Comparative safety and effectiveness of Pfizer BA.4-5 versus Sanofi during the spring 2023 COVID-19 booster vaccination programme in England: a matched cohort study in OpenSAFELY-TPP (preprint)

Introduction: The spring 2023 COVID-19 booster vaccination programme in England used both Pfizer BA.4-5 and Sanofi vaccines. All people aged 75 years or over and the clinically vulnerable were eligible to receive a booster dose. Direct comparisons of the effectiveness of these two vaccines in boosting protection against severe COVID-19 events have not been made in trials or observational data. Methods With the approval of NHS England, we used the OpenSAFELY-TPP database to compare effectiveness of the Pfizer BA.4-5 and Sanofi vaccines during the spring 2023 booster programme, between 1 April and 30 June 2023. We investigated two cohorts separately: those aged 75 or over (75+); and those aged 50 or over and clinically vulnerable (CV). In each cohort, vaccine recipients were matched on date of vaccination, COVID-19 vaccine history, age, and other characteristics. Effectiveness outcomes were COVID-19 hospital admission, COVID-19 critical care admission, and COVID-19 death up to 16 weeks after vaccination. Safety outcomes were pericarditis and myocarditis up to 4 weeks after vaccination. We report the cumulative incidence of each outcome, and compare safety and effectiveness using risk differences (RD), relative risks (RR), and incidence rate ratios (IRRs). Results 492,642 people were 1-1 matched in the CV cohort, and 673,926 in the 75+ cohort, contributing a total of 7,423,251 and 10,173,230 person-weeks of follow-up, respectively. The incidence of COVID-19 hospital admission was higher for Sanofi than for Pfizer BA.4-5. In the CV cohort, 16-week risks per 10,000 people were 22.3 (95%CI 20.4 to 24.3) for Pfizer BA.4-5 and 26.4 (24.4 to 28.7) for Sanofi, with an IRR of 1.19 (95%CI 1.06 to 1.34). In the 75+ cohort, these were 17.5 (16.1 to 19.1) for Pfizer BA.4-5 and 20.4 (18.9 to 22.1) for Sanofi, with an IRR of 1.18 (1.05-1.32). These findings were similar across all pre-specified subgroups. More severe COVID-19 related outcomes (critical care admission and death), and safety outcomes at 4 weeks, were rare in both vaccines so we could not reliably compare effectiveness of the two vaccines. Conclusion This observational study comparing effectiveness of Pfizer BA.4-5 and Sanofi vaccine during the spring 2023 programme in England in the two main eligible cohorts - people aged 75 and over and in clinically vulnerable people - found some evidence of superior effectiveness against COVID-19 hospital admission for Pfizer BA.4-5 compared with Sanofi within 16 weeks after vaccination.

Changes in opioid prescribing during the COVID-19 pandemic in England: cohort study of 20 million patients in OpenSAFELY-TPP (preprint)

Background: The COVID-19 pandemic led to disruptions in healthcare delivery, including postponement of elective procedures and difficulty accessing in-person care, which may have increased the need for strong pharmacological pain relief in some patients. Methods: With NHS England approval, we used routine clinical data from >20 million general practice adult patients in OpenSAFELY-TPP. We used interrupted time series analysis to quantify trends in prevalent and incident opioid prescribing prior to the pandemic (January 2018-February 2020) and changes during the COVID-19 lockdown period (March 2020-March 2021) and recovery period (April 2021-June 2022). We identified how these changes varied in people living in care homes, and by age, sex, deprivation, ethnicity, and geographic region. Results: The median number of people prescribed an opioid per month was 50.9 per 1000 patients prior to the pandemic. We observed little change in overall prescribing after the start of the pandemic, except for a temporary increase in March 2020. There was a 9.8% (95%CI -14.5%, -6.5%) reduction in new opioid prescribing from March 2020, sustained to the end of the study period. Reductions in new prescribing were observed for all demographics except people 80+ years. Among care home residents, in April 2020 new opioid prescribing increased by 112.5% (95%CI 92.2%, 134.9%) and parenteral opioid prescribing increased by 186.3% (95%CI 153.1%, 223.9%). Conclusion: Changes in opioid prescribing during the COVID-19 pandemic were mostly consistent across subgroups with the exception of differences by age and care home residence. Among people in care homes, increases in parenteral opioid prescribing likely reflect use to treat end-of-life COVID-19 symptoms. Further research is needed to understand what is driving the reduction in new opioid prescribing and its relation to changes to health care provision during the pandemic.

The safety of antivirals and neutralising monoclonal antibodies used in prehospital treatment of Covid-19 (preprint)

Objective This proof-of-principle pharmacovigilance study used Electronic Health Record (EHR) data to examine the safety of sotrovimab, paxlovid and molnupiravir in prehospital treatment of Covid-19. Method With NHS England approval, we conducted an observational cohort study using OpenSAFELY-TPP, a secure software-platform which executes analyses across EHRs for 24 million people in England. High-risk individuals with Covid-19 eligible for prehospital treatment were included. Adverse events (AEs) were categorised into events in the drugs Summary of Product Characteristics (SmPC), drug-reactions and immune-mediated. Cox models compared risk across treatments. A pre-pandemic record analysis was performed for comparative purposes. Results Between 2021-2023, 37,449 patients received sotrovimab, paxlovid or molnupiravir whilst 109,647 patients made up an eligible-but-untreated population. The 29-day rates of AEs were low: SmPC 0.34 per 1000 patient-years (95% CI 0.32-0.36); drug-reactions 0.01 (95% CI 0.01-0.02) and immune-mediated 0.03 (95% CI 0.03-0.04), and similar or lower than the pre-pandemic period. Compared with the eligible but untreated population, sotrovimab and paxlovid associated with a risk of SmPC AE [adjHR 1.36 (95% CI 1.15-1.62) and 1.28 (95% CI 1.05-1.55), respectively], whilst sotrovimab associated with a risk of drug-reactions [adjHR 2.95 (95% CI 1.56-5.55)] and immune-mediated events [adjHR 3.22 (95% CI 1.86-5.57)]. Conclusion Sotrovimab, paxlovid and molnupiravir demonstrate acceptable safety profiles. Although the risk of AEs was greatest with sotrovimab, event rates were lower than comparative pre-pandemic period.

Healthcare utilisation in people with long COVID: an OpenSAFELY cohort study (preprint)

BackgroundLong COVID, characterised by various symptoms and complications, potentially increases healthcare utilisation and costs. However, its impact on the NHS remains to be determined. ObjectiveThis study aims to assess the healthcare utilisation of individuals with long COVID. MethodsWith 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. ResultsWe 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: 8.07, 95% CI: 7.54 - 8.64), and have 49% more healthcare utilisation (RR: 1.49, 95% CI: 1.47 - 1.50). 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 = 7.47, 95% CI = 7.02 - 7.95), with costs being 43% higher than the comparator group (cost ratio = 1.43, 95% CI: 1.38 - 1.49). The long COVID group costs approximately {pound}2,500 per person per year (predicted mean cost: {pound}2,562.50, 95% CI: {pound}2,335.60 - {pound}2,819.22), and the comparator group costs {pound}1,500 (predicted mean cost: {pound}1,527.43, 95% CI: {pound}1,404.33 - 1,664.45.) 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. ConclusionLong COVID increases healthcare utilisation and costs. Public health policies should allocate more resources towards preventing, treating, and supporting individuals with long COVID.

Weight trends amongst adults with diabetes or hypertension during the COVID-19 pandemic: an observational study using OpenSAFELY (preprint)

AimsTo describe patterns of weight change amongst adults living in England with Type 2 Diabetes (T2D) and/or hypertension during the COVID-19 pandemic. Design and SettingWith the approval of NHS England, we conducted an observational cohort study using the routinely collected health data of approximately 40% of adults living in England, accessed through the OpenSAFELY service inside TPP. MethodWe estimated individual rates of weight gain during the pandemic ({delta}). We then estimated associations between clinical and sociodemographic characteristics and rapid weight gain (>0.5kg/m2/year) using multivariable logistic regression. ResultsWe extracted data on adults with T2D (n=1,231,455, 44% female, 76% white British) or hypertension (n=3,558,405, 50% female, 84% white British). Adults with T2D lost weight overall (median {delta} = -0.1kg/m2/year [IQR: -0.7, 0.4]), however, rapid weight gain was common (20.7%) and associated with sex (male vs female: aOR 0.78[95%CI 0.77, 0.79]); age, older age reduced odds (e.g. 60-69-year-olds vs 18-29-year-olds: aOR 0.66[0.61, 0.71]); deprivation, (least-deprived-IMD vs most-deprived-IMD: aOR 0.87[0.85, 0.89]); white ethnicity (Black vs White: aOR 0.70[0.69, 0.71]); mental health conditions (e.g. depression: aOR 1.13 [1.12, 1.15]); and diabetes treatment (non-insulin treatment vs no pharmacological treatment: aOR 0.68[0.67, 0.69]). Adults with hypertension maintained stable weight overall (median {delta} = 0.0kg/m2/year [-0.6, 0.5]), however, rapid weight gain was common (24.7%) and associated with similar characteristics as in T2D. ConclusionAmongst adults living in England with T2D and/or hypertension, rapid pandemic weight gain was more common amongst females, younger adults, those living in more deprived areas, and those with mental health conditions. How this fits inPrevious studies, in the general population, have reported female sex, deprivation and comorbid mental health conditions increased risk of unhealthy weight gain during the pandemic, but it is not clear whether people living with hypertensions and/or type 2 diabetes experienced the same trends. We found that, during the pandemic, adults with hypertension maintained a stable weight whilst those with type 2 diabetes lost weight overall. However, underlying these overall trends, rapid weight gain was common amongst people with type 2 diabetes (20.7%) or hypertension (24.7%)), with female sex, younger age, deprivation, and comorbid mental health conditions associated with an increased odds of rapid weight gain in both populations. We have identified clinical and sociodemographic characteristics of individuals with hypertension and/or type 2 diabetes who could benefit from primary care interventions on weight and health behaviours to combat health inequalities in patterns of weight gain that were exacerbated by the pandemic.

The impact of Long COVID on Health-Related Quality-of-life using OpenPROMPT (preprint)

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. Methods With the approval of NHS England, we developed 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. Results We used data from 6,070 participants where 24.7% self-reported long COVID. In multivariable regressions, long COVID had a consistent impact on HRQoL, showing a high probability of reporting loss in quality-of-life (OR: 22, 95% CI:12.35-39.29) compared with people who did not report long COVID. Reporting a disability was the largest predictor of losses of HRQoL (OR: 60.2, 95% CI: 27.79-130.57) across survey responses. Self-reported long COVID was associated with an 0.37 QALM loss. Conclusions 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.

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

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 those with 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. We calculated rates per 100,000 person-years and plotted how these changed over time. We compared crude and minimally adjusted 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, with incidence of new long COVID records increasing steadily over 2021, and declining over 2022. The overall rate per 100,000 person-years was 177.5 cases in women (95% CI: 175.5-179) and 100.5 men (99.5-102). In terms of vaccination against COVID-19, the lowest rates were observed in those with 3+ vaccine doses (103.5 [95% CI: 101.5-105]). Finally, the majority of those with a long COVID record did not have a recorded positive SARS-COV-2 test 12 weeks before the long COVID record. Interpretation EHR recorded long COVID remains very low compared and incident records of long COVID declined over 2022. We found the lowest rates of recorded long COVID in people with 3 or more vaccine doses. We summarised several sources of possible bias for researchers using EHRs to study long COVID. Funding This research was supported by the National Institute for Health and Care Research (NIHR) (OpenPROMPT: COV-LT2-0073))

Group A streptococcal cases and treatments during the COVID-19 pandemic and 2022 outbreak: a retrospective cohort study in England using OpenSAFELY-TPP (preprint)

ObjectiveTo investigate the impact of the COVID-19 pandemic on Group A streptococcal (GAS) cases and related antibiotic prescriptions. DesignA retrospective cohort study with supporting dashboards with the approval of NHS England. SettingPrimary care practices in England using TPP SystmOne software from January 2018 through March 2023. ParticipantsPatients included were those registered at a TPP practice for each month of the study period. Patients with missing sex or age were excluded, resulting in a population of 23,816,470 in January 2018, increasing to 25,541,940 by March 2023. Main outcome measuresWe calculated monthly counts and crude rates of GAS cases (sore throat/tonsillitis, scarlet fever, invasive group A strep) and prescriptions linked with a GAS case, before (pre-April 2020), during and after (post-April 2021) COVID-19 restrictions. We calculated the maximum and minimum count and rate for each season (years running September-August), and the rate ratio (RR) of the 2022/23 season to the last comparably high season (2017/18). ResultsRecording of GAS cases and antibiotic prescription linked with a GAS case peaked in December 2022, higher than the 2017/2018 peak. The peak rate of monthly sore throat/tonsillitis (possible group A strep throat) recording was 5.33 per 1,000 (RR 2022/23 versus 2017/18 1.39 (CI: 1.38 to 1.40)). Scarlet fever recording peaked at 0.51 per 1,000 (RR 2.68 (CI: 2.59 to 2.77)), and invasive group A streptococcal infection (iGAS) at 0.01 per 1,000 (RR 4.37 (CI: 2.94 to 6.48)). First line antibiotics with a record of a GAS infection peaked at 2.80 per 1,000 (RR 1.37 (CI:1.35 to 1.38)), alternative antibiotics at 2.03 per 1,000 (RR 2.30 (CI:2.26 to 2.34)), and reserved antibiotics at 0.09 per 1,000 (RR 2.42 (CI:2.24 to 2.61). For individual antibiotics, azithromycin with GAS indication showed the greatest relative increase (RR 7.37 (CI:6.22 to 8.74)).This followed a sharp drop in recording of cases and associated prescriptions during the period of COVID-19 restrictions where the maximum count and rates were lower than any pre COVID-19 minimum. More detailed demographic breakdowns can be found in our regularly updated dashboard report. ConclusionsRates of scarlet fever, sore throat/tonsillitis and iGAS recording and associated antibiotic prescribing peaked in December 2022. Primary care data can supplement existing infectious disease surveillance through linkages with relevant prescribing data and detailed clinical and demographic subgroups. What is knownDuring the COVID-19 pandemic there has been a substantial change to the pattern of circulating viruses and bacteria that cause illnesses. A spike in group A streptococcal infections in England starting December 2022 was associated with 426 deaths, including 48 children as of 7th May 2023. Increased demand for antibiotics in this period led to medicines shortages and the introduction of Serious Shortage Protocols (SSPs). Existing surveillance systems such as notifiable disease reports and GP in-hours surveillance bulletins describe clinical events, but they do not link to relevant prescribing data. What this study adds- This study supports the findings of routine surveillance reports which indicated a drop in GAS infections during the COVID-19 restrictions, followed by a spike in December 2022, demonstrating that the OpenSAFELY platform and primary care data can be used to rapidly describe not only clinical events but also relevant prescribing in the case of future outbreaks. - Antibiotic prescribing with a GAS indication, particularly for phenoxymethylpenicillin alternatives and reserved antibiotics, was higher in the December 2022 peak than in the 2017/2018 peak.

Fit notes associated with COVID-19 in 24 million patients' primary care records: A cohort study in OpenSAFELY-TPP (preprint)

Background: Fit notes ("sick notes") are issued by general practitioners (GPs) when a person can't work for health reasons and is an indication of the public health and economic burden for people recovering from COVID-19. Methods: With NHS England approval, we used routine clinical data from >24 million patients to compare fit note incidence in people 18-64 years with and without evidence of COVID-19 in 2020, 2021 and 2022. We fit Cox regression models to estimate adjusted hazard ratios, overall and by time post-diagnosis and within demographic subgroups. Results: We identified 365,421, 1,206,555 and 1,321,313 people with evidence of COVID-19 in 2020, 2021 and 2022. The fit note rate was 4.88 per 100 person-months (95%CI 4.83-4.93) in 2020, 2.66 (95%CI 2.64-2.67) in 2021, and 1.73 (95%CI 1.72-1.73) in 2022. Compared with the age, sex and region matched general population, the hazard ratio (HR) adjusted for demographics and clinical characteristics over the follow-up period was 4.07 (95%CI 4.02-4.12) in 2020 decreasing to 1.57 (95%CI 1.56-1.58) in 2022. The HR was highest in the first 30 days in all years. Conclusions: Despite likely underestimation of the fit note rate, we identified a considerable increase among people with COVID-19, even in an era when most people are vaccinated. Most fit notes are associated with the acute phase of the disease, but the increased risk several months post-diagnosis provides further evidence of the long-term impact.

The impact of COVID-19 on medication reviews in English primary care. An OpenSAFELY-TPP analysis of 20 million adult electronic health records. (preprint)

Background The COVID-19 pandemic caused significant disruption to routine activity in primary care. Medication reviews are an important primary care activity to ensure safety and appropriateness of ongoing prescribing and a disruption could have significant negative implications for patient care. Aim Using routinely collected data, our aim was to i) describe the SNOMED CT codes used to report medication review activity ii) report the impact of COVID-19 on the volume and variation of medication reviews. Design and setting With the approval of NHS England, we conducted a cohort study of 20 million adult patient records in general practice, in-situ using the OpenSAFELY platform. Method For each month between April 2019 - March 2022, we report the percentage of patients with a medication review coded monthly and in the previous 12 months. These measures were broken down by regional, clinical and demographic subgroups and amongst those prescribed high risk medications. Results In April 2019, 32.3% of patients had a medication review coded in the previous 12 months. During the first COVID-19 lockdown, monthly activity substantially decreased (-21.1% April 2020), but the rate of patients with a medication review coded in the previous 12 months was not substantially impacted according to our classification (-10.5% March 2021). There was regional and ethnic variation (March 2022 - London 21.9% vs North West 33.6%; Chinese 16.8% vs British 33.0%). Following the introduction of "structured medication reviews", the rate of structured medication review in the last 12 months reached 2.9% by March 2022, with higher percentages in high risk groups (March 2022 - care home residents 34.1%, 90+ years 13.1%, high risk medications 10.2%). The most used SNOMED CT medication review code across the study period was Medication review done - 314530002 (59.5%). Conclusion We have reported a substantial reduction in the monthly rate of medication reviews during the pandemic but rates recovered by the end of the study period.

Impact of COVID-19 on recorded blood pressure screening and hypertension management in England: An analysis of monthly changes in Quality and Outcomes Framework indicators in OpenSAFELY (preprint)

Background: Cardiovascular disease management in primary care in England was disrupted during the COVID-19 pandemic. Objective: We aim to describe the impact of the COVID-19 pandemic on blood pressure screening and hypertension management, based upon a national quality of care scheme (Quality and Outcomes Framework, QOF) across key demographic, regional, and clinical subgroups. To this end, we translate complex clinical quality of care schemes from text descriptions into reusable analytic code. Methods: With the approval of NHS England, a population based cohort study was conducted on 25.2 million patient records in situ using OpenSAFELY-TPP. We included all NHS patients registered at general practices using TPP software between March 2019 and March 2023. Individuals that were eligible for blood pressure screening and with a diagnosis of hypertension were identified according to the QOF 2021/22 business rules. We examined monthly changes in recorded blood pressure screening in the preceding 5 years in patients aged [≥] 45, recorded hypertension prevalence, and the recorded percentage of patients treated to target (i.e., [≤] 140/90 mmHg for patients [≤] 79 years and [≤] 150/90 mmHg for patients [≥] 80 years) in the preceding 12 months, within demographic, regional, and clinical subgroups as well as the variation across practices. Results: The overall percentage of patients aged [≥] 45 who had blood pressure screening recorded in the preceding 5 years decreased from 90% in March 2019 to 85% in March 2023. Recorded hypertension prevalence was relatively stable at 15% throughout the study period. The percentage of patients with a record of hypertension treated to target in the preceding 12 months reduced from a maximum of 71% in March 2020 to a minimum of 47% in February 2021 in patients aged [≤] 79 years, and from 85% in March 2020 to a minimum of 58% in February 2021 in patients aged [≥] 80 years before recovering. Blood pressure screening rates in the preceding 5 years remained stable in older age groups, patients with a record of learning disability, or care home status. Conclusions: There was substantial disruption to hypertension management QOF indicators during the pandemic, which can likely be attributed to a general reduction of blood pressure screening. OpenSAFELY can be used to continuously monitor monthly changes in national quality of care schemes to identify changes in key clinical subgroups early and support prioritisation of recovery from disrupted care caused by COVID-19.

Evaluation of the impact of COVID-19 pandemic on hospital admission related to common infections (preprint)

Background: Antimicrobial resistance (AMR) is a multifaceted global challenge, partly driven by inappropriate antibiotic prescribing. The COVID-19 pandemic impacted antibiotic prescribing for common bacterial infections. This highlights the need to examine risk of hospital admissions related to common infections, excluding COVID-19 infections during the pandemic. Methods: With the approval of NHS England, we accessed electronic health records from The Phoenix Partnership (TPP) through OpenSAFELY platform. We included patients with primary care diagnosis of common infections, including lower respiratory tract infection (LRTI), upper respiratory tract infections (URTI), and lower urinary tract infection (UTI), from January 2019 to August 2022. We excluded patients with a COVID-19 record 90 days before to 30 days after the infection diagnosis. Using Cox proportional-hazard regression models, we predicted risk of infection-related hospital admission in 30 days follow-up period after the diagnosis. Results: We found 12,745,165 infection diagnoses from January 2019 to August 2022. Of them, 80,395 (2.05%) cases were admitted to hospital in the follow-up period. Counts of hospital admission for infections dropped during COVID-19, e.g., LRTI from 3,950 in December 2019 to 520 in April 2020. Comparing those prescribed an antibiotic to those without, reduction in risk of hospital admission were largest with LRTI (adjusted odds ratio (OR) of 0.35; 95% CI, 0.35-0.36) and UTI (adjusted OR 0.45; 95% CI, 0.44-0.46), compared to URTI (adjusted OR 1.04; 95% CI, 1.03-1.06). Conclusion: Large effectiveness of antibiotics in preventing complications related to LRTI and UTI can support better targeting of antibiotics to patients with higher complication risks.

OpenSAFELY: The impact of COVID-19 on azathioprine, leflunomide, and methotrexate monitoring, and factors associated with change in monitoring rate. (preprint)

Background: The COVID-19 pandemic created unprecedented pressure on healthcare services. This study aimed to investigate if disease-modifying anti-rheumatic drug (DMARD) safety monitoring was affected during the COVID-19 pandemic. Methods: A population-based cohort study was conducted with the approval of NHS England, using the OpenSAFELY platform to access electronic health record data from 24.2 million patients registered at general practices using TPP's SystmOne software. Patients were included for further analysis if prescribed azathioprine, leflunomide, or methotrexate between November 2019 and July 2022. Outcomes were assessed as monthly trends and variation between various sociodemographic and clinical groups for adherence with standard safety monitoring recommendations. Findings: An acute increase in the rate of missed monitoring occurred across the study population (+12.4 percentage points) when lockdown measures were implemented in March 2020. This increase was more pronounced for some patient groups (70-79 year-olds: +13.7 percentage points; females: +12.8 percentage points), regions (North West: +17.0 percentage points), medications (Leflunomide: +20.7 percentage points), and monitoring tests (Blood Pressure: +24.5 percentage points). Missed monitoring rates decreased substantially for all groups by July 2022. Substantial and consistent differences were observed in overall missed monitoring rates between several groups throughout the study. Interpretation: DMARD monitoring rates temporarily deteriorated during the COVID-19 pandemic. Deterioration coincided with the onset of lockdown measures, with monitoring rates recovering rapidly as lockdown measures were eased. Differences observed in monitoring rates between medications, tests, regions, and patient groups, highlight opportunities to tackle potential inequalities in the provision or uptake of monitoring services. Further research should aim to evaluate the causes of the differences identified between groups. Funding: None. Keywords COVID-19, electronic health records, general practice, primary health care, antirheumatic agents, methotrexate, azathioprine, leflunomide.

Primary Care Post-COVID syndrome Diagnosis and Referral Coding (preprint)

Introduction - Guidelines for diagnosing and managing Post-COVID syndrome have been rapidly developed. Consistency of the application of these guidelines in primary care is unknown. Electronic health records provide an opportunity to review the use of codes relating to Post-COVID syndrome. This paper explores the use of primary care records as a surrogate uptake measure for NICEs rapid guideline managing the long-term effects of COVID-19 by measuring the use of Post-COVID syndrome diagnosis and referral codes in the pathway. Method - With the approval of NHS England we used routine clinical data from the OpenSafely-EMIS/-TPP platforms. Counts of Post-COVID syndrome diagnosis and referral codes were generated from a cohort of all adults, establishing numbers of diagnoses and referrals following diagnosis. The relationship between Post-COVID syndrome diagnosis and referral codes was explored with reference to NICEs rapid guideline. Results - Of over 45 million patients, 69,220 (0.15%) had a Post-COVID syndrome diagnostic code, and 67,741 (0.15%) had a referral code. 78% of referral codes did not have an associated diagnosis code. 79% of diagnosis codes had no subsequent referral code. Only 18,633 (0.04%) had both. There were higher rates of both diagnosis and referral in those who were more deprived, female and some ethnic groups. Discussion - This study demonstrates variation in diagnosis and referral coding rates for Post-COVID syndrome across different patient groups. The results, with limited crossover of referral and diagnostic codes, suggest only one type of code is usually recorded. Recording one code limits the use of routine data for monitoring Post-COVID syndrome diagnosis and management, but suggests several areas for improvement in coding. Post-COVID syndrome coding, particularly diagnosis coding, needs to improve before administrators and researchers can use it to evaluate care pathways.

Trends in weight gain recorded in English primary care before and during the Coronavirus-19 pandemic: an observational cohort study using the OpenSAFELY platform (preprint)

Background We investigated which clinical and sociodemographic characteristics were associated with unhealthy patterns of weight gain amongst adults living in England during the pandemic. Methods With the approval of NHS England we conducted an observational cohort study of Body Mass Index (BMI) changes between March 2015 and March 2022 using the OpenSAFELY-TPP platform. We estimated individual rates of weight gain before and during the pandemic, and identified individuals with rapid weight gain (>0.5kg/m2/year) in each period. We also estimated the change in rate of weight gain between the prepandemic and pandemic period and defined extreme-accelerators as the ten percent of individuals with the greatest increase (>1.84kg/m2/year). We estimated associations with these outcomes using multivariate logistic regression. Findings We extracted data on 17,742,365 adults (50.1% female, 76.1% White British). Median BMI increased from 27.8kg/m2[IQR:24.3 to 32.1] in 2019 (March 2019 to February 2020) to 28.0kg/m2 [24.4 to 32.6] in 2021. Rapid pandemic weight gain (n=3,214,155) was associated with female sex (male vs female: aOR 0.76 [95%CI:0.76 to 0.76]); younger age (50 to 59 years vs 18 to 29 years: aOR 0.60 [0.60 to 0.61]); White British ethnicity (Black Caribbean vs White British: aOR 0.91 [0.89 to 0.94]); deprivation (least-deprived-IMD-quintile vs most-deprived:aOR 0.77 [0.77 to 0.78]); and long-term conditions, of which mental health conditions had the greatest effect (e.g. depression (aOR 1.18[1.17 to 1.18])). Similar characteristics increased risk of extreme acceleration (n=2,768,695). Interpretation We found female sex, younger age, deprivation and mental health conditions increased risk of unhealthy patterns of pandemic weight gain. This highlights the need to incorporate sociodemographic, physical, and mental health characteristics when formulating post-pandemic research, policies, and interventions targeting BMI. Funding NIHR

Insights from Large-Scale Analysis of Long Term and Repeat Antibiotic Prescribing Pre and during the COVID-19 Pandemic Periods (preprint)

COVID-19 pandemic-related pressures on primary care may have driven inappropriate continuation of antibiotic prescriptions. Yet prescribing modality (repeat/non-repeat) has not previously been investigated in a pandemic context. Using the OpenSAFELY-TPP analytics platform, we analysed repeat/non-repeat prescribing frequency in monthly patient cohorts between Jan 2020–2022. In-depth analysis was conducted on Jan 2020 (“pre-pandemic”) and Jan 2021 (“pandemic”) cohorts. Per-patient prescribing and clinical conditions were determined by searching primary care record data using clinical code lists. Repeat prescribing was defined as >=3 prescriptions in a 6 month lookback period. Associations between demographics (e.g. age, sex, geography) and repeat/non-repeat prescribing were explored using unadjusted risk ratios. Antibiotic prescribing declined from May 2020; non-repeat prescribing declined more strongly than repeat prescribing (maximum declines -26% vs -11%, respectively). In the pandemic cohort, older patients were at higher risk of prescribing (especially repeat prescribing). The most common clinical conditions for repeat prescribing were COPD comorbidity and urinary tract infection. Comorbidities were more common among repeat vs non-repeat prescribed patients. In the pandemic cohort, vs pre-pandemic, repeat and non-repeat prescribing for comorbidities generally declined less compared with shorter-term conditions (infections, including COPD exacerbation/lower respiratory tract infection). Our findings inform ongoing development of stewardship interventions in England..

Primary care coding activity related to the use of online consultation systems or remote consulting: an analysis of 53 million peoples' health records using OpenSAFELY (preprint)

Objective: We aimed to explore general practice coding activity associated with the use of online consultation systems in terms of trends, COVID-19 effect, variation and quality. The pandemic accelerated work by the NHS in England to enable and stimulate use of online consultation systems across all practices, for improved access to primary care. Methods: With the approval of NHS England, OpenSAFELY-TPP and OpenSAFELY-EMIS were used to query and analyse in situ records of electronic health record systems of over 53 million patients in over 6,400 practices, mainly in 2019-2020. SNOMED CT codes relevant to online consultation systems and written online consultations were identified. Coded events were described by volumes, practice coverage, trends pre- and post-COVID-19 and inter-practice and sociodemographic variation. Results: 3,550,762 relevant coding events were found in TPP practices, with code eConsultation detected in 84% of practices. Coding activity related to digital forms of interaction increased rapidly from March 2020 at the onset of the COVID-19 pandemic, though we found large variation in coding instance rates among practices in England. Code instances were more commonly found among females, those aged 18-40, those least deprived or white. eConsultation coded activity was more commonly found recorded among patients with a history of asthma or depression. Conclusions: We successfully queried general practice coding activity relevant to the use of online consultation systems, showing increased adoption as well as key areas of variation during the COVID-19 pandemic. The work can be expanded to support monitoring of coding quality and underlying activity. In future, large-scale impact evaluation studies can be implemented within the platform, namely looking at resource utilisation and patient outcomes.

Comparative effectiveness of Paxlovid versus sotrovimab and molnupiravir for preventing severe COVID-19 outcomes in non-hospitalised patients: observational cohort study using the OpenSAFELY platform (preprint)

Objective: To compare the effectiveness of Paxlovid vs. sotrovimab and molnupiravir in preventing severe COVID-19 outcomes in non-hospitalised high-risk COVID-19 adult patients. Design: With the approval of NHS England, we conducted a real-world cohort study using the OpenSAFELY-TPP platform. Setting: Patient-level electronic health record data were obtained from 24 million people registered with a general practice in England that uses TPP software. The primary care data were securely linked with data on COVID-19 infection and therapeutics, hospital admission, and death within the OpenSAFELY-TPP platform, covering a period where both Paxlovid and sotrovimab were first-line treatment options in community settings. Participants: Non-hospitalised adult COVID-19 patients at high risk of severe outcomes treated with Paxlovid, sotrovimab or molnupiravir between February 11, 2022 and October 1, 2022. Interventions: Paxlovid, sotrovimab or molnupiravir administered in the community by COVID-19 Medicine Delivery Units. Main outcome measure: COVID-19 related hospitalisation or COVID-19 related death within 28 days after treatment initiation. Results: A total of 7683 eligible patients treated with Paxlovid (n=4836) and sotrovimab (n=2847) were included in the main analysis. The mean age was 54.3 (SD=14.9) years; 64% were female, 93% White and 93% had three or more COVID-19 vaccinations. Within 28 days after treatment initiation, 52 (0.68%) COVID-19 related hospitalisations/deaths were observed (33 (0.68%) treated with Paxlovid and 19 (0.67%) with sotrovimab). Cox proportional hazards model stratified by region showed that after adjusting for demographics, high-risk cohort categories, vaccination status, calendar time, body mass index and other comorbidities, treatment with Paxlovid was associated with a similar risk of outcome event as treatment with sotrovimab (HR=1.14, 95% CI: 0.62 to 2.08; P=0.673). Results from propensity score weighted Cox model also showed comparable risks in these two treatment groups (HR=0.88, 95% CI: 0.45 to 1.71; P=0.700). An exploratory analysis comparing Paxlovid users with 802 molnupiravir users (11 (1.37%) COVID-19 related hospitalisations/deaths) showed some evidence in favour of Paxlovid but with variation in the effect estimates between models (HR ranging from 0.26 to 0.61). Conclusion: 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 Paxlovid and sotrovimab between February and October 2022, when different subvariants of Omicron were dominant.

The impact of the COVID-19 pandemic on Antipsychotic Prescribing in individuals with autism, dementia, learning disability, serious mental illness or living in a care home: A federated analysis of 59 million patients primary care records in situ using OpenSAFELY (preprint)

Background: The COVID-19 pandemic significantly affected health and social care services. We aimed to explore whether this impacted the prescribing rates of antipsychotics within at-risk populations. Methods With the approval of NHS England, we completed a retrospective cohort study, using the OpenSAFELY platform to explore primary care data of 59 million patients. We identified patients in five at-risk groups: autism, dementia, learning disability, serious mental illness and care home residents. We then calculated the monthly prevalence of antipsychotic prescribing in the population, as well as the incidence of new prescriptions in each month over the study period (Jan 2019-Dec 2021). Results The average monthly rate of antipsychotic prescribing increased in dementia from 82.75 patients prescribed an antipsychotic per 1000 patients (95% CI 82.30-83.19) in Q1 2019 to 90.1 (95% CI 89.68-90.60) in Q4 2021 and from 154.61 (95% CI 153.79-155.43) in Q1 2019 to 166.95 (95% CI 166.23-167.67) in Q4 2021 in care homes . There were notable spikes in the rate of new prescriptions issued to patients with dementia and in care homes. In learning disability and autism groups, the average monthly rate of prescribing per 1000 decreased from 122.97 (95% CI 122.29-123.66) in Q1 2019 to 119.29 (95% CI 118.68-119.91) in Q4 2021, and from 54.91 (95% CI 54.52-55.29) in Q1 2019 to 51.04 (95% CI 50.74-51.35) in Q4 2021 respectively. Conclusions During each of the lockdowns in 2020, we observed a significant spike in antipsychotic prescribing in the dementia and care home groups. We have shown that these peaks are likely due to prescribing of antipsychotics for palliative care purposes and may have been linked to pre-emptive prescribing, when on-site medical visits would have been restricted. Over the study period, we observed gradual increases in antipsychotic use in patients with dementia and in care homes and a decrease in their use in patients with learning disability or autism.