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Background Statins are prescribed to lower LDL cholesterol. Clinical guidelines recommend 30–50% reduction within 3 months, yet many patients do not achieve this. We investigated predictors of LDL-c reduction, treatment adherence, and adverse clinical outcomes in a sample of UK Biobank participants. Methods We analysed 76,000 UK Biobank participants prescribed atorvastatin or simvastatin in primary care: 41,000 had LDL-c measurements before statin initiation (median = 16 days prior, IQR = 28) and within a year of starting treatment (median = 89 days, IQR = 125). Adherence was defined as the “proportion of days covered” (PDC). We estimated associations between PDC within 1 year of statin initiation, genetic factors, post-treatment LDL-c reduction, and clinical adverse outcomes. For 13,000 patients with ≥ 3 LDL-c measures, we used inverse probability of treatment weighting methods to estimate the effect of sustained adherence intervention on LDL-c reduction longitudinally. Results LDL-c reduction following statin initiation was predicted by time until the 1st measurement (up to 26% greater reduction if returned ≤ 3 months vs > 3 months), PDC (up to 38% reduction when PDC > 95% [high] vs. 15% when PDC < 50% [low]), and the pharmacogenetic variant SLCO1B1 *5 (lowest reduction in CC-allele: 37% versus TT-allele: 39.5%). Longitudinal causal modelling showed that the most recent PDC measure exerted the largest influence on overall LDL-c reduction, followed by the initial PDC. Genetic predictors of reduced PDC included liability to schizophrenia (Coef top 20%  − 1.94, 95%CI − 2.69 to − 1.19), while genetic liability to cardiovascular diseases increased PDC (Coef top 20% 1.30, 95%CI 0.55 to 2.05). High PDC was associated with increased risk of incident iron deficiency anaemia (HR 1.30, 95%CI 1.09–1.54) and cataract (HR 1.20, 95%CI 1.07–1.34), and decreased risk of incident coronary heart disease (HR 0.78, 95%CI 0.73–0.84). Conclusions We identify substantial variability in the time to first on-treatment LDL-c measurements and also in adherence to statin medication, highlighting a gap between NHS guidelines, LDL-c monitoring, and statin adherence. We show its subsequent impact on long-term health, demonstrating the potential effect of targeted interventions to improve adherence. We identify important predictors of reduced statin effectiveness, including pharmacogenetic variants, polygenic scores, but most of all, adherence. Tailored statin therapy strategies with patient education on statin indication and adherence could optimize treatment efficacy, safety, and long-term clinical outcomes.

Background Prior to the COVID-19 pandemic, the majority of clinical trial activity took place face to face within clinical or research units. The COVID-19 pandemic resulted in a significant shift towards trial delivery without in-person face-to-face contact or “Remote Trial Delivery”. The National Institute of Health Research (NIHR) assembled a Remote Trial Delivery Working Group to consider challenges and enablers to this major change in clinical trial delivery and to provide a toolkit for researchers to support the transition to remote delivery. Methods The NIHR Remote Trial Delivery Working Group evaluated five key domains of the trial delivery pathway: participant factors, recruitment, intervention delivery, outcome measurement and quality assurance. Independent surveys were disseminated to research professionals, and patients and carers, to ascertain benefits, challenges, pitfalls, enablers and examples of good practice in Remote Trial Delivery. A toolkit was constructed to support researchers, funders and governance structures in moving towards Remote Trial Delivery. The toolkit comprises a website encompassing the key principles of Remote Trial Delivery, and a repository of best practice examples and questions to guide research teams. Results The patient and carer survey received 47 respondents, 34 of whom were patients and 13 of whom were carers. The professional survey had 115 examples of remote trial delivery practice entered from across England. Key potential benefits included broader reach and inclusivity, the ability for standardisation and centralisation, and increased efficiency and patient/carer convenience. Challenges included the potential exclusion of participants lacking connectivity or digital skills, the lack of digitally skilled workforce and appropriate infrastructure, and validation requirements. Five key principles of Remote Trial Delivery were proposed: national research standards, inclusivity, validity, cost-effectiveness and evaluation of new methodologies. Conclusions The rapid changes towards Remote Trial Delivery catalysed by the COVID-19 pandemic could lead to sustained change in clinical trial delivery. The NIHR Remote Trial Delivery Working Group provide a toolkit for researchers recommending five key principles of Remote Trial Delivery and providing examples of enablers.

Background Multimorbidity, the co-occurrence of multiple long-term conditions (LTCs), is an increasingly important clinical problem, but little is known about the underlying causes. We investigate the role of a critical multimorbidity risk factor, obesity, as measured by body mass index (BMI), in explaining shared genetics amongst 71 common LTCs. Methods In a population of northern Europeans, we estimated genetic correlation, between LTCs and partial genetic correlations after adjustment for the genetics of BMI. We used multiple causal inference methods to confirm that BMI causally affects individual LTCs, and their co-occurrence. Finally, we quantified the population-level impact of intervening and lowering BMI on the prevalence of 15 key common multimorbid LTC pairs. Results BMI partially explains some of the shared genetics for 740 LTC pairs (30% of all pairs considered). For a further 161 LTC pairs, the genetic similarity between the LTCs was entirely accounted for by BMI genetics. This list included diabetes and osteoarthritis and gout and osteoarthritis: Causal inference methods confirmed that higher BMI acts as a common risk factor for a subset of these pairs, and therefore BMI-lowering interventions would likely reduce their prevalence. For example, we estimated that a 1 standard deviation or 4.5 unit decrease in BMI would result in 17 fewer people with both chronic kidney disease and osteoarthritis per 1000 who currently have both LTCs. Conclusions Our genetics-centred approach quantifies the contribution of obesity to multi-morbidity. Our method for calculating full and partial genetic correlations is published as an R package {partialLDSC} . Plain language summary More than half of people over 65 have several long-term health conditions at the same time. This is becoming a bigger issue in the UK, but we don’t fully understand why some people develop many conditions. We looked at how body weight, measured by body mass index (BMI), affects the shared genetic risks for 71 common health problems such as diabetes, heart disease, arthritis and depression. Using data from people with northern European ancestry, we studied how much the same genes are linked to different conditions — both before and after taking the genetics of BMI into account. We found that BMI explains some of the shared genetic risks between many health conditions, and all of the shared risk for some, such as diabetes and osteoarthritis. Our results suggest that helping people lower their BMI could reduce the number of long-term health problems they experience, allowing more people to live longer and healthier lives. Mounier et al., analyse whether obesity, measured by body mass index (BMI) affects the shared genetic risk between 71 long-term health conditions including diabetes, heart disease and arthritis. Health interventions that help to lower BMI can reduce multimorbidity and promote longer and healthier lives.

Pharmacogenetic variants are associated with clinical outcomes during Calcium Channel Blocker (CCB) treatment, yet whether the effects are modified by genetically predicted clinical risk factors is unknown. We analyzed 32,000 UK Biobank participants treated with dihydropiridine CCBs (mean 5.9 years), including 23 pharmacogenetic variants, and calculated polygenic scores for systolic and diastolic blood pressures, body fat mass, and other patient characteristics. Outcomes included treatment discontinuation and heart failure. Pharmacogenetic variant rs10898815-A ( NUMA1 ) increased discontinuation rates, highest in those with high polygenic scores for fat mass. The RYR3 variant rs877087 T-allele alone modestly increased heart failure risks versus non-carriers (HR:1.13, p  = 0.02); in patients with high polygenic scores for fat mass, lean mass, and lipoprotein A, risks were substantially elevated (HR:1.55, p  = 4 × 10 −5 ). Incorporating polygenic scores for adiposity and lipoprotein A may improve risk estimates of key clinical outcomes in CCB treatment such as treatment discontinuation and heart failure, compared to pharmacogenetic variants alone.

We aimed to estimate the real-world effectiveness of the influenza vaccine against myocardial infarction (MI) and influenza in the decade since adults aged ≥ 65 years were first recommended the vaccine. We identified annual cohorts, 1997 to 2011, of adults aged ≥ 65 years, without previous influenza vaccination, from UK general practices, registered with the Clinical Practice Research Datalink. Using a quasi-experimental study design to control for confounding bias, we estimated influenza vaccine effectiveness on hospitalization for MI, influenza, and antibiotic prescriptions for lower respiratory tract infections. Vaccination was moderately effective against influenza, the prior event rate ratio–adjusted hazard ratios ranging from 0.70 in 1999 to 0.99 in 2001. Prior event rate ratio–adjusted hazard ratios demonstrated a protective effect against MIs, varying between 0.40 in 2010 and 0.89 in 2001. Aggregated across the cohorts, influenza vaccination reduced the risk of MIs by 39% (95% confidence interval: 34%, 44%). Effectiveness of the flu vaccine in preventing MIs in older UK adults is consistent with the limited evidence from clinical trials. Similar trends in effectiveness against influenza and against MIs suggest the risk of influenza mediates the effectiveness against MIs, although divergence in some years implies the mechanism may be complex. [Display omitted] •Real-world data study of flu vaccine in adults aged ≥ 65 years adjusting for confounding bias.•Flu vaccine effective against both flu and myocardial infarctions from 1997 to 2010.•Trends suggest complex mediation of protection against myocardial infarctions.•Myocardial infarction risk reduced overall by 39% after flu vaccination.•Our real-world estimate agrees closely with limited evidence from clinical trials.

ObjectiveTo determine whether CYP2C19 loss-of-function (LoF) alleles increase risk of ischaemic stroke and myocardial infarction (MI) in UK primary care patients prescribed clopidogrel.DesignRetrospective cohort analysis.SettingPrimary care practices in the UK from January 1999 to September 2017.Participants7483 European-ancestry adults from the UK Biobank study with genetic and linked primary care data, aged 36–79 years at time of first clopidogrel prescription.InterventionsClopidogrel prescription in primary care, mean duration 2.6 years (range 2 months to 18 years).Main outcome measureHospital inpatient-diagnosed ischaemic stroke, MI or angina while treated with clopidogrel.Results28.7% of participants carried at least one CYP2C19 LoF variant. LoF carriers had higher rates of incident ischaemic stroke while treated with clopidogrel compared with those without the variants (8 per 1000 person-years vs 5.2 per 1000 person-years; HR 1.53, 95% CIs 1.04 to 2.26, p=0.031). LoF carriers also had increased risk of MI (HR 1.14, 95% CI 1.04 to 1.26, p=0.008). In combined analysis LoF carriers had increased risk of any ischaemic event (stroke or MI) (HR 1.17, 95% CI 1.06 to 1.29, p=0.002). Adjustment for aspirin coprescription produced similar estimates. In lifetables using observed incidence rates, 22.5% (95% CI 14.4% to 34.0%) of CYP2C19 LoF carriers on clopidogrel were projected to develop an ischaemic stroke by age 79 (oldest age in the study), compared with 15.4% (95% CI 11.4% to 20.5%) in non-carriers, that is, 7.1% excess stroke incidence in LoF carriers by age 79.ConclusionsA substantial proportion of the UK population carry genetic variants that reduce metabolism of clopidogrel to its active form. In family practice patients on clopidogrel, CYP2C19 LoF variants are associated with substantially higher incidence of ischaemic events. Genotype-guided selection of antiplatelet medications may improve outcomes in patients carrying CYP2C19 genetic variants.

Background High risk medications are commonly prescribed to older US patients. Currently, less is known about high risk medication prescribing in other Western Countries, including the UK. We measured trends and correlates of high risk medication prescribing in a subset of the older UK population (community/institutionalized) to inform harm minimization efforts. Methods Three cross-sectional samples from primary care electronic clinical records (UK Clinical Practice Research Datalink, CPRD) in fiscal years 2003/04, 2007/08 and 2011/12 were taken. This yielded a sample of 13,900 people aged 65 years or over from 504 UK general practices. High risk medications were defined by 2012 Beers Criteria adapted for the UK. Using descriptive statistical methods and regression modelling, prevalence of ‘any’ (drugs prescribed at least once per year) and ‘long-term’ (drugs prescribed all quarters of year) high risk medication prescribing and correlates were determined. Results While polypharmacy rates have risen sharply, high risk medication prevalence has remained stable across a decade. A third of older (65+) people are exposed to high risk medications, but only half of the total prevalence was long-term (any = 38.4 % [95 % CI: 36.3, 40.5]; long-term = 17.4 % [15.9, 19.9] in 2011/12). Long-term but not any high risk medication exposure was associated with older ages (85 years or over). Women and people with higher polypharmacy burden were at greater risk of exposure; lower socio-economic status was not associated. Ten drugs/drug classes accounted for most of high risk medication prescribing in 2011/12. Conclusions High risk medication prescribing has not increased over time against a background of increasing polypharmacy in the UK. Half of patients receiving high risk medications do so for less than a year. Reducing or optimising the use of a limited number of drugs could dramatically reduce high risk medications in older people. Further research is needed to investigate why the oldest old and women are at greater risk. Interventions to reduce high risk medications may need to target shorter and long-term use separately.

The solute carrier organic anion transporter family member 1B1 (SLCO1B1) encodes the organic anion-transporting polypeptide 1B1 (OATP1B1 protein) that transports statins to liver cells. Common genetic variants in SLCO1B1, such as *5, cause altered systemic exposure to statins and therefore affect statin outcomes, with potential pharmacogenetic applications; yet, evidence is inconclusive. We studied common and rare SLCO1B1 variants in up to 64,000 patients from UK Biobank prescribed simvastatin or atorvastatin, combining whole-exome sequencing data with up to 25-year routine clinical records. We studied 51 predicted gain/loss-of-function variants affecting OATP1B1. Both SLCO1B1*5 alone and the SLCO1B1*15 haplotype increased LDL during treatment (beta*5 = 0.08 mmol/L, p = 6 × 10−8; beta*15 = 0.03 mmol/L, p = 3 × 10−4), as did the likelihood of discontinuing statin prescriptions (hazard ratio*5 = 1.12, p = 0.04; HR*15 = 1.05, p = 0.04). SLCO1B1*15 and SLCO1B1*20 increased the risk of General Practice (GP)-diagnosed muscle symptoms (HR*15 = 1.22, p = 0.003; HR*20 = 1.25, p = 0.01). We estimated that genotype-guided prescribing could potentially prevent 18% and 10% of GP-diagnosed muscle symptoms experienced by statin patients, with *15 and *20, respectively. The remaining common variants were not individually significant. Rare variants in SLCO1B1 increased LDL in statin users by up to 1.05 mmol/L, but replication is needed. We conclude that genotype-guided treatment could reduce GP-diagnosed muscle symptoms in statin patients; incorporating further SLCO1B1 variants into clinical prediction scores could improve LDL control and decrease adverse events, including discontinuation.

Traditional pathways to promote research collaboration typically take years to expand beyond individual institutions. Social media and online networking provide an innovative approach to promote research collaboration. The objective of this paper is to present the formation of the Geriatric Medicine Research Collaborative, United Kingdom - a national trainee-led research collaborative. This collaborative aims to facilitate research projects that will directly benefit older patients, improve research skills of geriatric medicine trainees, and facilitate recommendations for health care policy for older adults. Our methods of collaboration comprised trainee-led meetings regionally and at national conferences, email communication, direct uploading of project material to our website, social media, and virtual meetings. Structured use of local, regional, and network leads has facilitated this collaboration. Having a clear virtual presence has been the key to the rapid development of the network. The use of social media and online networking encouraged the involvement of multiple regions early in the development of the collaborative and allowed rapid dissemination of project ideas. This facilitated the collection of large datasets and enhanced scientific validity of project outcomes. Furthermore, this has the potential to transform geriatric medicine research, as older patients have been historically excluded from large commercial trials due to multimorbidity, frailty, and cognitive impairment. Perceived limitations to predominantly online or virtual collaboratives, including reduced accountability, and loss of interpersonal relationships are balanced by increased trainee engagement, high frequency of communication, and rapid access to a breadth of expertise. Utilization of virtual communication has the potential to lead to future interspecialty, interprofessional, and international collaboration, and to accelerate research that improves outcomes for older adults.