statistic of 0.70. The highest ranked predictions had post-test probabilities ranging from 40% to 50%. Net benefit analysis presented mixed results with some net benefit using the ML model in the 6%-30% range. The top 50 percentile of predicted risks represented nearly $C60 million in health system costs related to falls. Intervening on the top 25 or 50 percentiles of predicted risk could realise substantial (up to $C16 million) savings. CONCLUSION: ML prediction models based on population-level administrative data can assist health systems with fall prevention programmes identify older adults at risk of fall-related admissions and reduce costs. ML predictions based on ranked predictions or probability thresholds could guide subsequent interventions to mitigate fall risks. Increased access to diverse forms of data could improve ML performance and further reduce costs.

Nonfasting remnant cholesterol and cardiovascular disease risk prediction in Albertans: a prospective cohort study.

BACKGROUND: European studies have shown that nonfasting remnant cholesterol can be a strong predictor of cardiovascular disease risk and may contribute to identifying residual risk; however, Canadian data are lacking on nonfasting remnant cholesterol. In this study, we aimed to determine the relation between nonfasting remnant cholesterol, low-density lipoprotein (LDL) cholesterol and cardiovascular disease among people in Alberta. METHODS: In this retrospective analysis, we used data from Alberta's Tomorrow Project, a large prospective cohort that enrolled Albertans aged 35-69 years (2000-2015). Participants with consent to data linkage, with complete nonfasting lipid data and without existing cardiovascular disease were included. The nonfasting remnant cholesterol and LDL cholesterol relation with a composite cardiovascular disease outcome of major incident cardiovascular diagnoses, ascertained by linking to Alberta Health databases, was determined by multivariable logistic regression, adjusting for age, sex, statin use, comorbidities, and LDL cholesterol or remnant cholesterol. RESULTS: The final sample of 13 988 participants was 69.4% female, and the mean age was 61.8 (standard deviation [SD] 9.7) years. Follow-up time was approximately 15 years. Mean remnant cholesterol was significantly higher among individuals with versus without cardiovascular disease (0.87 [SD 0.40] mmol/L v. 0.78 [SD 0.38] mmol/L, standardized mean difference [SMD] -0.24), and mean LDL cholesterol was significantly lower (2.69 [SD 0.93] mmol/L v. 2.88 [SD 0.84] mmol/L, SMD 0.21). The odds of incident composite cardiovascular disease were significantly increased per mmol/L increase in remnant cholesterol (adjusted odds ratio [OR] 1.48, 95% confidence interval [CI] 1.27-1.73) but significantly decreased per mmol/L increase in LDL cholesterol (adjusted OR 0.73, 95% CI 0.68-0.79). INTERPRETATION: In this large Albertan cohort of predominantly older females, nonfasting remnant cholesterol had a positive relation with cardiovascular disease incidence, whereas LDL cholesterol did not. These findings support the clinical utility of measuring non-fasting remnant cholesterol to detect cardiovascular disease risk.

Effectiveness of RADAR: An Innovative Model to Organize Diabetes Care in First Nations Communities.

Challenges exist for the management of diabetes care in First Nations populations. RADAR (Reorganizing the Approach to Diabetes through the Application of Registries) is a culturally appropriate, innovative care model that incorporates a disease registry and electronic health record for local care provision with remote coordination, tailored for First Nations people. This study assessed the effectiveness of RADAR on patient outcomes and diabetes care organization in participating communities in Alberta, Canada. It revealed significant improvements in outcomes after 2 years, with 91% of patients achieving a primary combined end point of a 10% improvement in or persistence at target for A1C, systolic blood pressure, and/or LDL cholesterol. Qualitative assessment showed that diabetes care organization also improved. These multimethod findings support tailored diabetes care practices in First Nations populations.

Pharmacists' chronic disease management in chronic obstructive pulmonary disease: Effect on health services utilization.

BACKGROUND: There is limited real-world evidence on evaluation of chronic disease management initiatives provided by pharmacists to patients with chronic obstructive pulmonary disease (COPD). OBJECTIVE: To evaluate changes in COPD-related health care resource utilization between patients with COPD who had pharmacist-provided chronic disease management (comprehensive annual care plan [CACP]) vs those who did not have CACP. METHODS: Patients with COPD who received a CACP in Alberta between 2012 and 2015 were identified within the Alberta Health administrative data. Each of these patients were matched with 2 control patients with COPD based on age, sex, provider, date of service, and qualifying comorbidities. Controlled interrupted time series analysis was used to evaluate changes in COPD-specific hospitalizations, emergency department (ED) visits, physician visits, and claims for pulmonary function test. Immediate and temporal changes were calculated for the difference in outcomes 1 year before and 1 year after receiving the CACP for the intervention group and matched controls. RESULTS: Eligible patients (N = 74,365), of whom 28,795 (38.7%) had received CACPs, were matched to a total of 45,570 controls. In 1 year after the CACPs implementation, the number of COPD-related hospitalization visits decreased by 174 (95% CI = -270.8 to -76.5) per 10,000 patients per month, COPD-related ED visits decreased by 123 (95% CI = -294.9 to 49.6) per 10,000 per month, general practitioner visits decreased by 153.9 per 10,000 per month (95% CI = -293.3 to -14.5), and pulmonary function test claims decreased by 19.5 per 10,000 per month (95% CI = -70.1 to 31.2) when compared with the matched controls. However, significant difference between the 2 groups was found for COPD-related hospitalizations only, which was not confirmed by the sensitivity analysis. CONCLUSIONS: In patients with COPD who were provided with care plans by their community pharmacists, there was no significant decrease in COPD-related hospitalizations or ED visits over 1 year compared with the matched controls who did not have a pharmacist-provided care plan. Physician visits and pulmonary function tests did not change significantly for those who had CACP compared with those who did not. There is a need to further understand how care plans can better impact other outcomes that are important in COPD management. DISCLOSURES: This study was supported by a grant from the M.S.I. Foundation (Grant#895) based in Alberta, Canada. Dr Bhutani has consulted for Astra Zeneca, GlaxoSmithKline, Boehringer Ingelheim, Valeo, Covis, and Sanofi. The authors declare no other relevant conflicts of interest or financial relationships. This study is based on data provided by Alberta Health. The interpretation and conclusions of the results are those of the researchers and do not necessarily represent the views of the government of Alberta nor the funder (M.S.I. Foundation). All authors meet criteria for authorship as recommended by the International Committee of Medical Journal Editors.

Analgesic Use Among Adults with a Trauma-Related Emergency Department Visit: A Retrospective Cohort Study from Alberta, Canada.

INTRODUCTION: A better understanding of current acute pain-driven analgesic practices within the emergency department (ED) and upon discharge will provide foundational information in this area, as few studies have been conducted in Canada. METHODS: Administrative data were used to identify adults with a trauma-related ED visit in the Edmonton area in 2017/2018. Characteristics of the ED visit included time from initial contact to analgesic administration, type of analgesics dispensed during and upon being discharged home directly from the ED (≤ 7 days after), and patient characteristics. RESULTS: A total of 50,950 ED visits by 40,505 adults with trauma were included. Analgesics were administered in 24.2% of visits, of which non-opioids were dispensed in 77.0% and opioids were dispensed in 49.0%. Time to analgesic initiation occurred more than 2 h after first contact. Upon discharge, 11.5% received a non-opioid and 15.2% received an opioid analgesic, among whom 18.5% received a daily dose ≥ 50 morphine milligram equivalents (MME) and 30.2% received > 7 days of supply. Three hundred and seventeen adults newly met criteria for chronic opioid use after the ED visit, among whom 43.5% received an opioid dispensation upon discharge; of these individuals, 26.8% had a daily dose ≥ 50 MME and 65.9% received > 7 days of supply. CONCLUSIONS: Findings can be used to inform optimization of analgesic pharmacotherapy practices for the treatment of acute pain, which may include reducing the time to initiation of analgesics in the ED, as well as close consideration of recommendations for acute pain management upon discharge to provide ideal patient-centered, evidence-informed care.

Non-fasting lipids and cardiovascular disease in those with and without diabetes in Alberta's Tomorrow Project: A prospective cohort study.

AIMS: Non-fasting remnant cholesterol (RC) is a novel marker of cardiovascular disease (CVD) risk, however, data on this relationship in Canadians with diabetes (at high risk of CVD) is lacking. The objective of this analysis was to determine the relationship of RC with CVD in individuals with and without diabetes in the Alberta's Tomorrow Project (ATP) cohort. METHODS: Non-fasting lipid data collected as part of the ATP was linked to administrative health records (October 2000-March 2015) to ascertain incident CVD and prevalent diabetes. Participants without prevalent CVD or incident diabetes and who had complete, non-negative non-fasting lipid data collected with triglycerides <4.5 mmol/L were included (n = 13,631). The relationship between non-fasting RC and incident CVD diagnoses was assessed by Cox proportional hazards regression, after stratification by diabetes status. RESULTS: Participants were 69.8% women with a mean age of 61.6 ± 9.7 years, and 6.5% had prevalent diabetes. Non-fasting RC was higher in participants with diabetes compared to those without (mean 0.94 ± 0.41 mmol/L vs. 0.77 ± 0.38 mmol/L, p < 0.0001) and was associated with increased risk of incident CVD among those without diabetes (adjusted hazard ratio (aHR) 1.22, 95% CI 1.03-1.43, p = 0.02). Although a similar trend was observed in participants with diabetes it did not reach statistical significance (aHR 1.31, 95% CI 0.84-2.05, p = 0.23). CONCLUSIONS: Elevated non-fasting RC predicted increased CVD risk in middle and older-aged adults without diabetes; similar trends were observed in participants with diabetes and require further testing in a larger sample.

Dairy product consumption and risk of non-alcoholic fatty liver disease: A systematic review and meta-analysis of observational studies.

BACKGROUND AND AIMS: It is unclear whether regular consumption of dairy products is associated with the risk of developing non-alcoholic fatty liver disease (NAFLD). Thus, we conducted a systematic review followed by a meta-analysis of studies reporting on the association of dairy consumption with NAFLD risk. METHODS AND RESULTS: We comprehensively searched PubMed, Web of Science, and Scopus for observational studies that evaluated the association between dairy intake and NAFLD likelihood that were published before September 1, 2022. The reported odds ratios (ORs) of fully adjusted models and their 95% confidence intervals (CIs) were pooled using a random-effects model for the meta-analysis. Out of 1206 articles retrieved, 11 observational studies, including 43,649 participants and 11,020 cases, were included. Pooled OR indicated a significant association between dairy intake and NAFLD (OR = 0.90; 95% CI: 0.83, 0.98; I2 = 67.8%, n = 11). Pooled ORs revealed that milk (OR: 0.86; 95% CI: 0.78, 0.95; I2 = 65.7%, n = 6), yogurt (OR: 0.88; 95% CI: 0.82; I2 = 0.0%, n = 4), and high-fat dairy (OR: 0.38; 95% CI: 0.19, 0.75; I2 = 0.0%, n = 5) consumption was inversely associated with NAFLD while cheese was not linked to NAFLD risk. CONCLUSION: We observed that consumption of dairy products is linked to a reduced risk of developing NAFLD. Overall, the data in the source articles is of low to moderate quality; therefore, further observational studies are required to support the current findings (PROSPERO Reg. number: CRD42022319028).

Impact of Comorbidity on Hospitalization and Emergency Room Visits in Adults With Diabetes: A Longitudinal Study of Alberta's Tomorrow Project.

OBJECTIVE: Our aim in this study was to characterize the impact of comorbidities, including number and types, on hospitalization and emergency room (ER) visits in people with diabetes. METHODS: Incident cases of diabetes from Alberta's Tomorrow Project with >24 months of follow-up were included. Comorbidities, classified by Elixhauser conditions, were updated every 12 months after diagnosis. A generalized estimating equation model was used to examine the association (by incidence rate ratio [IRR]) between time-varying comorbidity profile and hospitalization and ER visits per year of follow-up after adjusting for sociodemographic factors, lifestyle behaviours, and historic health-care utilization in the previous 5 years. RESULTS: Among 2,110 incident cases of diabetes (51.0% females; median age at diagnosis: 59.5 years; median follow-up: 7.19 years), the average number of Elixhauser comorbidities was 1.9±1.6 in the first year of diagnosis and 3.3±2.0 in year 15 after diagnosis. The number of comorbidities in the previous year was positively associated with risk of hospitalization (IRR=1.33 [95% confidence interval {CI}: 1.04 to 1.70] and 2.14 [95% CI: 1.67 to 2.74] for 1 or 2 and ≥2 comorbidities, respectively) and ER visits (IRR=1.31 [95% CI: 1.15 to 1.50] and 1.62 [95% CI: 1.41 to 1.87] for 1 or 2 and ≥2 comorbidities, respectively) in the subsequent year. Cardiovascular diseases, peripheral vascular diseases, cancer, liver disease, fluid and electrolyte disorders, and depression were the conditions most typically associated with increased health-care utilization. CONCLUSIONS: The number of comorbidities was a major risk factor of health-care utilization for people with diabetes. Vascular diseases, cancer, and conditions closely related to diabetic frailty (e.g. fluid and electrolyte disorders and depression) were the main drivers of hospital care and ER visits.

A method for generating synthetic longitudinal health data.

Getting access to administrative health data for research purposes is a difficult and time-consuming process due to increasingly demanding privacy regulations. An alternative method for sharing administrative health data would be to share synthetic datasets where the records do not correspond to real individuals, but the patterns and relationships seen in the data are reproduced. This paper assesses the feasibility of generating synthetic administrative health data using a recurrent deep learning model. Our data comes from 120,000 individuals from Alberta Health's administrative health database. We assess how similar our synthetic data is to the real data using utility assessments that assess the structure and general patterns in the data as well as by recreating a specific analysis in the real data commonly applied to this type of administrative health data. We also assess the privacy risks associated with the use of this synthetic dataset. Generic utility assessments that used Hellinger distance to quantify the difference in distributions between real and synthetic datasets for event types (0.027), attributes (mean 0.0417), Markov transition matrices (order 1 mean absolute difference: 0.0896, sd: 0.159; order 2: mean Hellinger distance 0.2195, sd: 0.2724), the Hellinger distance between the joint distributions was 0.352, and the similarity of random cohorts generated from real and synthetic data had a mean Hellinger distance of 0.3 and mean Euclidean distance of 0.064, indicating small differences between the distributions in the real data and the synthetic data. By applying a realistic analysis to both real and synthetic datasets, Cox regression hazard ratios achieved a mean confidence interval overlap of 68% for adjusted hazard ratios among 5 key outcomes of interest, indicating synthetic data produces similar analytic results to real data. The privacy assessment concluded that the attribution disclosure risk associated with this synthetic dataset was substantially less than the typical 0.09 acceptable risk threshold. Based on these metrics our results show that our synthetic data is suitably similar to the real data and could be shared for research purposes thereby alleviating concerns associated with the sharing of real data in some circumstances.