Genetic Determinants of Thiazide-Induced Hyperuricemia, Hyperglycemia, and Urinary Electrolyte Disturbances - A Genome-Wide Evaluation of the UK Biobank.

Thiazide diuretics, widely used in hypertension, cause a variety of adverse reactions, including hyperglycemia, hyperuricemia, and electrolyte abnormalities. In this study, we aimed to identify genetic variants that interact with thiazide-use to increase the risk of these adverse reactions. Using UK Biobank data, we first performed genomewide variance quantitative trait locus (vQTL) analysis of ~ 6.2 million SNPs on 95,493 unrelated hypertensive White British participants (24,313 on self-reported bendroflumethiazide treatment at recruitment) for 2 blood (glucose and urate) and 2 urine (potassium and sodium) biomarkers. Second, we conducted direct gene-environment interaction (GEI) tests on the significant (P < 2.5 × 10-9) vQTLs, included a second UK Biobank cohort comprising 13,647 unrelated hypertensive White British participants (3,478 on thiazides other than bendroflumethiazide) and set significance at P = 0.05 divided by the number of vQTL SNPs tested for GEIs. The vQTL analysis identified eight statistically significant SNPs for blood glucose (5 SNPs) and serum urate (3 SNPs), with none being identified for the urinary biomarkers. Two of the SNPs (1 glucose SNP: CDKAL1 intron rs35612982, GEI P = 6.24 × 10-3; and 1 serum urate SNP: SLC2A9 intron rs938564, GEI P = 4.51 × 10-4) demonstrated significant GEI effects in the first, but not the second, cohort. Both genes are biologically plausible candidates, with the SLC2A9-mediated interaction having been previously reported. In conclusion, we used a two-stage approach to detect two biologically plausible genetic loci that can interact with thiazides to increase the risk of thiazide-associated biochemical abnormalities. Understanding how environmental exposures (including medications such as thiazides) and genetics interact, is an important step toward precision medicine and improved patient outcomes.

Drug-induced orthostatic hypotension: Cluster analysis of co-prescription patterns in older people in UK primary care.

PURPOSE: Over 250 medications are reported to cause orthostatic hypotension, associated with serious adverse outcomes in older adults. Studies suggest a harmful cumulative risk of orthostatic hypotension with multiple medication use. However, there is limited evidence on the potential for harm in practice, particularly which drugs is co-prescribed and may increase risk of orthostatic hypotension. METHODS: Retrospective cohort study and cluster analysis using general practice data from IQVIA Medical Research Data (IMRD) in patients aged ≥50 contributing data between 1 January 2018 and 31 December 2018. Thirteen drug groups known to be associated with orthostatic hypotension by mechanism, were analyzed and clusters generated by sex and age-band. RESULTS: A total of 602 713 individuals aged ≥50 with 283 912 (47%) men and 318 801 (53%) women were included. The most prevalent prescriptions that might contribute to orthostatic hypotension were ACE inhibitors, calcium-channel blockers, beta-blockers, selective serotonin reuptake inhibitors and uroselective alpha-blockers. We identified distinct clusters of cardiovascular system (cardiovascular system) drugs in men and women at all ages. cardiovascular system plus psychoactive drug clusters were common in women at all ages, and in men aged ≤70. cardiovascular system plus uroselective alpha-blockers were identified in men aged ≥70. CONCLUSIONS: Distinct clusters of drugs associated with orthostatic hypotension exist in practice, which change over the life course. Our findings highlight potentially harmful drug combinations that may cause cumulative risk of orthostatic hypotension in older people. This may guide clinicians about the potential of synergistic harm and to monitor for orthostatic hypotension if using combinations of cardiovascular system drugs, cardiovascular system plus psychoactive drugs and/or alpha-blockers-particularly in patients aged ≥70 or at high-risk due to comorbidity. Future research should consider quantifying the risk of drug-induced orthostatic hypotension with such drug combinations.

Prevalence of chronic pain or analgesic use in children and young people and its long-term impact on substance misuse, mental illness, and prescription opioid use: a retrospective longitudinal cohort study.

Background: Epidemiological studies suggest chronic and recurrent pain affects around a quarter of children, while 8% report intense and frequent pain. The long-term implications of chronic pain in childhood are uncertain. Using electronic health records (EHRs) we used both disease codes and medicines prescription records to investigate the scale of chronic pain and long-term analgesic use in children and young people (CYP), and if chronic pain and/or use of analgesic medicines at an early age is associated with substance misuse, use of prescription opioids, and poor mental health in adulthood. Methods: We conducted a cohort study using data from IQVIA Medical Research Data UK. We identified individuals aged 2-24 with exposure to either a diagnostic code indicating chronic pain (diagnosis-exposed), repeat prescription for medicines commonly used to treat pain (prescription-exposed), or both. Follow-up began at 25, and the unexposed population acted as comparators. We calculated hazard ratios (HR) for mental health and substance misuse outcomes, and rate ratios (RR) for opioid prescriptions in adulthood. Additionally, we investigated which diagnoses, if any, were over-represented in the prescription-exposed subgroup. Findings: The cohort constituted 853,625 individuals; 146,431 had one or more of the exposures of interest (diagnosis-exposed = 115,101, prescription-exposed = 20,298, both-exposed = 11,032), leaving 707,194 as comparators. Median age at index exposure was 18.7 years (IQR 14.7-22.3). On average during follow-up, the pooled exposed group had, respectively, a 31% and 17% higher risk of adverse mental health and substance misuse outcomes (adjusted HR [95% CI] of 1.31 [1.29-1.32] and 1.17 [1.11-1.24]). Exposed individuals also received prescription opioids at double the rate of unexposed individuals on average during follow-up (adjusted RR 2.01 [95% CI 1.95-2.10]). Outcomes varied between exposure subgroups, with prescription- and both-exposure tending to have worse outcomes. Unlike these two subgroups, in the diagnosis-exposed subgroup we did not detect a greater risk of substance misuse. Interpretation: Chronic pain in CYP is associated with increased prescription opioid use and adverse mental health outcomes in adulthood, as is repeat prescription for analgesic medicines, but only the latter is also associated with substance misuse in adulthood. It is essential to avoid the harms of under-treating pain in CYP while giving due consideration to the risks posed by analgesic medicines. Early recognition of chronic pain in CYP and utilising non-pharmacological management options may help minimise overprescribing, and long-term reliance on dependence-forming-drugs. Funding: AL is an NIHR funded academic clinical fellow, and was supported by funding from UCLH Charities while carrying out this work. RS and DS are part of the Advanced Pain Discovery Platform and were supported by a UKRI and Versus Arthritis grant (MR/W002566/1) as part of the Consortium Against Pain Inequality. AW was supported by the Wellcome Trust (220558/Z/20/Z).

Ethnic disparities in progression rates for sight-threatening diabetic retinopathy in diabetic eye screening: a population-based retrospective cohort study.

INTRODUCTION: The English Diabetic Eye Screening Programme (DESP) offers people living with diabetes (PLD) annual eye screening. We examined incidence and determinants of sight-threatening diabetic retinopathy (STDR) in a sociodemographically diverse multi-ethnic population. RESEARCH DESIGN AND METHODS: North East London DESP cohort data (January 2012 to December 2021) with 137 591 PLD with no retinopathy, or non-STDR at baseline in one/both eyes, were used to calculate STDR incidence rates by sociodemographic factors, diabetes type, and duration. HR from Cox models examined associations with STDR. RESULTS: There were 16 388 incident STDR cases over a median of 5.4 years (IQR 2.8-8.2; STDR rate 2.214, 95% CI 2.214 to 2.215 per 100 person-years). People with no retinopathy at baseline had a lower risk of sight-threatening diabetic retinopathy (STDR) compared with those with non-STDR in one eye (HR 3.03, 95% CI 2.91 to 3.15, p<0.001) and both eyes (HR 7.88, 95% CI 7.59 to 8.18, p<0.001). Black and South Asian individuals had higher STDR hazards than white individuals (HR 1.57, 95% CI 1.50 to 1.64 and HR 1.36, 95% CI 1.31 to 1.42, respectively). Additionally, every 5-year increase in age at inclusion was associated with an 8% reduction in STDR hazards (p<0.001). CONCLUSIONS: Ethnic disparities exist in a health system limited by capacity rather than patient economic circumstances. Diabetic retinopathy at first screen is a strong determinant of STDR development. By using basic demographic characteristics, screening programmes or clinical practices can stratify risk for sight-threatening diabetic retinopathy development.

Performance of polygenic risk scores in screening, prediction, and risk stratification: secondary analysis of data in the Polygenic Score Catalog.

Objective: To clarify the performance of polygenic risk scores in population screening, individual risk prediction, and population risk stratification. Design: Secondary analysis of data in the Polygenic Score Catalog. Setting: Polygenic Score Catalog, April 2022. Secondary analysis of 3915 performance metric estimates for 926 polygenic risk scores for 310 diseases to generate estimates of performance in population screening, individual risk, and population risk stratification. Participants: Individuals contributing to the published studies in the Polygenic Score Catalog. Main outcome measures: Detection rate for a 5% false positive rate (DR5) and the population odds of becoming affected given a positive result; individual odds of becoming affected for a person with a particular polygenic score; and odds of becoming affected for groups of individuals in different portions of a polygenic risk score distribution. Coronary artery disease and breast cancer were used as illustrative examples. Results: For performance in population screening, median DR5 for all polygenic risk scores and all diseases studied was 11% (interquartile range 8-18%). Median DR5 was 12% (9-19%) for polygenic risk scores for coronary artery disease and 10% (9-12%) for breast cancer. The population odds of becoming affected given a positive results were 1:8 for coronary artery disease and 1:21 for breast cancer, with background 10 year odds of 1:19 and 1:41, respectively, which are typical for these diseases at age 50. For individual risk prediction, the corresponding 10 year odds of becoming affected for individuals aged 50 with a polygenic risk score at the 2.5th, 25th, 75th, and 97.5th centiles were 1:54, 1:29, 1:15, and 1:8 for coronary artery disease and 1:91, 1:56, 1:34, and 1:21 for breast cancer. In terms of population risk stratification, at age 50, the risk of coronary artery disease was divided into five groups, with 10 year odds of 1:41 and 1:11 for the lowest and highest quintile groups, respectively. The 10 year odds was 1:7 for the upper 2.5% of the polygenic risk score distribution for coronary artery disease, a group that contributed 7% of cases. The corresponding estimates for breast cancer were 1:72 and 1:26 for the lowest and highest quintile groups, and 1:19 for the upper 2.5% of the distribution, which contributed 6% of cases. Conclusion: Polygenic risk scores performed poorly in population screening, individual risk prediction, and population risk stratification. Strong claims about the effect of polygenic risk scores on healthcare seem to be disproportionate to their performance.

Two-year recall for people with no diabetic retinopathy: a multi-ethnic population-based retrospective cohort study using real-world data to quantify the effect.

BACKGROUND/AIMS: The English Diabetic Eye Screening Programme (DESP) offers people living with diabetes (PLD) annual screening. Less frequent screening has been advocated among PLD without diabetic retinopathy (DR), but evidence for each ethnic group is limited. We examined the potential effect of biennial versus annual screening on the detection of sight-threatening diabetic retinopathy (STDR) and proliferative diabetic retinopathy (PDR) among PLD without DR from a large urban multi-ethnic English DESP. METHODS: PLD in North-East London DESP (January 2012 to December 2021) with no DR on two prior consecutive screening visits with up to 8 years of follow-up were examined. Annual STDR and PDR incidence rates, overall and by ethnicity, were quantified. Delays in identification of STDR and PDR events had 2-year screening intervals been used were determined. FINDINGS: Among 82 782 PLD (37% white, 36% South Asian, and 16% black people), there were 1788 incident STDR cases over mean (SD) 4.3 (2.4) years (STDR rate 0.51, 95% CI 0.47 to 0.55 per 100-person-years). STDR incidence rates per 100-person-years by ethnicity were 0.55 (95% CI 0.48 to 0.62) for South Asian, 0.34 (95% CI 0.29 to 0.40) for white, and 0.77 (95% CI 0.65 to 0.90) for black people. Biennial screening would have delayed diagnosis by 1 year for 56.3% (1007/1788) with STDR and 43.6% (45/103) with PDR. Standardised cumulative rates of delayed STDR per 100 000 persons for each ethnic group were 1904 (95% CI 1683 to 2154) for black people, 1276 (95% CI 1153 to 1412) for South Asian people, and 844 (95% CI 745 to 955) for white people. INTERPRETATION: Biennial screening would have delayed detection of some STDR and PDR by 1 year, especially among those of black ethnic origin, leading to healthcare inequalities.

Antipsychotic drug prescribing and mortality in people with dementia before and during the COVID-19 pandemic: a retrospective cohort study in Wales, UK.

BACKGROUND: Concerns have been raised that antipsychotic drug prescribing, which has been associated with increased mortality in people with dementia, might have increased during the COVID-19 pandemic due to social restrictions imposed to limit the spread of SARS-CoV-2. We used multisource, routinely collected health-care data from Wales, UK to investigate prescribing and mortality variations in people with dementia before and during the COVID-19 pandemic. METHODS: In this retrospective cohort study, we used individual-level, anonymised, population-scale linked health data to identify adults aged 60 years and older with a diagnosis of dementia in Wales, UK. We used the CVD-COVID-UK initiative to access Welsh routinely collected electronic health record data from the Secure Anonymised Information Linkage (SAIL) Databank. Patients who were alive and registered with a SAIL general practice on Jan 1, 2016, and who received a dementia diagnosis before the age of 60 years and before or during the study period were included. We explored antipsychotic drug prescribing rate changes over 67 months, between Jan 1, 2016, and Aug 1, 2021, overall and stratified by age and dementia subtype. We used time-series analyses to examine all-cause and myocardial infarction and stroke mortality over the study period and identified the leading causes of death in people with dementia between Jan 1, 2020, and Aug 1, 2021. FINDINGS: Of 3 106 690 participants in SAIL between Jan 1, 2016 and Aug 1, 2021, 57 396 people (35 148 [61·2%] women and 22 248 [38·8%] men) met inclusion criteria for this study and contributed 101 428 person-years of follow-up. Of the 57 396 people with dementia, 11 929 (20·8%) were prescribed an antipsychotic drug at any point during follow-up. Accounting for seasonality, antipsychotic drug prescribing increased during the second half of 2019 and throughout 2020. However, the absolute difference in prescribing rates was small, ranging from 1253 prescriptions per 10 000 person-months in March, 2019, to 1305 per 10 000 person-months in September, 2020. All-cause mortality and stroke mortality increased throughout 2020, while myocardial infarction mortality declined. From Jan 1, 2020, to Aug 1, 2021, 1286 (17·1%) of 7508 participants who died had COVID-19 recorded as the underlying cause of death. INTERPRETATION: During the COVID-19 pandemic, antipsychotic drug prescribing in people with dementia in the UK increased slightly; however, it is unlikely that this was solely related to the pandemic and this increase was unlikely to be a major factor in the substantial increase in mortality during 2020. The long-term increase in antipsychotic drug prescribing in younger people and in those with Alzheimer's disease warrants further investigation using resources with access to more granular clinical data. Although deprescribing antipsychotic medications remains an essential aspect of dementia care, the results of this study suggest that changes in prescribing and deprescribing practices as a result of the COVID-19 pandemic are not required. FUNDING: British Heart Foundation (via the British Heart Foundation Data Science Centre led by Health Data Research UK), and the Scottish Neurological Research Fund.

Effectiveness of biosimilar adoption within a UK tertiary hospital: 6-year follow-up.

Health systems encourage switching from originators to biosimilars as biosimilars are more cost-effective. The speed and completeness of biosimilar adoption is a measure of efficiency. We describe the approach to biosimilar adoption at a single hospital Trust and compare its efficiency against the English average. We additionally follow up patients who reverted to a previously used biologic, having switched to a biosimilar, to establish whether they benefitted from re-establishing prior treatment. The approach we describe resulted in a faster and more complete switch to biosimilars, which saved an additional £380 000 on drug costs in 2021/2022. Of patients who reverted to their original biologic, 87% improved short-term, and a time on treatment analysis showed the benefit was retained long term. Our approach to biosimilar adoption outperformed the English average and permits patients to revert to their original biosimilar post-switch if appropriate.

How to assess pharmacogenomic tests for implementation in the NHS in England.

AIMS: Pharmacogenomic testing has the potential to target medicines more effectively towards those who will benefit and avoid use in individuals at risk of harm. Health economies are actively considering how pharmacogenomic tests can be integrated into health care systems to improve use of medicines. However, one of the barriers to effective implementation is evaluation of the evidence including clinical usefulness, cost-effectiveness, and operational requirements. We sought to develop a framework that could aid the implementation of pharmacogenomic testing. We take the view from the National Health Service (NHS) in England. METHODS: We used a literature review using EMBASE and Medline databases to identify prospective studies of pharmacogenomic testing, focusing on clinical outcomes and implementation of pharmacogenomics. Using this search, we identified key themes relating to the implementation of pharmacogenomic tests. We used a clinical advisory group with expertise in pharmacology, pharmacogenomics, formulary evaluation, and policy implementation to review data from our literature review and the interpretation of these data. With the clinical advisory group, we prioritized themes and developed a framework to evaluate proposals to implement pharmacogenomics tests. RESULTS: Themes that emerged from review of the literature and subsequent discussion were distilled into a 10-point checklist that is proposed as a tool to aid evidence-based implementation of pharmacogenomic testing into routine clinical care within the NHS. CONCLUSION: Our 10-point checklist outlines a standardized approach that could be used to evaluate proposals to implement pharmacogenomic tests. We propose a national approach, taking the view of the NHS in England. Using this approach could centralize commissioning of appropriate pharmacogenomic tests, reduce inequity and duplication using regional approaches, and provide a robust and evidence-based framework for adoption. Such an approach could also be applied to other health systems.

The impact of the COVID-19 pandemic on cardiovascular disease prevention and management.

How the Coronavirus Disease 2019 (COVID-19) pandemic has affected prevention and management of cardiovascular disease (CVD) is not fully understood. In this study, we used medication data as a proxy for CVD management using routinely collected, de-identified, individual-level data comprising 1.32 billion records of community-dispensed CVD medications from England, Scotland and Wales between April 2018 and July 2021. Here we describe monthly counts of prevalent and incident medications dispensed, as well as percentage changes compared to the previous year, for several CVD-related indications, focusing on hypertension, hypercholesterolemia and diabetes. We observed a decline in the dispensing of antihypertensive medications between March 2020 and July 2021, with 491,306 fewer individuals initiating treatment than expected. This decline was predicted to result in 13,662 additional CVD events, including 2,281 cases of myocardial infarction and 3,474 cases of stroke, should individuals remain untreated over their lifecourse. Incident use of lipid-lowering medications decreased by 16,744 patients per month during the first half of 2021 as compared to 2019. By contrast, incident use of medications to treat type 2 diabetes mellitus, other than insulin, increased by approximately 623 patients per month for the same time period. In light of these results, methods to identify and treat individuals who have missed treatment for CVD risk factors and remain undiagnosed are urgently required to avoid large numbers of excess future CVD events, an indirect impact of the COVID-19 pandemic.

Incidence, morbidity, mortality and disparities in dementia: A population linked electronic health records study of 4.3 million individuals.

INTRODUCTION: We report dementia incidence, comorbidities, reasons for health-care visits, mortality, causes of death, and examined dementia patterns by relative deprivation in the UK. METHOD: A longitudinal cohort analysis of linked electronic health records from 4.3 million people in the UK was conducted to investigate dementia incidence and mortality. Reasons for hospitalization and causes of death were compared in individuals with and without dementia. RESULTS: From 1998 to 2016 we observed 145,319 (3.1%) individuals with incident dementia. Repeated hospitalizations among senior adults for infection, unknown morbidity, and multiple primary care visits for chronic pain were observed prior to dementia diagnosis. Multiple long-term conditions are present in half of the individuals at the time of diagnosis. Individuals living in high deprivation areas had higher dementia incidence and high fatality. DISCUSSION: There is a considerable disparity of dementia that informs priorities of prevention and provision of patient care.

Are high-cost drug funding mechanisms fit for purpose? A retrospective study of individual funding requests in an NHS tertiary hospital.

AIMS: To report on a retrospective study of individual funding request (IFR) submissions from a large tertiary hospital and describe gaps in current mechanisms for funding of high-cost medicines in England. METHODS: Data on the number and outcome of IFR submissions submitted to commissioners between 2014/15 and 2018/19 was extracted from the electronic patient health record and a local high-cost drug database. RESULTS: In total, 230 IFRs were submitted: 112 to NHS England and 118 to a Clinical Commissioning Group (CCG). The decline rate for IFRs was 71% for NHS England and 34% for CCGs. Lack of exceptionality was the primary reason cited for declining IFRs submitted between 2016-18 (n = 42/45; 93%). Half of the patients whose IFR was declined received treatment funded through other routes, the majority (13/23; 57%) from internal hospital budget. This was governed via a local high-cost drug panel. Positive clinical outcomes were observed in 50% (4/8) of patients who received NHS England IFR-funded treatment, 54% (19/35) who received CCG IFR-funded treatment and 91% (21/23) who were funded via other routes. CONCLUSION: The high rate of IFR decline signals inefficient use of resource expended in the IFR process. Gaps in access to high-cost medicines remain for patients with rare and refractory disease requiring urgent treatment, largely due to the demand for exceptionality from NHS commissioners. Local mechanisms address this unmet need but have limitations. An outcomes-based evaluation approach to commissioning and greater transparency of previous funding decisions by commissioners may improve efficiency and equity in the IFR system.

Identifying and visualising multimorbidity and comorbidity patterns in patients in the English National Health Service: a population-based study.

BACKGROUND: Globally, there is a paucity of multimorbidity and comorbidity data, especially for minority ethnic groups and younger people. We estimated the frequency of common disease combinations and identified non-random disease associations for all ages in a multiethnic population. METHODS: In this population-based study, we examined multimorbidity and comorbidity patterns stratified by ethnicity or race, sex, and age for 308 health conditions using electronic health records from individuals included on the Clinical Practice Research Datalink linked with the Hospital Episode Statistics admitted patient care dataset in England. We included individuals who were older than 1 year and who had been registered for at least 1 year in a participating general practice during the study period (between April 1, 2010, and March 31, 2015). We identified the most common combinations of conditions and comorbidities for index conditions. We defined comorbidity as the accumulation of additional conditions to an index condition over an individual's lifetime. We used network analysis to identify conditions that co-occurred more often than expected by chance. We developed online interactive tools to explore multimorbidity and comorbidity patterns overall and by subgroup based on ethnicity, sex, and age. FINDINGS: We collected data for 3 872 451 eligible patients, of whom 1 955 700 (50·5%) were women and girls, 1 916 751 (49·5%) were men and boys, 2 666 234 (68·9%) were White, 155 435 (4·0%) were south Asian, and 98 815 (2·6%) were Black. We found that a higher proportion of boys aged 1-9 years (132 506 [47·8%] of 277 158) had two or more diagnosed conditions than did girls in the same age group (106 982 [40·3%] of 265 179), but more women and girls were diagnosed with multimorbidity than were boys aged 10 years and older and men (1 361 232 [80·5%] of 1 690 521 vs 1 161 308 [70·8%] of 1 639 593). White individuals (2 097 536 [78·7%] of 2 666 234) were more likely to be diagnosed with two or more conditions than were Black (59 339 [60·1%] of 98 815) or south Asian individuals (93 617 [60·2%] of 155 435). Depression commonly co-occurred with anxiety, migraine, obesity, atopic conditions, deafness, soft-tissue disorders, and gastrointestinal disorders across all subgroups. Heart failure often co-occurred with hypertension, atrial fibrillation, osteoarthritis, stable angina, myocardial infarction, chronic kidney disease, type 2 diabetes, and chronic obstructive pulmonary disease. Spinal fractures were most strongly non-randomly associated with malignancy in Black individuals, but with osteoporosis in White individuals. Hypertension was most strongly associated with kidney disorders in those aged 20-29 years, but with dyslipidaemia, obesity, and type 2 diabetes in individuals aged 40 years and older. Breast cancer was associated with different comorbidities in individuals from different ethnic groups. Asthma was associated with different comorbidities between males and females. Bipolar disorder was associated with different comorbidities in younger age groups compared with older age groups. INTERPRETATION: Our findings and interactive online tools are a resource for: patients and their clinicians, to prevent and detect comorbid conditions; research funders and policy makers, to redesign service provision, training priorities, and guideline development; and biomedical researchers and manufacturers of medicines, to provide leads for research into common or sequential pathways of disease and inform the design of clinical trials. FUNDING: UK Research and Innovation, Medical Research Council, National Institute for Health and Care Research, Department of Health and Social Care, Wellcome Trust, British Heart Foundation, and The Alan Turing Institute.

COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records.

BACKGROUND: Updatable estimates of COVID-19 onset, progression, and trajectories underpin pandemic mitigation efforts. To identify and characterise disease trajectories, we aimed to define and validate ten COVID-19 phenotypes from nationwide linked electronic health records (EHR) using an extensible framework. METHODS: In this cohort study, we used eight linked National Health Service (NHS) datasets for people in England alive on Jan 23, 2020. Data on COVID-19 testing, vaccination, primary and secondary care records, and death registrations were collected until Nov 30, 2021. We defined ten COVID-19 phenotypes reflecting clinically relevant stages of disease severity and encompassing five categories: positive SARS-CoV-2 test, primary care diagnosis, hospital admission, ventilation modality (four phenotypes), and death (three phenotypes). We constructed patient trajectories illustrating transition frequency and duration between phenotypes. Analyses were stratified by pandemic waves and vaccination status. FINDINGS: Among 57 032 174 individuals included in the cohort, 13 990 423 COVID-19 events were identified in 7 244 925 individuals, equating to an infection rate of 12·7% during the study period. Of 7 244 925 individuals, 460 737 (6·4%) were admitted to hospital and 158 020 (2·2%) died. Of 460 737 individuals who were admitted to hospital, 48 847 (10·6%) were admitted to the intensive care unit (ICU), 69 090 (15·0%) received non-invasive ventilation, and 25 928 (5·6%) received invasive ventilation. Among 384 135 patients who were admitted to hospital but did not require ventilation, mortality was higher in wave 1 (23 485 [30·4%] of 77 202 patients) than wave 2 (44 220 [23·1%] of 191 528 patients), but remained unchanged for patients admitted to the ICU. Mortality was highest among patients who received ventilatory support outside of the ICU in wave 1 (2569 [50·7%] of 5063 patients). 15 486 (9·8%) of 158 020 COVID-19-related deaths occurred within 28 days of the first COVID-19 event without a COVID-19 diagnoses on the death certificate. 10 884 (6·9%) of 158 020 deaths were identified exclusively from mortality data with no previous COVID-19 phenotype recorded. We observed longer patient trajectories in wave 2 than wave 1. INTERPRETATION: Our analyses illustrate the wide spectrum of disease trajectories as shown by differences in incidence, survival, and clinical pathways. We have provided a modular analytical framework that can be used to monitor the impact of the pandemic and generate evidence of clinical and policy relevance using multiple EHR sources. FUNDING: British Heart Foundation Data Science Centre, led by Health Data Research UK.

Evaluation of antithrombotic use and COVID-19 outcomes in a nationwide atrial fibrillation cohort.

OBJECTIVE: To evaluate antithrombotic (AT) use in individuals with atrial fibrillation (AF) and at high risk of stroke (CHA2DS2-VASc score ≥2) and investigate whether pre-existing AT use may improve COVID-19 outcomes. METHODS: Individuals with AF and CHA2DS2-VASc score ≥2 on 1 January 2020 were identified using electronic health records for 56 million people in England and were followed up until 1 May 2021. Factors associated with pre-existing AT use were analysed using logistic regression. Differences in COVID-19-related hospitalisation and death were analysed using logistic and Cox regression in individuals with pre-existing AT use versus no AT use, anticoagulants (AC) versus antiplatelets (AP), and direct oral anticoagulants (DOACs) versus warfarin. RESULTS: From 972 971 individuals with AF (age 79 (±9.3), female 46.2%) and CHA2DS2-VASc score ≥2, 88.0% (n=856 336) had pre-existing AT use, 3.8% (n=37 418) had a COVID-19 hospitalisation and 2.2% (n=21 116) died, followed up to 1 May 2021. Factors associated with no AT use included comorbidities that may contraindicate AT use (liver disease and history of falls) and demographics (socioeconomic status and ethnicity). Pre-existing AT use was associated with lower odds of death (OR=0.92, 95% CI 0.87 to 0.96), but higher odds of hospitalisation (OR=1.20, 95% CI 1.15 to 1.26). AC versus AP was associated with lower odds of death (OR=0.93, 95% CI 0.87 to 0.98) and higher hospitalisation (OR=1.17, 95% CI 1.11 to 1.24). For DOACs versus warfarin, lower odds were observed for hospitalisation (OR=0.86, 95% CI 0.82 to 0.89) but not for death (OR=1.00, 95% CI 0.95 to 1.05). CONCLUSIONS: Pre-existing AT use may be associated with lower odds of COVID-19 death and, while not evidence of causality, provides further incentive to improve AT coverage for eligible individuals with AF.

The importance of blood pressure thresholds versus predicted cardiovascular risk on subsequent rates of cardiovascular disease: a cohort study in English primary care.

BACKGROUND: For five decades, blood pressure lowering treatment has been recommended for patients with hypertension (currently defined as blood pressure of ≥140/90 mm Hg). In the past 20 years, guidelines for treatment began incorporating predicted absolute cardiovascular disease risk (predicted risk) and reducing blood pressure thresholds. The blood pressure threshold at which to start treatment has become a secondary consideration in some countries. We aimed to provide descriptive data to assess the relative importance of blood pressure thresholds versus predicted risk on the subsequent rate of cardiovascular disease to inform treatment decisions. METHODS: In this English population-based cohort study, we used linked data from the Clinical Practice Research Datalink (CPRD) GOLD, Hospital Episode Statistics Admitted Patient Care, and the Office for National Statistics mortality data, and area-based deprivation indices (Townsend scores). Eligible patients were aged 30-79 years on Jan 1, 2011 (cohort entry date) and could be linked to hospital, mortality, and deprivation data. Patients were followed up until death, end of CPRD follow-up, or Nov 31, 2018. We examined three outcomes: cardiovascular disease, markers of potential target organ damage, and incident dementia without a known cause. The rate of each outcome was estimated and stratified by systolic blood pressure and predicted 10-year risk of cardiovascular disease (QRISK2 algorithm). FINDINGS: Between Jan 1, 2011, and Nov 31, 2018, 1 098 991 patients were included in the cohort and followed up for a median of 4·3 years (IQR 2·6-6·0; total follow-up of 4·6 million person-years). Median age at entry was 52 years (IQR 42-62) and 629 711 (57·3%) patients were female. There were 51 996 cardiovascular disease events and the overall rate of cardiovascular disease was 11·2 per 1000 person-years (95% CI 11·1-11·3). Median QRISK2 10-year predicted risk was 4·6% (IQR 1·4-12·0) and mean systolic blood pressure before cohort entry was 129·1 mm Hg (SD 15·7). Within strata of predicted risk, the effect of increasing systolic blood pressure on outcomes was small. For example, in the group with 10·0-19·9% predicted risk, rates of all cardiovascular disease rose from 20·1 to 23·6 per 1000 person-years between systolic blood pressures less than 110 mm Hg and 180 and higher mm Hg. But among patients with systolic blood pressure 140·0-149·9 mm Hg, rates rose from 6·9 to 52·3 per 1000 person-years between those with less than 10·0% risk and those with 30·0% or higher predicted risk. INTERPRETATION: For a wide range of blood pressures, the rate of cardiovascular disease and effectiveness of blood pressure drug treatment was mainly determined by predicted risk, with blood pressure thresholds 140/90 mm Hg or 160/100 mm Hg-ubiquitous in most countries-adding little useful information. When medium-term predicted risk is low, there is no urgency to initiate drug treatment, allowing time to attempt non-pharmacological blood pressure reduction. FUNDING: National Institute for Health Research.

Pharmacogenomic alerts: Developing guidance for use by healthcare professionals.

AIMS: For diseases with a genetic cause, genomics can deliver improved diagnostics and facilitate access to targeted treatments. Drug pharmacodynamics and pharmacokinetics are often dependent on genetic variation underlying these processes. As pharmacogenomics comes of age, it may be the first way in which genomics is utilised at a population level. Still required is guidance and standards of how genomic information can be communicated within the health record, and how clinicians should be alerted to variation impacting the use of medicines. METHODS: The Professional Record Standards Body commissioned by NHS England developed guidance on using pharmacogenomics information in clinical practice. We conducted research with those implementing pharmacogenomics in England and internationally to produce guidance and recommendations for a systems-based approach. RESULTS: A consensus viewpoint is that systems need to be in place to ensure the safe provision of pharmacogenomics information that is curated, actionable and up-to-date. Standards should be established with respect to notification and information exchange, which could impact new or existing prescribing and these must be in keeping with routine practice. Alerting systems should contribute to safer practices. CONCLUSION: Ensuring pharmacogenetics information is available to make safer use of medicines will require a major effort, of which this guidance is a beginning. Standards are required to ensure useful genomic information within the health record can be communicated to clinicians in the right format and at the right times to be actioned successfully. A multidisciplinary group of stakeholders must be engaged in developing pharmacogenomic standards to support the most appropriate prescribing.