Traditional methods hold their ground against machine learning in predicting potentially inappropriate medication use in older adults.

OBJECTIVES: Machine learning methods have gained much attention in health sciences for predicting various health outcomes but are scarcely used in pharmacoepidemiology. The ability to identify predictors of suboptimal medication use is essential for conducting interventions aimed at improving medication outcomes. It remains uncertain whether machine learning methods could enhance the identification of potentially inappropriate medication use among older adults compared to traditional methods. The aim of this study was 1) to compare the performances of machine learning models in predicting use of potentially inappropriate medications and 2) to quantify and compare the relative importance of predictors in a population of community dwelling older adults (>65 years) in the province of Quebec, Canada. METHODS: We used the Quebec Integrated Chronic Disease Surveillance System and selected a cohort of 1,105,295 older adults of whom 533,719 were potentially inappropriate medication users. Potentially inappropriate medications were defined according to the Beers list. We compared performances between five popular machine learning models (gradient boosting machines, logistic regression, naïve Bayes, neural networks, and random forests) based on ROC curves and other performance criteria, using a set of sociodemographic and medical predictors. RESULTS: No model clearly outperformed the others. All models except neural networks were in agreement regarding the top predictors (sex and anxiety-depressive disorders and schizophrenia) and the bottom predictors (rurality and social and material deprivation indices). CONCLUSIONS: Including other types of predictors (e.g., unstructured data) may be more useful for increasing performance in prediction of potentially inappropriate medication use.

Multimorbidity prevalence and health outcome prediction: assessing the impact of lookback periods, disease count, and definition criteria in health administrative data at the population-based level.

BACKGROUND: Health administrative databases play a crucial role in population-level multimorbidity surveillance. Determining the appropriate retrospective or lookback period (LP) for observing prevalent and newly diagnosed diseases in administrative data presents challenge in estimating multimorbidity prevalence and predicting health outcome. The aim of this population-based study was to assess the impact of LP on multimorbidity prevalence and health outcomes prediction across three multimorbidity definitions, three lists of diseases used for multimorbidity assessment, and six health outcomes. METHODS: We conducted a population-based study including all individuals ages > 65 years on April 1st, 2019, in Québec, Canada. We considered three lists of diseases labeled according to the number of chronic conditions it considered: (1) L60 included 60 chronic conditions from the International Classification of Diseases (ICD); (2) L20 included a core of 20 chronic conditions; and (3) L31 included 31 chronic conditions from the Charlson and Elixhauser indices. For each list, we: (1) measured multimorbidity prevalence for three multimorbidity definitions (at least two [MM2+], three [MM3+] or four (MM4+) chronic conditions); and (2) evaluated capacity (c-statistic) to predict 1-year outcomes (mortality, hospitalisation, polypharmacy, and general practitioner, specialist, or emergency department visits) using LPs ranging from 1 to 20 years. RESULTS: Increase in multimorbidity prevalence decelerated after 5-10 years (e.g., MM2+, L31: LP = 1y: 14%, LP = 10y: 58%, LP = 20y: 69%). Within the 5-10 years LP range, predictive performance was better for L20 than L60 (e.g., LP = 7y, mortality, MM3+: L20 [0.798;95%CI:0.797-0.800] vs. L60 [0.779; 95%CI:0.777-0.781]) and typically better for MM3 + and MM4 + definitions (e.g., LP = 7y, mortality, L60: MM4+ [0.788;95%CI:0.786-0.790] vs. MM2+ [0.768;95%CI:0.766-0.770]). CONCLUSIONS: In our databases, ten years of data was required for stable estimation of multimorbidity prevalence. Within that range, the L20 and multimorbidity definitions MM3 + or MM4 + reached maximal predictive performance.

A Bootstrap Approach for Evaluating Uncertainty in the Number of Groups Identified by Latent Class Growth Models.

The use of longitudinal finite mixture models such as group-based trajectory modeling has seen a sharp increase during the last few decades in the medical literature. However, these methods have been criticized, especially because of the data-driven modeling process, which involves statistical decision-making. In this paper, we propose an approach that uses the bootstrap to sample observations with replacement from the original data to validate the number of groups identified and to quantify the uncertainty in the number of groups. The method allows investigation of the statistical validity and uncertainty of the groups identified in the original data by checking to see whether the same solution is also found across the bootstrap samples. In a simulation study, we examined whether the bootstrap-estimated variability in the number of groups reflected the replicationwise variability. We evaluated the ability of 3 commonly used adequacy criteria (average posterior probability, odds of correct classification, and relative entropy) to identify uncertainty in the number of groups. Finally, we illustrate the proposed approach using data from the Quebec Integrated Chronic Disease Surveillance System to identify longitudinal medication patterns between 2015 and 2018 in older adults with diabetes.

An Alternative Perspective on the Robust Poisson Method for Estimating Risk or Prevalence Ratios.

The robust Poisson method is becoming increasingly popular when estimating the association of exposures with a binary outcome. Unlike the logistic regression model, the robust Poisson method yields results that can be interpreted as risk or prevalence ratios. In addition, it does not suffer from frequent nonconvergence problems such as the most common implementations of maximum likelihood estimators of the log-binomial model. However, using a Poisson distribution to model a binary outcome may seem counterintuitive. Methodologic papers have often presented this as a good approximation to the more natural binomial distribution. In this article, we provide an alternative perspective to the robust Poisson method based on the semiparametric theory. This perspective highlights that the robust Poisson method does not require assuming a Poisson distribution for the outcome. In fact, the method only assumes a log-linear relation between the risk or prevalence of the outcome and the explanatory variables. This assumption and the consequences of its violation are discussed. We also provide suggestions to reduce the risk of violating the modeling assumption. Additionally, we discuss and contrast the robust Poisson method with other approaches for estimating exposure risk or prevalence ratios. See video abstract at, http://links.lww.com/EDE/B987 .

Trends in Brain Research: A Bibliometric Analysis.

BACKGROUND: Bibliometrics methods have allowed researchers to assess the popularity of brain research through the ever-growing number of brain-related research papers. While many topics of brain research have been covered by previous studies, there is no comprehensive overview of the evolution of brain research and its various specialties and funding practices over a long period of time. OBJECTIVE: This paper aims to (1) determine how brain research has evolved over time in terms of number of papers, (2) countries' relative and absolute positioning in terms of papers and impact, and (3) how those various trends vary by area. METHODS: Using a list of validated keywords, we extracted brain-related articles and journals indexed in the Web of Science over the 1991-2020 period, for a total of 2,467,708 papers. We used three indicators to perform: number of papers, specialization, and research impact. RESULTS: Our results show that over the past 30 years, the number of brain-related papers has grown at a faster pace than science in general, with China being at the forefront of this growth. Different patterns of specialization among countries and funders were also underlined. Finally, the NIH, the European Commission, the National Natural Science Foundation of China, the UK Medical Research Council, and the German Research Foundation were found to be among the top funders. CONCLUSION: Despite data-related limitations, our findings provide a large-scope snapshot of the evolution of brain research and its funding, which may be used as a baseline for future studies on these topics.

Time trends in social contacts of individuals according to comorbidity and vaccination status, before and during the COVID-19 pandemic.

BACKGROUND: As we are confronted with more transmissible/severe variants with immune escape and the waning of vaccine efficacy, it is particularly relevant to understand how the social contacts of individuals at greater risk of COVID-19 complications evolved over time. We described time trends in social contacts of individuals according to comorbidity and vaccination status before and during the first three waves of the COVID-19 pandemic in Quebec, Canada. METHODS: We used data from CONNECT, a repeated cross-sectional population-based survey of social contacts conducted before (2018/2019) and during the pandemic (April 2020 to July 2021). We recruited non-institutionalized adults from Quebec, Canada, by random digit dialling. We used a self-administered web-based questionnaire to measure the number of social contacts of participants (two-way conversation at a distance ≤2 m or a physical contact, irrespective of masking). We compared the mean number of contacts/day according to the comorbidity status of participants (pre-existing medical conditions with symptoms/medication in the past 12 months) and 1-dose vaccination status during the third wave. All analyses were performed using weighted generalized linear models with a Poisson distribution and robust variance. RESULTS: A total of 1441 and 5185 participants with and without comorbidities, respectively, were included in the analyses. Contacts significantly decreased from a mean of 6.1 (95%CI 4.9-7.3) before the pandemic to 3.2 (95%CI 2.5-3.9) during the first wave among individuals with comorbidities and from 8.1 (95%CI 7.3-9.0) to 2.7 (95%CI 2.2-3.2) among individuals without comorbidities. Individuals with comorbidities maintained fewer contacts than those without comorbidities in the second wave, with a significant difference before the Christmas 2020/2021 holidays (2.9 (95%CI 2.5-3.2) vs 3.9 (95%CI 3.5-4.3); P<0.001). During the third wave, contacts were similar for individuals with (4.1, 95%CI 3.4-4.7) and without comorbidities (4.5, 95%CI 4.1-4.9; P=0.27). This could be partly explained by individuals with comorbidities vaccinated with their first dose who increased their contacts to the level of those without comorbidities. CONCLUSIONS: It will be important to closely monitor COVID-19-related outcomes and social contacts by comorbidity and vaccination status to inform targeted or population-based interventions (e.g., booster doses of the vaccine).

Changes in Polypharmacy and Psychotropic Medication Use After Diagnosis of Major Neurocognitive Disorders: A Population-based Study in Québec, Canada.

BACKGROUND: Older adults with major neurocognitive disorder (MNCD) are often exposed to polypharmacy. We aimed to assess the prescribing and discontinuation patterns of medications following diagnosis of MNCD among community-dwelling older adults. METHODS: Using the Quebec Integrated Chronic Disease Surveillance System, we conducted a population-based cohort study comparing 1-year prediagnosis and postdiagnosis use of medications between a group of individuals older than 65 years newly diagnosed with MNCD in 2016-2017 and a control group without MNCD. The difference-in-difference method was used to estimate the prediagnosis and postdiagnosis variation in the number of medications prescribed and in the proportion of psychotropic and anticholinergic medication users. RESULTS: In the MNCD group, the mean number of medications used (excluding Alzheimer disease treatments) increased by 1.25 in the year after the diagnosis. The respective increase was 0.45 in the control group, yielding an adjusted difference-in-differences of 0.81 (95% confidence interval: 0.74; 0.87) between groups. The adjusted difference-in-differences in the proportions of antipsychotic, antidepressant, and anticholinergic medication users was 13.2% (12.5; 13.9), 7.1% (6.5; 7.7), and 3.8% (3.1; 4.6), respectively. CONCLUSIONS: The medication burden among older adults tends to increase in the year following a diagnosis of MNCD. The use of antipsychotics and antidepressants may explain a part of the observed increase.

Trends in benzodiazepine and alternative hypnotic use in relation with multimorbidity among older adults in Quebec, Canada.

BACKGROUND: Benzodiazepines and other hypnotic alternatives are associated with increased risks of adverse events. Heightened awareness of risks may have changed prescribing habits over the years. However, these trends are not fully described, especially in vulnerable people such as multimorbid older adults. OBJECTIVE: We aimed to describe the annual prevalence of benzodiazepine and other hypnotic use in relation to multimorbidity among older adults in the province of Quebec, Canada, from 2000 to 2016. METHOD: We conducted a population-based study using the Quebec Integrated Chronic Disease Surveillance System. We included all individuals aged ≥66 years covered by the public drug plan. For each year, we evaluated the sex- and age-standardized proportion of benzodiazepine and other hypnotic users, defined as individuals with at least one drug claim in the year. We stratified our results according to multimorbidity and used log-binomial regression to study trends. RESULTS: The proportion of individuals using benzodiazepines decreased from 34.8% in 2000 to 24.8% in 2016 (p for trend <0.001). Multimorbid people (≥2 chronic diseases) remained the highest users over the years, with 43.3% and 30.6% of them being users in 2000 and 2016, respectively. Conversely, the proportion of users increased for other hypnotics, particularly for trazodone and quetiapine, rising from 5.4% to 8.4% (p < 0.001), and especially among multimorbid individuals (from 7.4% to 11.6%). CONCLUSION: Older adults used benzodiazepines less frequently but quetiapine and trazodone more frequently in recent years. The use of these medications, particularly in multimorbid people at risk of adverse events, must be addressed.

Multimorbidity measures from health administrative data using ICD system codes: A systematic review.

BACKGROUND: We aimed to identify and characterize adult population-based multimorbidity measures using health administrative data and the International Classification of Diseases (ICD) codes for disease identification. METHODS: We performed a narrative systematic review of studies using or describing development or validation of multimorbidity measures. We compared the number of diseases included in the measures, the process of data extraction (case definition) and the validation process. We assessed the methodological robustness using eight criteria, five based on general criteria for indicators (AIRE instrument) and three multimorbidity-specific criteria. RESULTS: Twenty-two multimorbidity measures were identified. The number of diseases they included ranged from 5 to 84 (median = 20), with 19 measures including both physical and mental conditions. Diseases were identified using ICD codes extracted from inpatient and outpatient data (18/22) and sometimes including drug claims (10/22). The validation process relied mainly on the capacity of the measures to predict health outcome (5/22), or on the validation of each individual disease against a gold standard (8/22). Six multimorbidity measures met at least six of the eight robustness criteria assessed. CONCLUSION: There is significant heterogeneity among the measures used to assess multimorbidity in administrative databases, and about a third are of low to moderate quality. A more consensual approach to the number of diseases or groups of diseases included in multimorbidity measures may improve comparison between regions, and potentially provide better control for multimorbidity-related confounding in studies.

Global-scale dispersal and connectivity in mangroves.

Dispersal provides a key mechanism for geographical range shifts in response to changing environmental conditions. For mangroves, which are highly susceptible to climate change, the spatial scale of dispersal remains largely unknown. Here we use a high-resolution, eddy- and tide-resolving numerical ocean model to simulate mangrove propagule dispersal across the global ocean and generate connectivity matrices between mangrove habitats using a range of floating periods. We find high rates of along-coast transport and transoceanic dispersal across the Atlantic, Pacific, and Indian Oceans. No connectivity is observed between populations on either side of the American and African continents. Archipelagos, such as the Galapagos and those found in Polynesia, Micronesia, and Melanesia, act as critical stepping-stones for dispersal across the Pacific Ocean. Direct and reciprocal dispersal routes across the Indian Ocean via the South Equatorial Current and seasonally reversing monsoon currents, respectively, allow connectivity between western Indian Ocean and Indo-West Pacific sites. We demonstrate the isolation of the Hawaii Islands and help explain the presence of mangroves on the latitudinal outlier Bermuda. Finally, we find that dispersal distance and connectivity are highly sensitive to the minimum and maximum floating periods. We anticipate that our findings will guide future research agendas to quantify biophysical factors that determine mangrove dispersal and connectivity, including the influence of ocean surface water properties on metabolic processes and buoyancy behavior, which may determine the potential of viably reaching a suitable habitat. Ultimately, this will lead to a better understanding of global mangrove species distributions and their response to changing climate conditions.

Psychiatric disorders in emerging adults with diabetes transitioning to adult care: A retrospective cohort study.

AIMS: During transition from paediatric to adult diabetes care, adolescents with diabetes are at increased risk of psychiatric disorders compared with those without diabetes. Prolonged gaps between the last paediatric and first adult diabetes care visit are associated with higher perceived stress and lower life satisfaction. We assessed the effect of a gap (>180 days) in establishing adult diabetes care on the risk of psychiatric disorders and determined other risk factors associated with psychiatric disorders during the transfer to adult care. METHODS: Using provincial health administrative databases, we conducted a retrospective cohort study of individuals from Québec, Canada, diagnosed with diabetes between ages 1 and 15 years in 1997-2015. These individuals were followed from 6 months after their last paediatric visit until age 25 years. We used multivariable Cox proportional hazard models to determine the association of gap in care with psychiatric disorders risk. RESULTS: Among 1772 youth with diabetes, 740 (42%) had a gap in care. There was a non-statistically significant association between gap in care and mood disorders diagnosed in the emergency department or hospital (hazard ratio [HR] 1.38, 95% confidence interval [CI]: [0.92, 2.07]). Older age at transfer, recent birth year and higher number of all-cause emergency department visits in the year before transfer increased the risks of psychiatric disorders. CONCLUSIONS: Prolonged gaps in care during transfer to adult care are common and may be associated with increased psychiatric disorder risk. Developmental factors associated with adolescence and emerging adulthood may further amplify this risk.

Does socio-economic status influence the effect of multimorbidity on the frequent use of ambulatory care services in a universal healthcare system? A population-based cohort study.

BACKGROUND: Frequent healthcare users place a significant burden on health systems. Factors such as multimorbidity and low socioeconomic status have been associated with high use of ambulatory care services (emergency rooms, general practitioners and specialist physicians). However, the combined effect of these two factors remains poorly understood. Our goal was to determine whether the risk of being a frequent user of ambulatory care is influenced by an interaction between multimorbidity and socioeconomic status, in an entire population covered by a universal health system. METHODS: Using a linkage of administrative databases, we conducted a population-based cohort study of all adults in Quebec, Canada. Multimorbidity (defined as the number of different diseases) was assessed over a two-year period from April 1st 2012 to March 31st 2014 and socioeconomic status was estimated using a validated material deprivation index. Frequents users for a particular category of ambulatory services had a number of visits among the highest 5% in the total population during the 2014-15 fiscal year. We used ajusted logistic regressions to model the association between frequent use of health services and multimorbidity, depending on socioeconomic status. RESULTS: Frequent users (5.1% of the population) were responsible for 25.2% of all ambulatory care visits. The lower the socioeconomic status, the higher the burden of chronic diseases, and the more frequent the visits to emergency departments and general practitioners. Socioeconomic status modified the association between multimorbidity and frequent visits to specialist physicians: those with low socioeconomic status visited specialist physicians less often. The difference in adjusted proportions of frequent use between the most deprived and the least deprived individuals varied from 0.1% for those without any chronic disease to 5.1% for those with four or more chronic diseases. No such differences in proportions were observed for frequent visits to an emergency room or frequent visits to a general practitioner. CONCLUSION: Even in a universal healthcare system, the gap between socioeconomic groups widens as a function of multimorbidity with regard to visits to the specialist physicians. Further studies are needed to better understand the differential use of specialized care by the most deprived individuals.

Exploring polypharmacy with artificial intelligence: data analysis protocol.

BACKGROUND: Polypharmacy is common among older adults and it represents a public health concern, due to the negative health impacts potentially associated with the use of several medications. However, the large number of medication combinations and sequences of use makes it complicated for traditional statistical methods to predict which therapy is genuinely associated with health outcomes. The project aims to use artificial intelligence (AI) to determine the quality of polypharmacy among older adults with chronic diseases in the province of Québec, Canada. METHODS: We will use data from the Quebec Integrated Chronic Disease Surveillance System (QICDSS). QICDSS contains information about prescribed medications in older adults in Quebec collected over 20 years. It also includes diagnostic codes and procedures, and sociodemographic data linked through a unique identification number for each individual. Our research will be structured around three interconnected research axes: AI, Health, and Law&Ethics. The AI research axis will develop algorithms for finding frequent patterns of medication use that correlate with health events, considering data locality and temporality (explainable AI or XAI). The Health research axis will translate these patterns into polypharmacy indicators relevant to public health surveillance and clinicians. The Law&Ethics axis will assess the social acceptability of the algorithms developed using AI tools and the indicators developed by the Heath axis and will ensure that the developed indicators neither discriminate against any population group nor increase the disparities already present in the use of medications. DISCUSSION: The multi-disciplinary research team consists of specialists in AI, health data, statistics, pharmacy, public health, law, and ethics, which will allow investigation of polypharmacy from different points of view and will contribute to a deeper understanding of the clinical, social, and ethical issues surrounding polypharmacy and its surveillance, as well as the use of AI for health record data. The project results will be disseminated to the scientific community, healthcare professionals, and public health decision-makers in peer-reviewed publications, scientific meetings, and reports. The diffusion of the results will ensure the confidentiality of individual data.

One-year persistence of potentially inappropriate medication use in older adults: A population-based study.

AIMS: To assess the 1-year persistence of potentially inappropriate medication (PIM) use and identify associated factors in community-dwelling older adults in Quebec, Canada. METHODS: A population-based cohort study was conducted using the Quebec Integrated Chronic Disease Surveillance System. Individuals insured by the public drug plan and aged ≥66 years who initiated a PIM between 1 April 2014 and 31 March 2015 were followed-up for 1 year. PIMs were identified using the 2015 Beers criteria. One-year persistence of PIM use was defined as continuous treatment with any PIM, without interruption for more than 60 days between prescriptions refills. Poisson regression models were performed to identify factors associated with 1-year persistence of any PIM. RESULTS: In total, 25.1% of PIM initiators were persistent at 1 year. In non-persistent individuals, the median time to PIM discontinuation was 31 days (interquartile range 21-92). Individuals were more persistent at 1 year with antipsychotics (43.9%), long-duration sulphonylureas (40.2%), antiarrhythmics/immediate-release nifedipine (36.5%) and proton pump inhibitors (36.0%). Factors significantly associated with persistence were an increased age, being a man and having a high number of medications and chronic diseases, especially dementia, diabetes and cardiovascular diseases. CONCLUSIONS: One-quarter of community-dwelling older adults are continuously exposed to PIMs. To optimize medication prescribing in the older population, further interventions are needed to limit the use of PIMs most likely to be continued, especially in individuals most at risk of being persistent and also particularly vulnerable to adverse events.

Potentially inappropriate medications in older adults: a population-based cohort study.

BACKGROUND: Non-optimal medication use among older adults is a public health concern. A concrete picture of potentially inappropriate medication (PIM) use is imperative to ensure optimal medication use. OBJECTIVE: To assess the prevalence of PIMs in community-dwelling older adults and identify associated factors. METHODS: A retrospective population-based cohort study was conducted using the Quebec Integrated Chronic Disease Surveillance System (QICDSS). The QICDSS includes data on drug claims for community-dwelling older adults with chronic diseases or at risk of developing chronic diseases aged ≥65 years who are insured by the public drug insurance plan. Individuals aged ≥66 years who were continuously insured with the public drug plan between 1 April 2014 and 31 March 2016 were included. PIMs were defined using the 2015 Beers criteria. We conducted multivariate robust Poisson regression analyses to explore factors associated with PIM use. RESULTS: A total of 1 105 295 individuals were included. Of these, 48.3% were prescribed at least one PIM. The most prevalent PIMs were benzodiazepines (25.7%), proton-pump inhibitors (21.3%), antipsychotics (5.6%), antidepressants (5.0%) and long-duration sulfonylureas (3.3%). Factors associated with PIM exposure included being a woman [rate ratio (RR): 1.20; 95% confidence interval (CI): 1.20-1.21], increased number of medications and having a high number of chronic diseases, especially mental disorders (RR: 1.50; 95% CI: 1.49-1.51). CONCLUSION: Almost one out of two community-dwelling older adults use a PIM. It is imperative to reduce the use of PIMs, by limiting their prescription and by promoting their deprescribing, which necessitates not only the active involvement of prescribers but also patients.

Evaluation of the Bio-Rad Geenius HIV 1/2 Assay as Part of a Confirmatory HIV Testing Strategy for Quebec, Canada: Comparison with Western Blot and Inno-Lia Assays.

The rapid confirmatory Bio-Rad Geenius HIV 1/2 assay was evaluated as an alternative to the HIV-1 Western blot (WB) confirmatory assay. A total of 370 retrospective samples collected from 356 patients were tested. Sensitivity of the Geenius assay to detect HIV-1 and HIV-2 infections was 100% and 97%, respectively, and that of the WB assay was 86% and 39%, respectively. Geenius reduced the number of indeterminate results by 85% and exhibited a differentiation capacity for HIV-1 and HIV-2 of 100% and 89%, respectively. Three of 10 patients presenting with an early HIV infection (1 to 2 weeks before seroconversion by WB) were positive using Geenius. None of the HIV-negative samples were positive using Geenius or WB. However, 7% and 10% of them were indeterminate with Geenius and WB, respectively, leading to a specificity rate of 93% for Geenius and 90% for WB. Ninety cadaveric samples (54 negative, 23 HIV-1 positive, and 3 HIV-1 indeterminate) were tested with Geenius, leading to a sensitivity of 100%, a specificity of 96%, and an indeterminate rate of 4%. Our results indicate that the Bio-Rad Geenius HIV 1/2 rapid test exhibits better sensitivity to detect HIV-1 infections and better performance than WB to confirm and differentiate between HIV-1 and HIV-2 infections. The performance of this new confirmatory assay to detect early infections, to reduce the rate of indeterminate status, and to confirm HIV-1 infection in cadaveric blood samples makes Geenius a potent reliable alternative to the WB.

Combined impacts of multimorbidity and mental disorders on frequent emergency department visits: a retrospective cohort study in Quebec, Canada.

BACKGROUND: Multimorbidity and mental disorders are independently associated with frequent visits to the emergency department (≥ 3 visits/yr), but their interaction has been little studied. We aimed to measure the interaction between mental disorders and physical multimorbidity with respect to frequent visits to the emergency department. METHODS: We conducted a population-based cohort study of adults in Quebec from 2012 to 2016, using the Quebec Integrated Chronic Disease Surveillance System. We assessed multimorbidity as the number of physical illnesses and mental disorders as serious (psychotic or bipolar disorders), common or absent, using data from 2012 to 2014. We counted emergency department visits from 2014 to 2015. We used logistic regression to estimate interaction on frequent visits to the emergency department from 2 perspectives: of public health (additive scale as differences in risk) and of individual patients (multiplicative scale as odds ratios). RESULTS: Each additional physical illness was associated with a greater increase in the absolute risk of frequent visits to the emergency department for people with mental disorders. Between 0 and ≥ 4 physical conditions, the absolute risk increased more for individuals with serious mental disorders (16.2%) than common (15.3%) or no disorders (11.4%). On the relative scale, for people with no mental disorders and ≥ 4 physical conditions, odds of frequent visits to the emergency department were 6.2 (95% confidence interval [CI] 6.08-6.35) times the odds for people with no physical conditions. For individuals with common and serious mental illnesses, corresponding odds ratios were 4.75 (95% CI 4.60-4.90) and 3.7 (95% CI 3.18-3.57), respectively. INTERPRETATION: Mental disorders interact with physical multimorbidity to increase the odds of frequent visits to the emergency department. More research is needed on interventions that promote high-quality care for mental illness, especially in the context of physical multimorbidity.

Polypharmacy among Older Individuals with COPD: Trends between 2000 and 2015 in Quebec, Canada.

The treatment of chronic obstructive pulmonary disease (COPD) and concomitant diseases requires several medications. Yet there is little data on how the pharmacological burden progressed over time among older individuals with COPD. We aimed to: 1) describe the proportion of older adults with COPD in Quebec, Canada, that were exposed to polypharmacy (≥10, ≥15 or ≥20 medications/year) between 2000 and 2015; 2) calculate the proportion of individuals receiving specific prescriptions for COPD during this period. We conducted a population-based cohort study with the Quebec Integrated Chronic Disease Surveillance System. Individuals aged ≥66 years with COPD and covered by the universal public drug plan were included. We calculated the total number of drugs used at least once by each individual during each of the studied years, and used age-standardized proportions to compare proportions of users between the years. The average number of drugs used increased from 12.0 in 2000 to 14.8 in 2015. The proportion of individuals exposed to polypharmacy increased (≥10 drugs: 62.0% to 74.6%;≥15 drugs: 31.2% to 45.4%; ≥20 drugs: 12.3% to 22.4%). The proportion of individuals receiving long-acting bronchodilators increased from 18.7% in 2000 to 69.6% in 2015. The use of short-acting bronchodilators decreased from 81.5% to 67.9%, and that of inhaled corticosteroids from 60.6% to 26.0%. The proportion of users of methylxanthines decreased from 15.0% to 1.9%. Older individuals with COPD are increasingly exposed to polypharmacy. Identifying which polypharmacy is beneficial is a priority.

Veal Liver as Food Vehicle for Human Campylobacter Infections.

A matched case-control study in Quebec, Canada, evaluated consumption of veal liver as a risk factor for campylobacteriosis. Campylobacter was identified in 28 of 97 veal livers collected concurrently from slaughterhouses and retailers. Veal liver was associated with human Campylobacter infection, particularly when consumed undercooked.

The human fetal adrenal produces cortisol but no detectable aldosterone throughout the second trimester.

BACKGROUND: Human fetal adrenal glands are highly active and, with the placenta, regulate circulating progesterone, estrogen and corticosteroids in the fetus. At birth the adrenals are essential for neonate salt retention through secretion of aldosterone, while adequate glucocorticoids are required to prevent adrenal insufficiency. The objective of this study was to carry out the first comprehensive analysis of adrenal steroid levels and steroidogenic enzyme expression in normal second trimester human fetuses. METHODS: This was an observational study of steroids, messenger RNA transcripts and proteins in adrenals from up to 109 second trimester fetuses (11 weeks to 21 weeks) at the Universities of Aberdeen and Glasgow. The study design was balanced to show effects of maternal smoking. RESULTS: Concentrations of 19 intra-adrenal steroids were quantified using liquid chromatography and mass spectrometry. Pregnenolone was the most abundant steroid while levels of 17α-hydroxyprogesterone, dehydroepiandrosterone sulphate (DHEAS) and progesterone were also high. Cortisol was present in all adrenals, but aldosterone was undetected and Δ4 androgens were low/undetected. CYP17A1, CYP21A2 and CYP11A1 were all highly expressed and the proteins localized to the adrenal fetal zone. There was low-level expression of HSD3B and CYP11B2, with HSD3B located mainly in the definitive zone. Maternal smoking altered fetal plasma adrenocorticotropic hormone (ACTH) (P = 0.052) and intra-adrenal progesterone, 17α-hydroxyprogesterone and 16α-hydroxyprogesterone, but not plasma or intra-adrenal cortisol, or intra-adrenal DHEAS. Fetal adrenal GATA6 and NR5A1 were increased by maternal smoking. CONCLUSIONS: The human fetal adrenal gland produces cortisol but very low levels of Δ4 androgens and no detectable aldosterone throughout the second trimester. The presence of cortisol in fetal adrenals suggests that adrenal regulation of circulating fetal ACTH remains a factor in development of congenital adrenal hyperplasia during the second trimester, while a relative lack of aldosterone explains the salt-wasting disorders frequently seen in extreme pre-term neonates. Finally, maternal smoking may alter fetal adrenal sensitivity to ACTH, which could have knock-on effects on post-natal health.