COVID-19 Mortality Risk in Down Syndrome: Results From a Cohort Study Of 8 Million Adults

Background: At the start of the coronavirus disease 2019 (COVID-19) pandemic, many national health organizations emphasized nonpharmacologic interventions, such as quarantining or physical distancing. In the United Kingdom, strict self-isolation (“shielding”) was advised for those deemed to be clinically extremely vulnerable on the basis of the presence of selected medical conditions or at the discretion of their general practitioners. Down syndrome features on neither the U.K. shielding list nor the U.S. Centers for Disease Control and Prevention list of groups at “increased risk.” However, it is associated with immune dysfunction, congenital heart disease, and pulmonary pathology and, given its prevalence, may be a relevant albeit unconfirmed risk factor for severe COVID-1

Preliminary results of a feasibility study of the use of information technology for identification of suspected colorectal cancer in primary care: the CREDIBLE study

This is the final version of the article. Available from Cancer Research UK/Nature Publishing Group via the DOI in this record.BACKGROUND: We report the findings of a feasibility study using information technology to search electronic primary care records and to identify patients with possible colorectal cancer. METHODS: An algorithm to flag up patients meeting National Institute for Health and Care Excellence (NICE) urgent referral criteria for suspected colorectal cancer was developed and incorporated into clinical audit software. This periodically flagged up such patients aged 60 to 79 years. General practitioners (GPs) reviewed flagged-up patients and decided on further clinical management. We report the numbers of patients identified and the numbers that GPs judged to need further review, investigations or referral to secondary care and the final diagnoses. RESULTS: Between January 2012 and March 2014, 19,580 records of patients aged 60 to 79 years were searched in 20 UK general practices, flagging up 809 patients who met urgent referral criteria. The majority of the patients had microcytic anaemia (236 (29%)) or rectal bleeding (205 (25%)). A total of 274 (34%) patients needed further clinical review of their records; 199 (73%) of these were invited for GP consultation, and 116 attended, of whom 42 were referred to secondary care. Colon cancer was diagnosed in 10 out of 809 (1.2%) flagged-up patients and polyps in a further 28 out of 809 (3.5%). CONCLUSIONS: It is technically possible to identify patients with colorectal cancer by searching electronic patient records.We acknowledge the General Practitioners, practice nurses, practice managers and administrative staff who supported this study, our trial co-ordinator Marie Crook, Anthony Ingold who was one of our patient representatives and MSDi for their support in developing the software algorithm. We also acknowledge the support of the National Institute for Health Research Clinical Research Network. This study was funded by the National Awareness and Early Diagnosis Initiative (NAEDI). TM is partly funded by the National Institute for Health Research (NIHR) through the Collaborations for Leadership in Applied Health Research and Care for the West Midlands (CLAHRC-WM) programme

Trends in antidepressant prescriptions in children and young people in England, 1998-2017: protocol of a cohort study using linked primary care and secondary care datasets

Introduction Increasing numbers of children and young people (CYP) are receiving prescriptions for antidepressants. This is the protocol of a study aiming to describe the trends and variation in antidepressant prescriptions in CYP in England, and to examine the indications for the prescriptions recorded and whether there was contact with secondary care specialists on or around the time of the first antidepressant prescription. Methods and analysis All eligible CYP aged between 5-17 years in 1998-2017 from the QResearch primary care database will be included. Incidence and prevalence rates of any antidepressant prescription in each year will be calculated. We will examine four different antidepressant classes: selective serotonin reuptake inhibitors (SSRIs), tricyclic and related antidepressants (TCAs), serotonin and norepinephrine reuptake inhibitors (SNRIs) and other antidepressants, as well as for individual drugs. Linked primary and secondary care data (hospital episode statistics) in the year before and up to six months after the first antidepressant prescription will be examined for CYP whose first antidepressant prescription was in 2006-2017. Whether there were records of indications and being seen by psychiatric or paediatric specialists will be identified. Trends over time and differences by region, deprivation and ethnicity will be examined using Poisson regression. Discussion This large, population-based study will give an up-to-date picture of antidepressant prescribing in CYP and identify any variation. Understanding what indications are recorded when CYP are being prescribed antidepressants, and whether this was done in partnership with secondary care specialists, will provide evidence of whether appropriate guidelines are being followed

Secondary care specialist visits made by children and young people prescribed antidepressants in primary care: A descriptive study using the QResearch database

© 2020 The Author(s). Background: Antidepressants may be used to manage a number of conditions in children and young people including depression, anxiety, and obsessive-compulsive disorder. UK guidelines for the treatment of depression in children and young people recommend that antidepressants should only be initiated following assessment and diagnosis by a child and adolescent psychiatrist. The aim of this study was to summarise visits to mental health specialists and indications recorded around the time of antidepressant initiation in children and young people in UK primary care. Methods: The study used linked English primary care electronic health records and Hospital Episode Statistics secondary care data. The study included 5-17-year-olds first prescribed antidepressants between January 2006 and December 2017. Records of visits to paediatric or psychiatric specialists and potential indications (from a pre-specified list) were extracted. Events were counted if recorded less than 12 months before or 6 months after the first antidepressant prescription. Results were stratified by first antidepressant type (all, selective serotonin reuptake inhibitors (SSRIs), tricyclic and related antidepressants) and by age group (5-11 years, 12-17 years). Results: In total, 33,031 5-17-year-olds were included. Of these, 12,149 (37%) had a record of visiting a paediatrician or a psychiatric specialist in the specified time window. The majority of recorded visits (7154, 22%) were to paediatricians. Of those prescribed SSRIs, 5463/22,130 (25%) had a record of visiting a child and adolescent psychiatrist. Overall, 17,972 (54%) patients had a record of at least one of the pre-specified indications. Depression was the most frequently recorded indication (12,501, 38%), followed by anxiety (4155, 13%). Conclusions: The results suggest many children and young people are being prescribed antidepressants without the recommended involvement of a relevant specialist. These findings may justify both greater training for GPs in child and adolescent mental health and greater access to specialist care and non-pharmacological treatments. Further research is needed to explore factors that influence how and why GPs prescribe antidepressants to children and young people and the real-world practice barriers to adherence to clinical guidelines

Dynamic updating of clinical survival prediction models in a changing environment

BackgroundOver time, the performance of clinical prediction models may deteriorate due to changes in clinical management, data quality, disease risk and/or patient mix. Such prediction models must be updated in order to remain useful. In this study, we investigate dynamic model updating of clinical survival prediction models. In contrast to discrete or one-time updating, dynamic updating refers to a repeated process for updating a prediction model with new data. We aim to extend previous research which focused largely on binary outcome prediction models by concentrating on time-to-event outcomes. We were motivated by the rapidly changing environment seen during the COVID-19 pandemic where mortality rates changed over time and new treatments and vaccines were introduced. MethodsWe illustrate three methods for dynamic model updating: Bayesian dynamic updating, recalibration, and full refitting. We use a simulation study to compare performance in a range of scenarios including changing mortality rates, predictors with low prevalence and the introduction of a new treatment. Next, the updating strategies were applied to a model for predicting 70-day COVID-19-related mortality using patient data from QResearch, an electronic health records database from general practices in the UK. ResultsIn simulated scenarios with mortality rates changing over time, all updating methods resulted in better calibration than not updating. Moreover, dynamic updating outperformed ad hoc updating. In the simulation scenario with a new predictor and a small updating dataset, Bayesian updating improved the C-index over not updating and refitting. In the motivating example with a rare outcome, no single updating method offered the best performance. ConclusionsWe found that a dynamic updating process outperformed one-time discrete updating in the simulations. Bayesian updating offered good performance overall, even in scenarios with new predictors and few events. Intercept recalibration was effective in scenarios with smaller sample size and changing baseline hazard. Refitting performance depended on sample size and produced abrupt changes in hazard ratio estimates between periods

Seasonal trends in antidepressant prescribing, depression, anxiety and self-harm in adolescents and young adults: an open cohort study using English primary care data

Background There is an increasing demand for mental health services for young people, which may vary across the year.Objective To determine whether there are seasonal patterns in primary care antidepressant prescribing and mental health issues in adolescents and young adults.Methods This cohort study used anonymised electronic health records from general practices in England contributing to QResearch. It included 5 081 263 males and females aged 14–18 (adolescents), 19–23 and 24–28 years between 2006 and 2019. The incidence rates per 1000 person-years and the incidence rate ratios (IRRs) were calculated for the first records of a selective serotonin reuptake inhibitor (SSRI) prescription, depression, anxiety and self-harm. The IRRs were adjusted for year, region, deprivation, ethnic group and number of working days.Findings There was an increase in SSRI prescribing, depression and anxiety incidence in male and female adolescents in the autumn months (September–November) that was not seen in older age groups. The IRRs for SSRI prescribing for adolescents peaked in November (females: 1.75, 95% CI 1.67 to 1.83, p<0.001; males: 1.72, 95% CI 1.61 to 1.84, p<0.001, vs in January) and for depression (females: 1.29, 95% CI 1.25 to 1.33,p<0.001; males: 1.29, 95% CI 1.23 to 1.35, p<0.001). Anxiety peaked in November for females aged 14–18 years (1.17, 95% CI 1.13 to 1.22, p<0.001) and in September for males (1.19, 95% CI 1.12 to 1.27, p<0.001).Conclusions There were higher rates of antidepressant prescribing and consultations for depression and anxiety at the start of the school year among adolescents.Clinical implications Support around mental health issues from general practitioners and others should be focused during autumn

Do changes in traditional coronary heart disease risk factors over time explain the association between socio-economic status and coronary heart disease?

<p>Abstract</p> <p>Background</p> <p>Socioeconomic status (SES) predicts coronary heart disease independently of the traditional risk factors included in the Framingham risk score. However, it is unknown whether <it>changes </it>in Framingham risk score variables over time explain the association between SES and coronary heart disease. We examined this question given its relevance to risk assessment in clinical decision making.</p> <p>Methods</p> <p>The Atherosclerosis Risk in Communities study data (initiated in 1987 with 10-years follow-up of 15,495 adults aged 45-64 years in four Southern and Mid-Western communities) were used. SES was assessed at baseline, dichotomized as low SES (defined as low education and/or low income) or not. The time dependent variables - smoking, total and high density lipoprotein cholesterol, systolic blood pressure and use of blood pressure lowering medication - were assessed every three years. Ten-year incidence of coronary heart disease was based on EKG and cardiac enzyme criteria, or adjudicated death certificate data. Cox survival analyses examined the contribution of SES to heart disease risk independent of baseline Framingham risk score, without and with further adjustment for the time dependent variables.</p> <p>Results</p> <p>Adjusting for baseline Framingham risk score, low SES was associated with an increased coronary heart disease risk (hazard ratio [HR] = 1.53; 95% Confidence Interval [CI], 1.27 to1.85). After further adjustment for the time dependent variables, the SES effect remained significant (HR = 1.44; 95% CI, 1.19 to1.74).</p> <p>Conclusion</p> <p>Using Framingham Risk Score alone under estimated the coronary heart disease risk in low SES persons. This bias was not eliminated by subsequent changes in Framingham risk score variables.</p

Ethnic differences in Glycaemic control in people with type 2 diabetes mellitus living in Scotland

Background and Aims: Previous studies have investigated the association between ethnicity and processes of care and intermediate outcomes of diabetes, but there are limited population-based studies available. The aim of this study was to use population-based data to investigate the relationships between ethnicity and glycaemic control in men and women with diabetes mellitus living in Scotland.&lt;p&gt;&lt;/p&gt; Methods: We used a 2008 extract from the population-based national electronic diabetes database of Scotland. The association between ethnicity with mean glycaemic control in type 2 diabetes mellitus was examined in a retrospective cohort study, including adjustment for a number of variables including age, sex, socioeconomic status, body mass index (BMI), prescribed treatment and duration of diabetes.&lt;p&gt;&lt;/p&gt; Results: Complete data for analyses were available for 56,333 White Scottish adults, 2,535 Pakistanis, 857 Indians, 427 Chinese and 223 African-Caribbeans. All other ethnic groups had significantly (p&#60;0.05) greater proportions of people with suboptimal glycaemic control (HbA1c &#62;58 mmol/mol, 7.5%) compared to the White Scottish group, despite generally younger mean age and lower BMI. Fully adjusted odds ratios for suboptimal glycaemic control were significantly higher among Pakistanis and Indians (1.85, 95% CI: 1.68–2.04, and 1.62,95% CI: 1.38–1.89) respectively.&lt;p&gt;&lt;/p&gt; Conclusions: Pakistanis and Indians with type 2 diabetes mellitus were more likely to have suboptimal glycaemic control than the white Scottish population. Further research on health services and self-management are needed to understand the association between ethnicity and glycaemic control to address ethnic disparities in glycaemic control.&lt;p&gt;&lt;/p&gt

ASCORE: an up-to-date cardiovascular risk score for hypertensive patients reflecting contemporary clinical practice developed using the (ASCOT-BPLA) trial data.

A number of risk scores already exist to predict cardiovascular (CV) events. However, scores developed with data collected some time ago might not accurately predict the CV risk of contemporary hypertensive patients that benefit from more modern treatments and management. Using data from the randomised clinical trial Anglo-Scandinavian Cardiac Outcomes Trial-BPLA, with 15 955 hypertensive patients without previous CV disease receiving contemporary preventive CV management, we developed a new risk score predicting the 5-year risk of a first CV event (CV death, myocardial infarction or stroke). Cox proportional hazard models were used to develop a risk equation from baseline predictors. The final risk model (ASCORE) included age, sex, smoking, diabetes, previous blood pressure (BP) treatment, systolic BP, total cholesterol, high-density lipoprotein-cholesterol, fasting glucose and creatinine baseline variables. A simplified model (ASCORE-S) excluding laboratory variables was also derived. Both models showed very good internal validity. User-friendly integer score tables are reported for both models. Applying the latest Framingham risk score to our data significantly overpredicted the observed 5-year risk of the composite CV outcome. We conclude that risk scores derived using older databases (such as Framingham) may overestimate the CV risk of patients receiving current BP treatments; therefore, 'updated' risk scores are needed for current patients

The risk of all-cause and cause-specific mortality in people prescribed mirtazapine: an active comparator cohort study using electronic health records

BackgroundStudies have reported an increased risk of mortality among people prescribed mirtazapine compared to other antidepressants. The study aimed to compare all-cause and cause-specific mortality between adults prescribed mirtazapine or other second-line antidepressants.Methods This cohort study used English primary care electronic medical records, hospital admission records, and mortality data from the Clinical Practice Research Datalink (CPRD), for the period 01 January 2005 to 30 November 2018. It included people aged 18-99 years with depression first prescribed a selective serotonin reuptake inhibitor (SSRI) and then prescribed mirtazapine (5,081), a different SSRI (15,032), amitriptyline (3,905), or venlafaxine (1,580). Follow-up was from starting to stopping the second antidepressant, with a 6-month wash-out window, censoring at the end of CPRD follow-up or 30 November 2018. Age-sex standardised rates of all-cause mortality and death due to circulatory system disease, cancer, or respiratory system disease were calculated. Survival analyses were performed, accounting for baseline characteristics using inverse probability of treatment weighting. ResultsThe cohort contained 25,598 people (median age 41 years). The mirtazapine group had the highest standardised mortality rate, with an additional 7.8 (95% confidence interval (CI) 5.9-9.7) deaths/1000 person-years compared to the SSRI group. Within two years of follow-up, the risk of all-cause mortality was statistically significantly higher in the mirtazapine group than the SSRI group (weighted hazard ratio (HR) 1.62, 95% CI 1.28-2.06). No significant difference was found between the mirtazapine group and the amitriptyline (HR 1.18, 95% CI 0.85-1.63) or venlafaxine (HR 1.11, 95% CI 0.60-2.05) groups. After two years, the risk was significantly higher in the mirtazapine group compared to the SSRI (HR 1.51, 95% CI 1.04-2.19), amitriptyline (HR 2.59, 95% CI 1.38-4.86), and venlafaxine (HR 2.35, 95% CI 1.02-5.44) groups. The risks of death due to cancer (HR 1.74, 95% CI 1.06-2.85) and respiratory system disease (HR 1.72, 95% CI 1.07- 2.77) were significantly higher in the mirtazapine than the SSRI group.ConclusionsMortality was higher in people prescribed mirtazapine than people prescribed a second SSRI, possibly reflecting residual differences in other risk factors between groups. Identifying these potential health risks when prescribing mirtazapine may help reduce the risk of mortality