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.

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.

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.

The Association of Medical Cannabis Use with Pain Levels and Opioid Use in Illinois' Opioid Alternative Pilot Program.

OBJECTIVE: The state of Illinois' Opioid Alternative Pilot Program (OAPP) is the first and only official harm-reduction program in the US to address the opioid crisis via facilitation of safe and legal access to medical cannabis. This study evaluates the association of medical cannabis use with pain level and frequency of opioid use in the first cohort of OAPP participants in 2019. METHODS: A survey was sent OAPP enrollees between February and July 2019. Cannabis users (n = 626) were compared to non-users (n = 234) to determine whether there was an association between cannabis use and self-reported (a) pain level and (b) frequency of opioid use. Backward stepwise regression models were used. RESULTS: A total of 860 participants was included in the analysis. Overall, 75% of the study sample reported pain as their primary medical symptom, and 67% of cannabis users reported having a disability. The mean difference in pain level between cannabis users and non-users was 4.5 units (on a 100-point scale) higher among cannabis users than non-users (p = 0.03); and cannabis use was statistically associated with pain level. High-frequency opioid users had lower odds of reporting cannabis use within the past year than low/no opioid users. CONCLUSIONS: Although there was a statistical association between cannabis use and pain, the difference of 4.5 points in pain level between users and non-users was too small to reflect a clinically meaningful relative difference. This study may provide useful information to providers and clinicians about how the OAPP and similar programs may reduce opioid use and improve health outcomes.

Changes in Sarcopenia Status Predict Survival Among Patients with Resectable Esophageal Cancer.

BACKGROUND: Sarcopenia is a predictor of survival in patients with esophageal cancer. The objective of this research was to obtain insight into how changes in sarcopenia influence survival in resectable esophageal cancer. PATIENTS AND METHODS: A retrospective cohort of patients with esophageal cancer undergoing tri-modality therapy was selected. Body composition parameters from the staging, post-neoadjuvant, and 1-year surveillance computed tomography (CT) scans were calculated. Overall survival (OS) and disease-free survival (DFS) were evaluated using the Kaplan-Meier method and log-rank test, as well as multivariable Cox-proportional hazards models. RESULTS: Of 141 patients, 118 had images at all three timepoints. The median DFS and OS were 33.2 [95% confidence interval (CI) 19.1-73.7] and 34.5 (95% CI 23.1-57.6) months, respectively. Sarcopenia classified by the staging CT was present in 20 (17.0%) patients. This changed to 45 (38.1%) patients by the post-neoadjuvant scan, and 44 (37.3%) by the surveillance scan. In multivariable analysis, sarcopenia at the post-neoadjuvant scan was significantly associated with OS [hazards ratio (HR) 2.65, 95% CI 1.59-4.40; p < 0.001] and DFS (HR 1.80, 95% CI 1.03-3.13; p = 0.038). The net change in skeletal muscle index was associated with OS (HR 0.93, 95% CI 0.90-0.97; p < 0.001) and DFS (HR 0.94, 95% CI 0.91-0.98; p = 0.001). CONCLUSIONS: Patients who develop sarcopenia as a consequence of skeletal muscle wasting during neoadjuvant therapy are at risk for worse DFS and OS. Patients who have a net loss of muscle over time may be at high risk for early disease recurrence.

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.

Sarcopenia in Lung Cancer: A Narrative Review.

It has been over 10 years since the relationship between sarcopenia and lung cancer was first explored. Since then, sarcopenia research has progressed substantially, and the prognostic value of this condition is becoming increasingly apparent. Prior systematic reviews and meta-analyses have established sarcopenia to be negatively associated with disease-free and overall-survival, as well as a major risk factor for post-operative complications. The bulk of the literature has explored sarcopenia in the resectable setting, with less emphasis placed on studies evaluating this condition in advanced disease. In this up-to-date review, an examination of the literature exploring the association between sarcopenia and long-term outcomes in advanced lung cancer is provided. We further explore the association between adverse events of medical therapy and the role of sarcopenia as a predictor of tumor response. Finally, the interventions on sarcopenia and cancer cachexia are reviewed, with an emphasis placed on prospective studies.

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.

Severity of in vivo corticospinal tract degeneration is associated with survival in amyotrophic lateral sclerosis: a longitudinal, multicohort study.

BACKGROUND AND PURPOSE: This study sought to evaluate the relationship of progressive corticospinal tract (CST) degeneration with survival in patients with amyotrophic lateral sclerosis (ALS). METHODS: Forty-one ALS patients and 42 healthy controls were prospectively recruited from the Canadian ALS Neuroimaging Consortium. Magnetic resonance imaging scanning and clinical evaluations were performed on participants at three serial visits with 4-month intervals. Texture analysis was performed on T1-weighted magnetic resonance imaging scans and the texture feature 'autocorrelation' was quantified. Whole-brain group-level comparisons were performed between patient subgroups. Linear mixed models were used to evaluate longitudinal progression. Region-of-interest and 3D voxel-wise Cox proportional-hazards regression models were constructed for survival prediction. For all survival analyses, a second independent cohort was used for model validation. RESULTS: Autocorrelation of the bilateral CST was increased at baseline and progressively increased over time at a faster rate in ALS short survivors. Cox proportional-hazards regression analyses revealed autocorrelation of the CST as a significant predictor of survival at 5 years follow-up (hazard ratio 1.28, p = 0.005). Similarly, voxel-wise whole-brain survival analyses revealed that increased autocorrelation of the CST was associated with shorter survival. ALS patients stratified by median autocorrelation in the CST had significantly different survival times using the Kaplan-Meier curve and log-rank tests (χ2  = 7.402, p = 0.007). CONCLUSIONS: Severity of cerebral degeneration is associated with survival in ALS. CST degeneration progresses faster in subgroups of patients with shorter survival. Neuroimaging holds promise as a tool to improve patient management and facilitation of clinical trials.

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.

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).

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.

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.

Invasive Pneumococcal Disease and Long-Term Mortality Rates in Adults, Alberta, Canada.

The relationship between increased short-term mortality rates after invasive pneumococcal disease (IPD) has been frequently studied. However, the relationship between IPD and long-term mortality rates is unknown. IPD patients in Alberta, Canada, had clinical data collected that were linked to administrative databases. We used Cox proportional hazards modeling, and the primary outcome was time to all-cause deaths. First IPD events were identified in 4,522 patients, who had a median follow-up of 3.2 years (interquartile range 0.8‒9.1 years). Overall all-cause mortality rates were consistently higher among cases than controls at 30 days (adjusted hazard ratio [aHR] 3.75, 95% CI 3.29-4.28), 30‒90 days (aHR 1.56, 95% CI 1.27‒1.93), and >90 days (aHR 1.43, 95% CI 1.33-1.54). IPD increases risk for short, intermediate, and long-term mortality rates regardless of age, sex, or concurrent conditions. These findings can help clinicians focus on postdischarge patient plans to limit long-term effects after acute IPD infection.

Cost-utility analysis of normothermic machine perfusion compared to static cold storage in liver transplantation in the Canadian setting.

To estimate the incremental cost-effectiveness of a liver transplant program that utilizes normothermic machine perfusion (NMP) alongside static cold storage (SCS) compared to SCS alone (control). A Markov model compared strategies (NMP vs. control) using 1-year cycle lengths over a 5-year time horizon from the public healthcare payer perspective. Primary micro-costing data from a single center retrospective trial were applied along with utility values from literature sources. Transition probabilities were deduced using the retrospective trial cohort, local transplant data, and supplemented with literature values. Scenario and probabilistic sensitivity analysis (PSA) were conducted. The NMP strategy was cost-effective in comparison to the control strategy, which was dominated. The mean cost for NMP was $456 455 (2021 US$) and the control was $519 222. The NMP strategy had greater incremental quality-adjusted life years (QALYs) gains over 5 years compared to the control, with 3.48 versus 3.17, respectively. The overarching results remained unchanged in scenario analysis. In PSA, NMP was cost-effective in 63% of iterations at a willingness-to-pay threshold of $40 941. The addition of NMP to a liver transplant program results in greater QALY gains and is cost-effective from the public healthcare payer perspective.

Sarcopenia Determined by Skeletal Muscle Index Predicts Overall Survival, Disease-free Survival, and Postoperative Complications in Resectable Esophageal Cancer: A Systematic Review and Meta-analysis.

BACKGROUND: Sarcopenia has been identified as a prognostic factor among certain types of cancer. In esophageal cancer, patients are at increased risk of malnutrition and sarcopenia, ultimately contributing to poor outcomes. A systematic review was conducted to determine whether sarcopenia, defined by the skeletal muscle index, is predictive of overall survival, disease-free survival, and postoperative complications in resectable esophageal cancer. MATERIALS AND METHODS: A systematic search of MEDLINE, EMBASE, Scopus, Web of Science, and Cochrane Library was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines up until January 2021. The primary outcome was overall survival; secondary outcomes included disease-free survival, pulmonary complications, and anastomotic leak. RESULTS: Twenty-one studies (4 prospective; 17 retrospective; 3966 patients) were included. Sarcopenia was present in 1940 (48.1%) patients and was associated with lower overall survival [hazard ratio (HR): 1.56; 95% confidence interval (CI): 1.25-1.95; P <0.00001; I2 =71%] and disease-free survival (HR: 1.73; 95% CI: 1.04-2.87; P =0.03; I2 =51%). A decrease in skeletal muscle index, independent of sarcopenia status, was associated with lower overall survival (HR: 1.81; 95% CI: 1.20-2.73; P =0.005; I2 =92%). Sarcopenia was associated with increased odds of pulmonary complications (odds ratio: 1.86; 95% CI: 1.29-2.66; P =0.0008; I2 =41%) and increased odds of anastomotic leak (odds ratio: 1.46; 95% CI: 1.11-1.93; P =0.008; I2 =0%). CONCLUSIONS: Sarcopenia is a predictor of overall survival, disease-free survival, and postoperative complications in patients with resectable esophageal cancer. Studies on the modifiability of sarcopenia in the preoperative period will help determine the utility of nutritional interventions.

Distinct patterns of progressive gray and white matter degeneration in amyotrophic lateral sclerosis.

Progressive cerebral degeneration in amyotrophic lateral sclerosis (ALS) remains poorly understood. Here, three-dimensional (3D) texture analysis was used to study longitudinal gray and white matter cerebral degeneration in ALS from routine T1-weighted magnetic resonance imaging (MRI). Participants were included from the Canadian ALS Neuroimaging Consortium (CALSNIC) who underwent up to three clinical assessments and MRI at four-month intervals, up to 8 months after baseline (T0 ). Three-dimensional maps of the texture feature autocorrelation were computed from T1-weighted images. One hundred and nineteen controls and 137 ALS patients were included, with 81 controls and 84 ALS patients returning for at least one follow-up. At baseline, texture changes in ALS patients were detected in the motor cortex, corticospinal tract, insular cortex, and bilateral frontal and temporal white matter compared to controls. Longitudinal comparison of texture maps between T0 and Tmax (last follow-up visit) within ALS patients showed progressive texture alterations in the temporal white matter, insula, and internal capsule. Additionally, when compared to controls, ALS patients had greater texture changes in the frontal and temporal structures at Tmax than at T0 . In subgroup analysis, slow progressing ALS patients had greater progressive texture change in the internal capsule than the fast progressing patients. Contrastingly, fast progressing patients had greater progressive texture changes in the precentral gyrus. These findings suggest that the characteristic longitudinal gray matter pathology in ALS is the progressive involvement of frontotemporal regions rather than a worsening pathology within the motor cortex, and that phenotypic variability is associated with distinct progressive spatial pathology.

Predicting 30-Day Readmissions in Patients With Heart Failure Using Administrative Data: A Machine Learning Approach.

BACKGROUND: We sought to develop machine learning (ML) models trained on administrative data which predict risk of readmission in patients with heart failure and to evaluate and compare the ML model with the currently used LaCE score using clinically informative metrics. METHODS AND RESULTS: This prognostic study was conducted in Alberta, Canada, on 9845 patients with confirmed heart failure admitted to hospital between 2012 and 2019. The outcome was unplanned all-cause hospital readmission within 30 days of discharge. We used 80% of the data for the ML model development and 20% for independent validation. We reported, using the validation set, c-statistics (area under the receiver operating characteristic curves)and performance metrics (likelihood ratio, positive predictive values) for the XGBoost model and a modified LaCE score within their respective predictive thresholds. Boosted tree-based classifiers had higher area under the receiver operating characteristic curves (0.65 for XGBoost) compared with others (0.58 for neural networks) and 0.57 for the modified LaCE. Within the predicted threshold range of the XGBoost classifier, the positive likelihood ratio was 1.00 at the low end of predicted risk and 6.12 at the high end, resulting in a positive predictive value (post-test probability) range of 21%-62%; the pretest probability of readmission was 20.9% using prevalence. The corresponding positive likelihood ratios and positive predictive values across LaCE score thresholds were 1.00-1.20 and 21%-24%, respectively. CONCLUSIONS: Despite predicting readmissions better than the LaCE, even the best ML model trained on administrative health data (XGBoost) did not provide substantially informative prediction performance as it only generated a moderate shift from pre to post-test probability. Health systems wishing to deploy such a tool should consider training ML models with additional data. Adding other techniques like natural language processing, along with ML, to use other clinical information (like chart notes) might improve prediction performance.

Five comparative cohorts to assess the risk of genital tract infections associated with sodium-glucose cotransporter-2 inhibitors initiation in type 2 diabetes mellitus.

AIM: To assess the association between SGLT-2 inhibitors initiation and genital tract infections (GTIs) among patients with type 2 diabetes. METHODS: A population-based cohort study using administrative healthcare data from Alberta, Canada, and primary care data from the UK's Clinical Practice Research Datalink (CPRD). Among new metformin users, we identified new users of SGLT-2 inhibitors and five active comparator cohorts (new users of dipeptidyl peptidase-4 (DPP-4) inhibitors, sulfonylureas (SU), glucagon-like peptide-1 receptor agonists (GLP-1 RA), thiazolidinediones (TZD) and insulin). The outcome of interest was a composite GTI outcome. In each cohort, we used high-dimensional propensity score matching to adjust for confounding and conditional Cox proportional hazards regression to estimate the hazard ratios (HR). We used random-effects meta-analysis to combine aggregate data across databases. RESULTS: The risk of GTI was higher for SGLT-2 inhibitors users compared with DPP4inhibitor users (pooled HR 2.68, 95% CI 2.19 3.28), SU users (3.29, 2.62-4.13), GLP1-RA users (2.51, 1.90-3.31), TZD users (4.17, 2.46-7.08) and insulin users (1.86, 1.27-2.73). CONCLUSION: In five comparative cohorts, SGLT-2 inhibitors initiation is associated with a higher risk of GTIs. These findings from real-world data are consistent with placebo-controlled randomized controlled trials.

Generalized Anxiety Disorder 7-Item (GAD-7) Scores in Medically Authorized Cannabis Patients-Ontario and Alberta, Canada.

OBJECTIVES: Despite increasing rates of legalization of medical cannabis worldwide, the current evidence available on its effect on mental health outcomes including anxiety is of mixed results. This study assesses the effect of medical cannabis on generalized anxiety disorder 7-item (GAD-7) scores in adult patients between 2014 and 2019 in Ontario and Alberta, Canada. METHODS: An observational cohort study of adults authorized to use medical cannabis. The GAD-7 was administered at the time of the first visit to the clinic and subsequently over the follow-up time period of up to 3.2 years. Overall changes in GAD-7 scores were computed (mean change) and categorized as: no change (<1 point); improvement; or worsening-over time. RESULTS: A total of 37,303 patients had initial GAD-7 scores recorded and 5,075 (13.6%) patients had subsequent GAD-7 follow-up scores. The average age was 54.2 years (SD 15.7 years), 46.0% were male, and 45.6% noted anxiety symptoms at the baseline. Average GAD-7 scores were 9.11 (SD 6.6) at the baseline and after an average of 282 days of follow-up (SD 264) the average final GAD-7 score recorded was 9.04 (SD 6.6): mean change -0.23 (95% CI, -0.28 to -0.17, t[5,074]: -8.19, p-value <0.001). A total of 4,607 patients (90.8%) had no change in GAD-7 score from their initial to final follow-up, 188 (3.7%) had a clinically significant decrease, and 64 (1.3%) noted a clinically significant increase in their GAD-7 scores. CONCLUSIONS: Overall, there was a statistically significant decrease in GAD-7 scores over time (in particular, in the 6-12-month period). However, this change did not meet the threshold to be considered clinically significant. Thus, we did not detect clinical improvements or detriment in GAD-7 scores in medically authorized cannabis patients. However, future well-controlled clinical trials are needed to fully examine risks or benefits associated with using medical cannabis to treat anxiety conditions.