Healthcare utilisation in people with long COVID: an OpenSAFELY cohort study.

BACKGROUND: Long COVID potentially increases healthcare utilisation and costs. However, its impact on the NHS remains to be determined. METHODS: This study aims to assess the healthcare utilisation of individuals with long COVID. With the approval of NHS England, we conducted a matched cohort study using primary and secondary care data via OpenSAFELY, a platform for analysing anonymous electronic health records. The long COVID exposure group, defined by diagnostic codes, was matched with five comparators without long COVID between Nov 2020 and Jan 2023. We compared their total healthcare utilisation from GP consultations, prescriptions, hospital admissions, A&E visits, and outpatient appointments. Healthcare utilisation and costs were evaluated using a two-part model adjusting for covariates. Using a difference-in-difference model, we also compared healthcare utilisation after long COVID with pre-pandemic records. RESULTS: We identified 52,988 individuals with a long COVID diagnosis, matched to 264,867 comparators without a diagnosis. In the 12 months post-diagnosis, there was strong evidence that those with long COVID were more likely to use healthcare resources (OR: 8.29, 95% CI: 7.74-8.87), and have 49% more healthcare utilisation (RR: 1.49, 95% CI: 1.48-1.51). Our model estimated that the long COVID group had 30 healthcare visits per year (predicted mean: 29.23, 95% CI: 28.58-29.92), compared to 16 in the comparator group (predicted mean visits: 16.04, 95% CI: 15.73-16.36). Individuals with long COVID were more likely to have non-zero healthcare expenditures (OR = 7.66, 95% CI = 7.20-8.15), with costs being 44% higher than the comparator group (cost ratio = 1.44, 95% CI: 1.39-1.50). The long COVID group costs approximately £2500 per person per year (predicted mean cost: £2562.50, 95% CI: £2335.60-£2819.22), and the comparator group costs £1500 (predicted mean cost: £1527.43, 95% CI: £1404.33-1664.45). Historically, individuals with long COVID utilised healthcare resources more frequently, but their average healthcare utilisation increased more after being diagnosed with long COVID, compared to the comparator group. CONCLUSIONS: Long COVID increases healthcare utilisation and costs. Public health policies should allocate more resources towards preventing, treating, and supporting individuals with long COVID.

Impact of long COVID on health-related quality-of-life: an OpenSAFELY population cohort study using patient-reported outcome measures (OpenPROMPT).

Background: Long COVID is a major problem affecting patient health, the health service, and the workforce. To optimise the design of future interventions against COVID-19, and to better plan and allocate health resources, it is critical to quantify the health and economic burden of this novel condition. We aimed to evaluate and estimate the differences in health impacts of long COVID across sociodemographic categories and quantify this in Quality-Adjusted Life-Years (QALYs), widely used measures across health systems. Methods: With the approval of NHS England, we utilised OpenPROMPT, a UK cohort study measuring the impact of long COVID on health-related quality-of-life (HRQoL). OpenPROMPT invited responses to Patient Reported Outcome Measures (PROMs) using a smartphone application and recruited between November 2022 and October 2023. We used the validated EuroQol EQ-5D questionnaire with the UK Value Set to develop disutility scores (1-utility) for respondents with and without Long COVID using linear mixed models, and we calculated subsequent Quality-Adjusted Life-Months (QALMs) for long COVID. Findings: The total OpenPROMPT cohort consisted of 7575 individuals who consented to data collection, with which we used data from 6070 participants who completed a baseline research questionnaire where 24.6% self-reported long COVID. In multivariable regressions, long COVID had a consistent impact on HRQoL, showing a higher likelihood or odds of reporting loss in quality-of-life (Odds Ratio (OR): 4.7, 95% CI: 3.72-5.93) compared with people who did not report long COVID. Reporting a disability was the largest predictor of losses of HRQoL (OR: 17.7, 95% CI: 10.37-30.33) across survey responses. Self-reported long COVID was associated with an 0.37 QALM loss. Interpretation: We found substantial impacts on quality-of-life due to long COVID, representing a major burden on patients and the health service. We highlight the need for continued support and research for long COVID, as HRQoL scores compared unfavourably to patients with conditions such as multiple sclerosis, heart failure, and renal disease. Funding: This research was supported by the National Institute for Health and Care Research (NIHR) (OpenPROMPT: COV-LT2-0073).

Clinical coding of long COVID in primary care 2020-2023 in a cohort of 19 million adults: an OpenSAFELY analysis.

Background: Long COVID is the patient-coined term for the persistent symptoms of COVID-19 illness for weeks, months or years following the acute infection. There is a large burden of long COVID globally from self-reported data, but the epidemiology, causes and treatments remain poorly understood. Primary care is used to help identify and treat patients with long COVID and therefore Electronic Health Records (EHRs) of past COVID-19 patients could be used to help fill these knowledge gaps. We aimed to describe the incidence and differences in demographic and clinical characteristics in recorded long COVID in primary care records in England. Methods: With the approval of NHS England we used routine clinical data from over 19 million adults in England linked to SARS-COV-2 test result, hospitalisation and vaccination data to describe trends in the recording of 16 clinical codes related to long COVID between November 2020 and January 2023. Using OpenSAFELY, we calculated rates per 100,000 person-years and plotted how these changed over time. We compared crude and adjusted (for age, sex, 9 NHS regions of England, and the dominant variant circulating) rates of recorded long COVID in patient records between different key demographic and vaccination characteristics using negative binomial models. Findings: We identified a total of 55,465 people recorded to have long COVID over the study period, which included 20,025 diagnoses codes and 35,440 codes for further assessment. The incidence of new long COVID records increased steadily over 2021, and declined over 2022. The overall rate per 100,000 person-years was 177.5 cases in women (95% CI: 175.5-179) and 100.5 in men (99.5-102). The majority of those with a long COVID record did not have a recorded positive SARS-COV-2 test 12 or more weeks before the long COVID record. Interpretation: In this descriptive study, EHR recorded long COVID was very low between 2020 and 2023, and incident records of long COVID declined over 2022. Using EHR diagnostic or referral codes unfortunately has major limitations in identifying and ascertaining true cases and timing of long COVID. Funding: This research was supported by the National Institute for Health and Care Research (NIHR) (OpenPROMPT: COV-LT2-0073).

Comparative effectiveness of nirmatrelvir/ritonavir versus sotrovimab and molnupiravir for preventing severe COVID-19 outcomes in non-hospitalised high-risk patients during Omicron waves: observational cohort study using the OpenSAFELY platform.

Background: Timely evidence of the comparative effectiveness between COVID-19 therapies in real-world settings is needed to inform clinical care. This study aimed to compare the effectiveness of nirmatrelvir/ritonavir versus sotrovimab and molnupiravir in preventing severe COVID-19 outcomes in non-hospitalised high-risk COVID-19 adult patients during Omicron waves. Methods: With the approval of NHS England, we conducted a real-world cohort study using the OpenSAFELY-TPP platform. Patient-level primary care data were obtained from 24 million people in England and were securely linked with data on COVID-19 infection and therapeutics, hospital admission, and death, covering a period where both nirmatrelvir/ritonavir and sotrovimab were first-line treatment options in community settings (February 10, 2022-November 27, 2022). Molnupiravir (third-line option) was used as an exploratory comparator to nirmatrelvir/ritonavir, both of which were antivirals. Cox proportional hazards model stratified by area was used to compare the risk of 28-day COVID-19 related hospitalisation/death across treatment groups. Findings: A total of 9026 eligible patients treated with nirmatrelvir/ritonavir (n = 5704) and sotrovimab (n = 3322) were included in the main analysis. The mean age was 52.7 (SD = 14.9) years and 93% (8436/9026) had three or more COVID-19 vaccinations. Within 28 days after treatment initiation, 55/9026 (0.61%) COVID-19 related hospitalisations/deaths were observed (34/5704 [0.60%] treated with nirmatrelvir/ritonavir and 21/3322 [0.63%] with sotrovimab). After adjusting for demographics, high-risk cohort categories, vaccination status, calendar time, body mass index and other comorbidities, we observed no significant difference in outcome risk between nirmatrelvir/ritonavir and sotrovimab users (HR = 0.89, 95% CI: 0.48-1.63; P = 0.698). Results from propensity score weighted model also showed non-significant difference between treatment groups (HR = 0.82, 95% CI: 0.45-1.52; P = 0.535). The exploratory analysis comparing nirmatrelvir/ritonavir users with 1041 molnupiravir users (13/1041 [1.25%] COVID-19 related hospitalisations/deaths) showed an association in favour of nirmatrelvir/ritonavir (HR = 0.45, 95% CI: 0.22-0.94; P = 0.033). Interpretation: In routine care of non-hospitalised high-risk adult patients with COVID-19 in England, no substantial difference in the risk of severe COVID-19 outcomes was observed between those who received nirmatrelvir/ritonavir and sotrovimab between February and November 2022, when Omicron subvariants BA.2, BA.5, or BQ.1 were dominant. Funding: UK Research and Innovation, Wellcome Trust, UK Medical Research Council, National Institute for Health and Care Research, and Health Data Research UK.

Acute Cardiovascular Events After COVID-19 in England in 2020: A Self-Controlled Case Series Study.

Purpose: To assess the risk of incident cardiovascular outcomes after COVID-19 by level of cardiovascular risk in waves one and two of the pandemic in England in 2020. Patients and methods: We conducted a self-controlled case-series study among adults aged 40-84 years with no pre-existing cardiovascular disease using linked data from the Clinical Practice Research Datalink. We generated season-adjusted incidence ratios (IRs) for first acute cardiovascular event after SARS-CoV-2 infection compared with baseline time before and >91 days after infection. We used composite and individual acute cardiovascular event outcomes including myocardial infarction, major ventricular arrhythmia, left ventricular heart failure, and ischemic stroke. We stratified by cardiovascular risk, using diagnosed hypertension and QRISK3 predicted risk, and by wave one and two of the pandemic. Results: We included 1762 individuals, 76.6% had a QRISK3 score ≥10% and 59.4% had hypertension. The risk of any cardiovascular event was elevated in the 1-7 days after infection (IR 7.14 [95% CI 6.06-8.41]) and, while the effect size tapered, the risk remained for 15-28 days after infection (1.74 [1.33-2.26]). Risks were similar for individual event type, differing by level of cardiovascular risk, and in wave one and two of the pandemic. . Conclusion: SARS-CoV-2 infection is associated with early elevations in the risk of first acute cardiovascular event, across cardiovascular risk levels and in both wave one and two of the pandemic. Prevention of COVID-19 is important to avert cardiovascular complications.

Living alone and mental health: parallel analyses in UK longitudinal population surveys and electronic health records prior to and during the COVID-19 pandemic.

BACKGROUND: People who live alone experience greater levels of mental illness; however, it is unclear whether the COVID-19 pandemic had a disproportionately negative impact on this demographic. OBJECTIVE: To describe the mental health gap between those who live alone and with others in the UK prior to and during the COVID-19 pandemic. METHODS: Self-reported psychological distress and life satisfaction in 10 prospective longitudinal population surveys (LPSs) assessed in the nearest pre-pandemic sweep and three periods during the pandemic. Recorded diagnosis of common and severe mental illnesses between March 2018 and January 2022 in electronic healthcare records (EHRs) within the OpenSAFELY-TPP. FINDINGS: In 37 544 LPS participants, pooled models showed greater psychological distress (standardised mean difference (SMD): 0.09 (95% CI: 0.04; 0.14); relative risk: 1.25 (95% CI: 1.12; 1.39)) and lower life satisfaction (SMD: -0.22 (95% CI: -0.30; -0.15)) for those living alone pre-pandemic. This gap did not change during the pandemic. In the EHR analysis of c.16 million records, mental health conditions were more common in those who lived alone (eg, depression 26 (95% CI: 18 to 33) and severe mental illness 58 (95% CI: 54 to 62) more cases more per 100 000). For common mental health disorders, the gap in recorded cases in EHRs narrowed during the pandemic. CONCLUSIONS: People living alone have poorer mental health and lower life satisfaction. During the pandemic, this gap in self-reported distress remained; however, there was a narrowing of the gap in service use. CLINICAL IMPLICATIONS: Greater mental health need and potentially greater barriers to mental healthcare access for those who live alone need to be considered in healthcare planning.

Ethnic differences in the indirect effects of the COVID-19 pandemic on clinical monitoring and hospitalisations for non-COVID conditions in England: a population-based, observational cohort study using the OpenSAFELY platform.

Background: The COVID-19 pandemic disrupted healthcare and may have impacted ethnic inequalities in healthcare. We aimed to describe the impact of pandemic-related disruption on ethnic differences in clinical monitoring and hospital admissions for non-COVID conditions in England. Methods: In this population-based, observational cohort study we used primary care electronic health record data with linkage to hospital episode statistics data and mortality data within OpenSAFELY, a data analytics platform created, with approval of NHS England, to address urgent COVID-19 research questions. We included adults aged 18 years and over registered with a TPP practice between March 1, 2018, and April 30, 2022. We excluded those with missing age, sex, geographic region, or Index of Multiple Deprivation. We grouped ethnicity (exposure), into five categories: White, Asian, Black, Other, and Mixed. We used interrupted time-series regression to estimate ethnic differences in clinical monitoring frequency (blood pressure and Hba1c measurements, chronic obstructive pulmonary disease and asthma annual reviews) before and after March 23, 2020. We used multivariable Cox regression to quantify ethnic differences in hospitalisations related to diabetes, cardiovascular disease, respiratory disease, and mental health before and after March 23, 2020. Findings: Of 33,510,937 registered with a GP as of 1st January 2020, 19,064,019 were adults, alive and registered for at least 3 months, 3,010,751 met the exclusion criteria and 1,122,912 were missing ethnicity. This resulted in 14,930,356 adults with known ethnicity (92% of sample): 86.6% were White, 7.3% Asian, 2.6% Black, 1.4% Mixed ethnicity, and 2.2% Other ethnicities. Clinical monitoring did not return to pre-pandemic levels for any ethnic group. Ethnic differences were apparent pre-pandemic, except for diabetes monitoring, and remained unchanged, except for blood pressure monitoring in those with mental health conditions where differences narrowed during the pandemic. For those of Black ethnicity, there were seven additional admissions for diabetic ketoacidosis per month during the pandemic, and relative ethnic differences narrowed during the pandemic compared to the White ethnic group (Pre-pandemic hazard ratio (HR): 0.50, 95% confidence interval (CI) 0.41, 0.60, Pandemic HR: 0.75, 95% CI: 0.65, 0.87). There was increased admissions for heart failure during the pandemic for all ethnic groups, though highest in those of White ethnicity (heart failure risk difference: 5.4). Relatively, ethnic differences narrowed for heart failure admission in those of Asian (Pre-pandemic HR 1.56, 95% CI 1.49, 1.64, Pandemic HR 1.24, 95% CI 1.19, 1.29) and Black ethnicity (Pre-pandemic HR 1.41, 95% CI: 1.30, 1.53, Pandemic HR: 1.16, 95% CI 1.09, 1.25) compared with White ethnicity. For other outcomes the pandemic had minimal impact on ethnic differences. Interpretation: Our study suggests that ethnic differences in clinical monitoring and hospitalisations remained largely unchanged during the pandemic for most conditions. Key exceptions were hospitalisations for diabetic ketoacidosis and heart failure, which warrant further investigation to understand the causes. Funding: LSHTM COVID-19 Response Grant (DONAT15912).

Severe COVID-19 outcomes by cardiovascular risk profile in England in 2020: a population-based cohort study.

Background: While cardiovascular disease (CVD) is a risk factor for severe COVID-19, the association between predicted cardiovascular risk and severe COVID-19 among people without diagnosed CVD is unclear. Methods: We carried out historical, population-based cohort studies among adults aged 40-84 years in England using linked data from the Clinical Practice Research Datalink. Individuals were categorized into: existing CVD, raised cardiovascular risk (defined using QRISK3 score ≥10%) and low risk (QRISK3 score <10%) at 12/03/2020. We described incidence and severe outcomes of COVID-19 (deaths, intensive care unit [ICU] admissions, hospitalisations, major adverse cardiovascular events [MACE]) for each group. Among those with a COVID-19 record to 31/12/2020, we re-classified cardiovascular risk at infection and assessed the risk of severe outcomes using multivariable Cox regression with complete case analysis. We repeated analyses using hypertension to define raised cardiovascular risk. Findings: Among 6,059,055 individuals, 741,913 (12.2%) had established CVD, 1,929,627 (31.8%) had a QRISK3 score ≥10% and 3,387,515 (55.9%) had a QRISK3 score <10%. Marked gradients were seen in the incidence of all severe COVID-19 outcomes by cardiovascular risk profile. Among those with COVID-19 (N = 146,760), there was a strong association between raised QRISK3 score and death: adjusted hazard ratio [aHR] 8.77 (7.62-10.10), N = 97,725, which remained present, though attenuated in age-stratified results. Risks of other outcomes were also higher among those with raised QRISK3 score: aHR 3.66 (3.18-4.21) for ICU admissions, 3.38 (3.22-3.56) for hospitalisations, 5.43 (4.44-6.64) for MACE. When raised cardiovascular risk was redefined by hypertension status, only the association with MACE remained: aHR 1.49 (1.20-1.85), N = 57,264. Interpretation: Individuals without pre-existing CVD but with raised cardiovascular risk (by QRISK3 score) were more likely to experience severe COVID-19 outcomes and should be prioritised for prevention and treatment. Addressing cardiovascular risk factors could improve COVID-19 outcomes. Funding: BMA Foundation for Medical Research/Rosetrees Trust, Wellcome, BHF.

Protocol for an OpenSAFELY cohort study collecting patient-reported outcome measures using the TPP Airmid smartphone application and linked big data to quantify the health and economic costs of long COVID (OpenPROMPT).

INTRODUCTION: The impact of long COVID on health-related quality of-life (HRQoL) and productivity is not currently known. It is important to understand who is worst affected by long COVID and the cost to the National Health Service (NHS) and society, so that strategies like booster vaccines can be prioritised to the right people. OpenPROMPT aims to understand the impact of long COVID on HRQoL in adults attending English primary care. METHODS AND ANALYSIS: We will ask people to participate in this cohort study through a smartphone app (Airmid), and completing a series of questionnaires held within the app. Questionnaires will ask about HRQoL, productivity and symptoms of long COVID. Participants will be asked to fill in the questionnaires once a month, for 90 days. Questionnaire responses will be linked, where possible, to participants' existing health records from primary care, secondary care, and COVID testing and vaccination data. Analysis will take place using the OpenSAFELY data platform and will estimate the impact of long COVID on HRQoL, productivity and cost to the NHS. ETHICS AND DISSEMINATION: The Proportionate Review Sub-Committee of the South Central-Berkshire B Research Ethics Committee has reviewed and approved the study and have agreed that we can ask people to take part (22/SC/0198). Our results will provide information to support long-term care, and make recommendations for prevention of long COVID in the future. TRIAL REGISTRATION NUMBER: NCT05552612.

Primary prevention of acute cardiovascular events by influenza vaccination: an observational study.

AIMS: Previous studies show a reduced incidence of first myocardial infarction and stroke 1-3 months after influenza vaccination, but it is unclear how underlying cardiovascular risk impacts the association. METHODS AND RESULTS: The study used linked Clinical Practice Research Datalink, Hospital Episode Statistics Admitted Patient Care and Office for National Statistics mortality data from England between 1 September 2008 and 31 August 2019. From the data, individuals aged 40-84 years with a first acute cardiovascular event and influenza vaccination occurring within 12 months of each September were selected. Using a self-controlled case series analysis, season-adjusted cardiovascular risk stratified incidence ratios (IRs) for cardiovascular events after vaccination compared with baseline time before and >120 days after vaccination were generated. 193 900 individuals with a first acute cardiovascular event and influenza vaccine were included. 105 539 had hypertension and 172 050 had a QRISK2 score ≥10%. In main analysis, acute cardiovascular event risk was reduced in the 15-28 days after vaccination [IR 0.72 (95% CI 0.70-0.74)] and, while the effect size tapered, remained reduced to 91-120 days after vaccination [0.83 (0.81-0.88)]. Reduced cardiovascular events were seen after vaccination among individuals of all age groups and with raised and low cardiovascular risk. CONCLUSIONS: Influenza vaccine may offer cardiovascular benefit among individuals at varying cardiovascular risk. Further studies are needed to characterize the populations who could derive the most cardiovascular benefits from vaccination.

Cancer history as a predictor in cardiovascular risk scores: a primary care cohort study.

BACKGROUND: Cardiovascular risks are raised in cancer survivors but cancer history is not included in cardiovascular risk scores that inform preventive decisions. AIM: To assess whether cancer diagnosis should be included in cardiovascular risk scores. DESIGN AND SETTING: Cohort study using data from English general practices linked to hospital, cancer registration, and death registration data from 1990 to 2015. METHOD: Adults alive 1 year after a first cancer diagnosis and age, sex, general practice, and calendar- time matched cancer-free individuals were included. Individuals with <2 years of follow-up before index, recent statin prescriptions, or pre-existing coronary heart or cerebrovascular disease were excluded. Cox proportional hazard models used to develop QRISK3 scores were replicated with added cancer history variables. Whether independent hazard ratios for these variables met thresholds for inclusion in QRISK3 (>10% relative difference with P<0.01) was assessed. RESULTS: In total, 81 420 cancer survivors and 413 547 cancer-free individuals were followed for a median 5.2 years (interquartile range [IQR] 2.8- 9.1) and 6.3 years (IQR 3.5-10.2), respectively. Including a 1-year cancer survivorship variable in a QRISK3-based model met the threshold for inclusion for males (independent hazard ratio [iHR] 1.16, 95% confidence interval [CI] = 1.11 to 1.20, P<0.001) but not females (iHR 1.07, 95% CI = 1.01 to 1.14, P = 0.02). When including cancer type, the threshold was met for both sexes with history of haematological cancer (males: iHR 1.27, 95% CI = 1.16 to 1.40, P <0.001; females: iHR 1.59, 95% CI = 1.32 to 1.91, P<0.001) and for males but not females with history of solid cancers (males: iHR 1.13, 95% CI = 1.08 to 1.18, P <0.001; females: iHR 1.04, 95% CI = 0.98 to 1.10, P = 0.19). CONCLUSION: Developers should consider including cancer history variables in future cardiovascular risk models.

Association between household composition and severe COVID-19 outcomes in older people by ethnicity: an observational cohort study using the OpenSAFELY platform.

BACKGROUND: Ethnic differences in the risk of severe COVID-19 may be linked to household composition. We quantified the association between household composition and risk of severe COVID-19 by ethnicity for older individuals. METHODS: With the approval of NHS England, we analysed ethnic differences in the association between household composition and severe COVID-19 in people aged 67 or over in England. We defined households by number of age-based generations living together, and used multivariable Cox regression stratified by location and wave of the pandemic and accounted for age, sex, comorbidities, smoking, obesity, housing density and deprivation. We included 2 692 223 people over 67 years in Wave 1 (1 February 2020-31 August 2020) and 2 731 427 in Wave 2 (1 September 2020-31 January 2021). RESULTS: Multigenerational living was associated with increased risk of severe COVID-19 for White and South Asian older people in both waves [e.g. Wave 2, 67+ living with three other generations vs 67+-year-olds only: White hazard ratio (HR) 1.61 95% CI 1.38-1.87, South Asian HR 1.76 95% CI 1.48-2.10], with a trend for increased risks of severe COVID-19 with increasing generations in Wave 2. There was also an increased risk of severe COVID-19 in Wave 1 associated with living alone for White (HR 1.35 95% CI 1.30-1.41), South Asian (HR 1.47 95% CI 1.18-1.84) and Other (HR 1.72 95% CI 0.99-2.97) ethnicities, an effect that persisted for White older people in Wave 2. CONCLUSIONS: Both multigenerational living and living alone were associated with severe COVID-19 in older adults. Older South Asian people are over-represented within multigenerational households in England, especially in the most deprived settings, whereas a substantial proportion of White older people live alone. The number of generations in a household, number of occupants, ethnicity and deprivation status are important considerations in the continued roll-out of COVID-19 vaccination and targeting of interventions for future pandemics.

Alcohol use recording in adults with depression in English primary care: a cross-sectional study.

OBJECTIVES: To investigate alcohol use recording in people with newly diagnosed depression in English primary care and individual characteristics associated with the recording of alcohol use. DESIGN: A population-based cross-sectional study. SETTING: Primary care data from English practices contributing to the UK Clinical Practice Research Datalink. PARTICIPANTS: We included adults (18+ years) diagnosed with depression between 1 January 2011 and 1 January 2017 without previous antidepressant use and at least 1 year of registration before diagnosis. PRIMARY AND SECONDARY OUTCOME MEASURES: We described the proportion of individuals with alcohol use and level of alcohol use recorded at four time points (the date of depression diagnosis, 3 months before or after depression diagnosis, 12 months before or after depression diagnosis and any point pre or postdepression diagnosis). We used logistic regression to investigate individual characteristics associated with alcohol use recording in the 3 months before or after depression diagnosis. RESULTS: We identified 36 424 adults with depression. 538 (2%) had alcohol use recorded in the 3 months before or after depression diagnosis using formal validated methods such as the Alcohol Use Disorders Identification Test and its abbreviated versions. At each time point, most individuals with alcohol use recorded were low risk drinkers. Alcohol use recording in the 3 months before or after depression diagnosis was associated with male sex (OR=1.38, 95% CI 1.29 to 1.48) and several other individual-level factors. CONCLUSIONS: Our study shows low levels of alcohol use recording in the 3 months before or after depression diagnosis. Levels of alcohol use recording varied depending on individual characteristics. Incentivised recording of alcohol use will increase completeness, which could improve clinical management and reduce missed opportunities for care in people with depression.

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.

Incidence of Inflammatory Bowel Disease in South Asian and Chinese People: A Population-Based Cohort Study from Ontario, Canada.

BACKGROUND: Inflammatory bowel disease (IBD) is now a global disease with incidence increasing throughout Asia. AIM: To determine the incidence of IBD among South Asians and Chinese people residing in Ontario, Canada's most populous province. METHODS: All incident cases of IBD in children (1994-2015) and adults (1999-2015) were identified from population-based health administrative data. We classified South Asian and Chinese ethnicity using immigration records and surnames. We determined standardized incidence of IBD and adjusted incidence rate ratio (aIRR) in South Asians and Chinese compared to the general population. RESULTS: Among 16,230,638 people living in Ontario, standardized incidence of IBD per 100,000 person-years was 24.7 (95% CI 24.4-25.0), compared with 14.6 (95% CI 13.7-15.5) in 982,472 South Asians and with 5.4 (95% CI 4.8-5.9) in 764,397 Chinese. The risk of IBD in South Asians was comparable to the general population after adjusting for immigrant status and confounders (aIRR 1.03, 95% CI 0.96-1.10). South Asians had a lower risk of Crohn's disease (CD) (aIRR 0.66, 95% CI 0.60-0.77), but a higher risk of ulcerative colitis (UC) (aIRR 1.47, 95% CI 1.34-1.61). Chinese people had much lower rates of IBD (aIRR 0.24, 95% CI 0.20-0.28), CD (aIRR 0.21, 95% CI 0.17-0.26), and UC (aIRR 0.28, 95% CI 0.23-0.25). CONCLUSION: Canadians of South Asian ethnicity had a similarly high risk of developing IBD compared to other Canadians, and a higher risk of developing UC, a finding distinct from the Chinese population. Our findings indicate the importance of genetic and environmental risk factors in people of Asian origin who live in the Western world.

Risk of acute respiratory infection and acute cardiovascular events following acute respiratory infection among adults with increased cardiovascular risk in England between 2008 and 2018: a retrospective, population-based cohort study.

BACKGROUND: Although acute respiratory infections can lead to cardiovascular complications, the effect of underlying cardiovascular risk on the incidence of acute respiratory infections and cardiovascular complications following acute respiratory infection in individuals without established cardiovascular disease is unknown. We aimed to investigate whether cardiovascular risk is associated with increased risk of acute respiratory infection and acute cardiovascular events after acute respiratory infection using 10 years of linked electronic health record (EHR) data in England. METHODS: In this retrospective, population-based cohort study we used EHRs from primary care providers registered on the Clinical Practice Research Datalink (CPRD) GOLD and Aurum databases in England. Eligible individuals were aged 40-64 years, did not have established cardiovascular disease or a chronic health condition that would make them eligible for influenza vaccination, were registered at a general practice contributing to the CPRD, and had linked Hospital Episode Statistics Admitted Patient Care data in England from Sept 1, 2008, to Aug 31, 2018. We classified cardiovascular risk on the basis of diagnosed hypertension and overall predicted cardiovascular risk, estimated by use of the QRISK2 risk-prediction tool (comparing a score of ≥10% [increased risk] with a score of <10% [low risk]). Using multivariable Poisson regression models, we calculated incidence rate ratios (IRRs) for systemic acute respiratory infection. Among individuals who had an acute respiratory infection, we used multivariable Cox regression to calculate hazard ratios (HRs) for the risk of acute cardiovascular events within 1 year of infection. FINDINGS: We identified 6 075 321 individuals aged 40-64 years with data in the CPRD and linked data in the Hospital Episode Statistics Admitted Patient Care database between Sept 1, 2008, and Aug 31, 2018. Of these individuals, 4 212 930 (including 526 480 [12·5%] with hypertension and 607 087 [14·4%] with a QRISK2 score of ≥10%) were included in the assessment of the incidence of acute respiratory infection. After adjusting for confounders (age, sex, ethnicity, socioeconomic status, body-mass index, alcohol consumption, smoking status, and consultation frequency in the hypertension analysis; and alcohol consumption and consultation frequency in the QRISK2 analysis), the incidence of acute respiratory infection was higher in individuals with hypertension than those without (IRR 1·04 [95% CI 1·03-1·05]) and higher in those with a QRISK2 score of 10% or higher than in those with a QRISK2 score of less than 10% (1·39 [1·37-1·40]). Of the 442 408 individuals who had an acute respiratory infection, 4196 (0·9%) had an acute cardiovascular event within 1 year of infection. After adjustment (for age, sex, ethnicity, socioeconomic status, body-mass index, alcohol consumption, and smoking status in the hypertension analysis; and for alcohol consumption in the QRISK2 analysis), hypertension (HR 1·98 [95% CI 1·83-2·15]) and a QRISK2 score of 10% or higher (3·65 [3·42-3·89]) were associated with a substantially increased risk of acute cardiovascular events after acute respiratory infection. INTERPRETATION: People with increased cardiovascular risk but without diagnosed cardiovascular disease, measured by diagnosed hypertension or overall predicted cardiovascular risk, could benefit from influenza and pneumococcal vaccine prioritisation to reduce their risk of both acute respiratory infection and cardiovascular complications following an acute respiratory infection. FUNDING: British Heart Foundation and the Wellcome Trust.

The effect of statins on muscle symptoms in primary care: the StatinWISE series of 200 N-of-1 RCTs.

BACKGROUND: Uncertainty persists about whether or not statins cause symptomatic muscle adverse effects (e.g. pain, stiffness and weakness) in the absence of severe myositis. OBJECTIVES: To establish the effect of statins on all muscle symptoms, and the effect of statins on muscle symptoms that are perceived to be statin related. DESIGN: A series of 200 double-blinded N-of-1 trials. SETTING: Participants were recruited from 50 general practices in England and Wales. PARTICIPANTS: Patients who were considering discontinuing statin use and those who had discontinued statin use in the last 3 years because of perceived muscle symptoms. INTERVENTIONS: Participants were randomised to a sequence of six 2-month treatment periods during which they received 20 mg of atorvastatin daily or a matched placebo. MAIN OUTCOME MEASURES: The primary outcome was self-reported muscle symptoms rated using a visual analogue scale on the last week of each treatment period. Secondary outcomes included the participant's belief about the cause of their muscle symptoms, the site of muscle symptoms, how the muscle symptoms affected the participant, any other symptoms they experienced, adherence to medication, the participant's decision about statin treatment following the trial, and whether or not they found their own trial result helpful. RESULTS: A total of 151 out of 200 (75.5%) randomised participants provided one or more visual analogue scale measurements in a placebo period and one or more measurements in a statin period, and were included in the primary analysis. There was no evidence of a difference in muscle symptom scores between statin and placebo periods (mean difference statin minus placebo -0.11, 95% confidence interval -0.36 to 0.14; p = 0.398). Withdrawals, adherence and missing data were similar during the statin periods and the placebo periods. CONCLUSIONS: Among people who previously reported severe muscle symptoms while taking statins, this series of randomised N-of-1 trials found no overall effect of statins on muscle symptoms compared with the placebo. The slight difference in withdrawals due to muscle symptoms suggests that statins may contribute to symptoms in a small number of patients. The results are generalisable to patients who are considering discontinuing or have already discontinued statins because of muscle symptoms, and who are willing to re-challenge or participate in their own N-of-1 trial. FUTURE WORK: We recommend that additional statins and doses are explored using N-of-1 trials. More broadly, N-of-1 trials present a useful tool for exploring transient symptoms with other medications. LIMITATIONS: This study used 20-mg doses of atorvastatin only. Furthermore, a dropout rate of 43% was observed, but this was accounted for in the power calculations. TRIAL REGISTRATION: Current Controlled Trials ISRCTN30952488 and EudraCT 2016-000141-31. FUNDING: This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 25, No. 16. See the NIHR Journals Library website for further project information.

Statins are one of the most commonly prescribed drugs in the UK. There is strong evidence that they are effective in safely reducing heart disease; however, there is some doubt about whether or not statins cause muscle pain, stiffness or weakness. This research has been carried out to understand the effect of statins on muscle symptoms. To answer our question, we asked 200 volunteers from across England and Wales to participate in the study. Patients who joined the study either had recently stopped taking statins because of muscle symptoms or were considering stopping because of muscle symptoms. Patients who participated were randomly assigned to a sequence of six 2-month treatment periods during which they received either statins or a placebo. Neither patients nor their general practitioner knew which tablet they were receiving. This helped to reduce bias in the data. At the end of each treatment period, patients were asked to report any muscle symptoms, or any other symptoms, that they experienced. The key result of this work is that patients reported no difference, on average, in their muscle symptoms between periods of taking a statin and periods of taking a placebo. We also assessed the impact on the patient's quality of life by looking at how statins affected the following areas: general activity, mood, walking ability, normal work, relations with other people, sleep and enjoyment of life. As with muscle symptoms, there was no evidence of a difference between statin and placebo periods. The majority of patients who finished the trial decided to continue using statins after the trial. Future research should be carried out to assess different statin doses, as higher doses are often used following a heart attack. In addition, further work is needed to see how the approach we used could be adopted into everyday clinical care.

Statin treatment and muscle symptoms: series of randomised, placebo controlled n-of-1 trials.

OBJECTIVE: To establish the effect of statins on muscle symptoms in people who had previously reported muscle symptoms when taking statins. DESIGN: Series of randomised, placebo controlled n-of-1 trials. SETTING: Primary care across 50 sites in the United Kingdom, December 2016 to April 2018. PARTICIPANTS: 200 participants who had recently stopped or were considering stopping treatment with statins because of muscle symptoms. INTERVENTIONS: Participants were randomised to a sequence of six double blinded treatment periods (two months each) of atorvastatin 20 mg daily or placebo. MAIN OUTCOME MEASURES: At the end of each treatment period, participants rated their muscle symptoms on a visual analogue scale (0-10). The primary analysis compared symptom scores in the statin and placebo periods. RESULTS: 151 participants provided symptoms scores for at least one statin period and one placebo period and were included in the primary analysis. Overall, no difference in muscle symptom scores was found between the statin and placebo periods (mean difference statin minus placebo -0.11, 95% confidence interval -0.36 to 0.14; P=0.40)). Withdrawals because of intolerable muscle symptoms were 18 participants (9%) during a statin period and 13 (7%) during a placebo period. Two thirds of those completing the trial reported restarting long term treatment with statins. CONCLUSIONS: No overall effect of atorvastatin 20 mg on muscle symptoms compared with placebo was found in participants who had previously reported severe muscle symptoms when taking statins. Most people completing the trial intended to restart treatment with statins. N-of-1 trials can assess drug effects at the group level and guide individual treatment. TRIAL REGISTRATION: ISRCTN30952488, EUDRACT 2016-000141-31, NCT02781064.