The impact of COVID-19 on antibiotic prescribing in primary care in England: Evaluation and risk prediction of appropriateness of type and repeat prescribing.

BACKGROUND: This study aimed to predict risks of potentially inappropriate antibiotic type and repeat prescribing and assess changes during COVID-19. METHODS: With the approval of NHS England, we used OpenSAFELY platform to access the TPP SystmOne electronic health record (EHR) system and selected patients prescribed antibiotics from 2019 to 2021. Multinomial logistic regression models predicted patient's probability of receiving inappropriate antibiotic type or repeat antibiotic course for each common infection. RESULTS: The population included 9.1 million patients with 29.2 million antibiotic prescriptions. 29.1% of prescriptions were identified as repeat prescribing. Those with same day incident infection coded in the EHR had considerably lower rates of repeat prescribing (18.0%) and 8.6% had potentially inappropriate type. No major changes in the rates of repeat antibiotic prescribing during COVID-19 were found. In the 10 risk prediction models, good levels of calibration and moderate levels of discrimination were found. CONCLUSIONS: Our study found no evidence of changes in level of inappropriate or repeat antibiotic prescribing after the start of COVID-19. Repeat antibiotic prescribing was frequent and varied according to regional and patient characteristics. There is a need for treatment guidelines to be developed around antibiotic failure and clinicians provided with individualised patient information.

Impact of COVID-19 on broad-spectrum antibiotic prescribing for common infections in primary care in England: a time-series analyses using OpenSAFELY and effects of predictors including deprivation.

Background: The COVID-19 pandemic impacted the healthcare systems, adding extra pressure to reduce antimicrobial resistance. Therefore, we aimed to evaluate changes in antibiotic prescription patterns after COVID-19 started. Methods: With the approval of NHS England, we used the OpenSAFELY platform to access the TPP SystmOne electronic health record (EHR) system in primary care and selected patients prescribed antibiotics from 2019 to 2021. To evaluate the impact of COVID-19 on broad-spectrum antibiotic prescribing, we evaluated prescribing rates and its predictors and used interrupted time series analysis by fitting binomial logistic regression models. Findings: Over 32 million antibiotic prescriptions were extracted over the study period; 8.7% were broad-spectrum. The study showed increases in broad-spectrum antibiotic prescribing (odds ratio [OR] 1.37; 95% confidence interval [CI] 1.36-1.38) as an immediate impact of the pandemic, followed by a gradual recovery with a 1.1-1.2% decrease in odds of broad-spectrum prescription per month. The same pattern was found within subgroups defined by age, sex, region, ethnicity, and socioeconomic deprivation quintiles. More deprived patients were more likely to receive broad-spectrum antibiotics, which differences remained stable over time. The most significant increase in broad-spectrum prescribing was observed for lower respiratory tract infection (OR 2.33; 95% CI 2.1-2.50) and otitis media (OR 1.96; 95% CI 1.80-2.13). Interpretation: An immediate reduction in antibiotic prescribing and an increase in the proportion of broad-spectrum antibiotic prescribing in primary care was observed. The trends recovered to pre-pandemic levels, but the consequence of the COVID-19 pandemic on AMR needs further investigation. Funding: This work was supported by Health Data Research UK and by National Institute for Health Research.

Excess years of life lost to COVID-19 and other causes of death by sex, neighbourhood deprivation, and region in England and Wales during 2020: A registry-based study.

BACKGROUND: Deaths in the first year of the Coronavirus Disease 2019 (COVID-19) pandemic in England and Wales were unevenly distributed socioeconomically and geographically. However, the full scale of inequalities may have been underestimated to date, as most measures of excess mortality do not adequately account for varying age profiles of deaths between social groups. We measured years of life lost (YLL) attributable to the pandemic, directly or indirectly, comparing mortality across geographic and socioeconomic groups. METHODS AND FINDINGS: We used national mortality registers in England and Wales, from 27 December 2014 until 25 December 2020, covering 3,265,937 deaths. YLLs (main outcome) were calculated using 2019 single year sex-specific life tables for England and Wales. Interrupted time-series analyses, with panel time-series models, were used to estimate expected YLL by sex, geographical region, and deprivation quintile between 7 March 2020 and 25 December 2020 by cause: direct deaths (COVID-19 and other respiratory diseases), cardiovascular disease and diabetes, cancer, and other indirect deaths (all other causes). Excess YLL during the pandemic period were calculated by subtracting observed from expected values. Additional analyses focused on excess deaths for region and deprivation strata, by age-group. Between 7 March 2020 and 25 December 2020, there were an estimated 763,550 (95% CI: 696,826 to 830,273) excess YLL in England and Wales, equivalent to a 15% (95% CI: 14 to 16) increase in YLL compared to the equivalent time period in 2019. There was a strong deprivation gradient in all-cause excess YLL, with rates per 100,000 population ranging from 916 (95% CI: 820 to 1,012) for the least deprived quintile to 1,645 (95% CI: 1,472 to 1,819) for the most deprived. The differences in excess YLL between deprivation quintiles were greatest in younger age groups; for all-cause deaths, a mean of 9.1 years per death (95% CI: 8.2 to 10.0) were lost in the least deprived quintile, compared to 10.8 (95% CI: 10.0 to 11.6) in the most deprived; for COVID-19 and other respiratory deaths, a mean of 8.9 years per death (95% CI: 8.7 to 9.1) were lost in the least deprived quintile, compared to 11.2 (95% CI: 11.0 to 11.5) in the most deprived. For all-cause mortality, estimated deaths in the most deprived compared to the most affluent areas were much higher in younger age groups, but similar for those aged 85 or over. There was marked variability in both all-cause and direct excess YLL by region, with the highest rates in the North West. Limitations include the quasi-experimental nature of the research design and the requirement for accurate and timely recording. CONCLUSIONS: In this study, we observed strong socioeconomic and geographical health inequalities in YLL, during the first calendar year of the COVID-19 pandemic. These were in line with long-standing existing inequalities in England and Wales, with the most deprived areas reporting the largest numbers in potential YLL.

Herpes zoster related hospitalization after inactivated (CoronaVac) and mRNA (BNT162b2) SARS-CoV-2 vaccination: A self-controlled case series and nested case-control study.

BACKGROUND: Stimulation of immunity by vaccination may elicit adverse events. There is currently inconclusive evidence on the relationship between herpes zoster related hospitalization and COVID-19 vaccination. This study aimed to evaluate the effect of inactivated virus (CoronaVac, Sinovac) and mRNA (BNT162b2, BioNTech/Fosun Pharma) COVID-19 vaccine on the risk of herpes zoster related hospitalization. METHODS: Self-controlled case series (SCCS) analysis was conducted using the data from the electronic health records in Hospital Authority and COVID-19 vaccination records in the Department of Health in Hong Kong. We conducted the SCCS analysis including patients with a first primary diagnosis of herpes zoster in the hospital inpatient setting between February 23 and July 31, 2021. A confirmatory analysis by nested case-control method was also conducted. Each herpes zoster case was randomly matched with ten controls according to sex, age, Charlson comorbidity index, and date of hospital admission. Conditional Poisson regression and logistic regression models were used to assess the potential excess rates of herpes zoster after vaccination. FINDINGS: From February 23 to July 31, 2021, a total of 16 and 27 patients were identified with a first primary hospital diagnosis of herpes zoster within 28 days after CoronaVac and BNT162b2 vaccinations. The incidence of herpes zoster was 7.9 (95% Confidence interval [CI]: 5.2-11.5) for CoronaVac and 7.1 (95% CI: 4.1-11.5) for BNT162b2 per 1,000,000 doses administered. In SCCS analysis, CoronaVac vaccination was associated with significantly higher risk of herpes zoster within 14 days after first dose (adjusted incidence rate ratio [aIRR]=2.67, 95% CI: 1.08-6.59) but not in other periods afterwards compared to the baseline period. Regarding BNT162b2 vaccination, a significantly increased risk of herpes zoster was observed after first dose up to 14 days after second dose (0-13 days after first dose: aIRR=5.23, 95% CI: 1.61-17.03; 14-27 days after first dose: aIRR=5.82, 95% CI: 1.62-20.91; 0-13 days after second dose: aIRR=5.14, 95% CI: 1.29-20.47). Using these relative rates, we estimated that there has been an excess of approximately 5 and 7 cases of hospitalization as a result of herpes zoster after every 1,000,000 doses of CoronaVac and BNT162b2 vaccination, respectively. The findings in the nested case control analysis showed similar results. INTERPRETATION: We identified an increased risk of herpes zoster related hospitalization after CoronaVac and BNT162b2 vaccinations. However, the absolute risks of such adverse event after CoronaVac and BNT162b2 vaccinations were very low. In locations where COVID-19 is prevalent, the protective effects on COVID-19 from vaccinations will greatly outweigh the potential side effects of vaccination. FUNDING: The project was funded by Research Grant from the Food and Health Bureau, The Government of the Hong Kong Special Administrative Region (Ref. No.COVID19F01). FTTL (Francisco Tsz Tsun Lai) and ICKW (Ian Chi Kei Wong)'s posts were partly funded by D24H; hence this work was partly supported by AIR@InnoHK administered by Innovation and Technology Commission.

Consultation patterns and frequent attenders in UK primary care from 2000 to 2019: a retrospective cohort analysis of consultation events across 845 general practices.

OBJECTIVE: To describe the distribution of consultations at the practice level and examine whether increases are uniform or driven by people who consult more frequently. DESIGN: Retrospective cohort study. SETTING: UK general practice data from the Clinical Practice Research Datalink (CPRD) GOLD database. PARTICIPANTS: 1 699 709 314 consultation events from 12 330 545 patients, in 845 general practices (1 April 2000 to 31 March 2019). METHODS: Consultation information was aggregated by financial year into: all consultations/all staff; all consultations/general practitioners (GPs); face-to-face consultations/all staff; face-to-face consultations/GPs. Patients with a number of consultations above the 90th centile, within each year, were classified as frequent attenders. Negative binomial regressions examined the association between available practice characteristics and consultation distribution. RESULTS: Among frequent attenders, all consultations by GPs increased from a median (25th and 75th centile) of 13 (10 and 16) to 21 (18 and 25) and all consultations by all staff increased from 27 (23-30) to 60 (51-69) over the study period. Approximately four out of ten consultations of any type concerned frequent attenders and the proportion of consultations attributed to them increased over time, particularly for face-to-face consultations with GPs, from a median of 38.0% (35.9%-40.3%) in 2000-2001 to 43.0% (40.6%-46.4%) in 2018-2019. Regression analyses indicated decreasing trends over time for face-to-face consultations and increasing trends for all consultation types, for both GPs and all staff. Frequent attenders consulted approximately five times more than the rest of the practice population, on average, with adjusted incidence rate ratios ranging between 4.992 (95% CI 4.917 to 5.068) for face-to-face consultations with all staff and 5.603 (95% CI 5.560 to 5.647) for all consultations with GPs. CONCLUSIONS: Frequent attenders progressively contributed to increased workload in general practices across the UK from 2000 to 2019. Important knowledge gaps remain in terms of the demographic, social and health characteristics of frequent attenders and how UK general practices can be prepared to meet the needs of these patients.

Association of SARS-CoV-2 Infection With Psychological Distress, Psychotropic Prescribing, Fatigue, and Sleep Problems Among UK Primary Care Patients.

Importance: Infection with SARS-CoV-2 is associated with fatigue and sleep problems long after the acute phase of COVID-19. In addition, there are concerns of SARS-CoV-2 infection causing psychiatric illness; however, evidence of a direct effect is inconclusive. Objective: To assess risk of risk of incident or repeat psychiatric illness, fatigue, or sleep problems following SARS-CoV-2 infection and to analyze changes according to demographic subgroups. Design, Setting, and Participants: This cohort study assembled matched cohorts using the Clinical Practice Research Datalink Aurum, a UK primary care registry of 11 923 499 individuals aged 16 years or older. Patients were followed-up for up to 10 months, from February 1 to December 9, 2020. Individuals with less than 2 years of historical data or less than 1 week follow-up were excluded. Individuals with positive results on a SARS-CoV-2 test without prior mental illness or with anxiety or depression, psychosis, fatigue, or sleep problems were matched with up to 4 controls based on sex, general practice, and year of birth. Controls were individuals who had negative SARS-CoV-2 test results. Data were analyzed from January to July 2021. Exposure: SARS-CoV-2 infection, determined via polymerase chain reaction testing. Main Outcomes and Measures: Cox proportional hazard models estimated the association between a positive SARS-CoV-2 test result and subsequent psychiatric morbidity (depression, anxiety, psychosis, or self-harm), sleep problems, fatigue, or psychotropic prescribing. Models adjusted for comorbidities, ethnicity, smoking, and body mass index. Results: Of 11 923 105 eligible individuals (6 011 020 [50.4%] women and 5 912 085 [49.6%] men; median [IQR] age, 44 [30-61] years), 232 780 individuals (2.0%) had positive result on a SARS-CoV-2 test. After applying selection criteria, 86 922 individuals were in the matched cohort without prior mental illness, 19 020 individuals had prior anxiety or depression, 1036 individuals had psychosis, 4152 individuals had fatigue, and 4539 individuals had sleep problems. After adjusting for observed confounders, there was an association between positive SARS-CoV-2 test results and psychiatric morbidity (adjusted hazard ratio [aHR], 1.83; 95% CI, 1.66-2.02), fatigue (aHR, 5.98; 95% CI, 5.33-6.71), and sleep problems (aHR, 3.16; 95% CI, 2.64-3.78). However, there was a similar risk of incident psychiatric morbidity for those with a negative SARS-CoV-2 test results (aHR, 1.71; 95% CI, 1.65-1.77) and a larger increase associated with influenza (aHR, 2.98; 95% CI, 1.55-5.75). Conclusions and Relevance: In this cohort study of individuals registered at an English primary care practice during the pandemic, there was consistent evidence that SARS-CoV-2 infection was associated with increased risk of fatigue and sleep problems. However, the results from the negative control analysis suggest that unobserved confounding may be responsible for at least some of the positive association between COVID-19 and psychiatric morbidity.

Temporal trends in primary care-recorded self-harm during and beyond the first year of the COVID-19 pandemic: Time series analysis of electronic healthcare records for 2.8 million patients in the Greater Manchester Care Record.

BACKGROUND: Surveillance of temporal trends in clinically treated self-harm is an important component of suicide prevention in the dynamic context of COVID-19. There is little evidence beyond the initial months following the onset of the pandemic, despite national and regional restrictions persisting to mid-2021. METHODS: Descriptive time series analysis utilizing de-identified, primary care health records of 2.8 million patients from the Greater Manchester Care Record. Frequencies of self-harm episodes between 1st January 2019 and 31st May 2021 were examined, including stratification by sex, age group, ethnicity, and index of multiple deprivation quintile. FINDINGS: There were 33,444 episodes of self-harm by 13,148 individuals recorded during the study period. Frequency ratios of incident and all episodes of self-harm were 0.59 (95% CI 0.51 to 0.69) and 0.69 (CI 0.63 to 0.75) respectively in April 2020 compared to February 2020. Between August 2020 and May 2021 frequency ratios were 0.92 (CI 0.88 to 0.96) for incident episodes and 0.86 (CI 0.84 to 0.88) for all episodes compared to the same months in 2019. Reductions were largest among men and people living in the most deprived neighbourhoods, while an increase in all-episode self-harm was observed for adolescents aged 10-17. INTERPRETATION: Reductions in primary care-recorded self-harm persisted to May 2021, though they were less marked than in April 2020 during the first national lockdown. The observed reductions could represent longer term reluctance to seek help from health services. Our findings have implications for the ability for services to offer recommended care for patients who have harmed themselves.

Impact of COVID-19 restrictions on diabetes health checks and prescribing for people with type 2 diabetes: a UK-wide cohort study involving 618 161 people in primary care.

OBJECTIVE: To compare rates of performing National Institute for Health and Care Excellence-recommended health checks and prescribing in people with type 2 diabetes (T2D), before and after the first COVID-19 peak in March 2020, and to assess whether trends varied by age, sex, ethnicity and deprivation. METHODS: We studied 618 161 people with T2D followed between March and December 2020 from 1744 UK general practices registered with the Clinical Practice Research Datalink. We focused on six health checks: haemoglobin A1c, serum creatinine, cholesterol, urinary albumin excretion, blood pressure and body mass index assessment. Regression models compared observed rates in April 2020 and between March and December 2020 with trend-adjusted expected rates derived from 10-year historical data. RESULTS: In April 2020, in English practices, rates of performing health checks were reduced by 76%-88% when compared with 10-year historical trends, with older people from deprived areas experiencing the greatest reductions. Between May and December 2020, the reduced rates recovered gradually but overall remained 28%-47% lower, with similar findings in other UK nations. Extrapolated to the UK population, there were ~7.4 million fewer care processes undertaken March-December 2020. In England, rates for new medication fell during April with reductions varying from 10% (95% CI: 4% to 16%) for antiplatelet agents to 60% (95% CI: 58% to 62%) for antidiabetic medications. Overall, between March and December 2020, the rate of prescribing new diabetes medications fell by 19% (95% CI: 15% to 22%) and new antihypertensive medication prescribing fell by 22% (95% CI: 18% to 26%), but prescribing of new lipid-lowering or antiplatelet therapy was unchanged. Similar trends were observed across the UK, except for a reduction in new lipid-lowering therapy prescribing in the other UK nations (reduction: 16% (95% CI: 10% to 21%)). Extrapolated to the UK population, between March and December 2020, there were ~31 800 fewer people with T2D prescribed a new type of diabetes medication and ~14 600 fewer prescribed a new type of antihypertensive medication. CONCLUSIONS: Over the coming months, healthcare services will need to manage this backlog of testing and prescribing. We recommend effective communications to ensure patient engagement with diabetes services, monitoring and opportunities for prescribing, and when appropriate use of home monitoring, remote consultations and other innovations in care.

Excess deaths from COVID-19 and other causes by region, neighbourhood deprivation level and place of death during the first 30 weeks of the pandemic in England and Wales: A retrospective registry study.

BACKGROUND: Excess deaths during the COVID-19 pandemic compared with those expected from historical trends have been unequally distributed, both geographically and socioeconomically. Not all excess deaths have been directly related to COVID-19 infection. We investigated geographical and socioeconomic patterns in excess deaths for major groups of underlying causes during the pandemic. METHODS: Weekly mortality data from 27/12/2014 to 2/10/2020 for England and Wales were obtained from the Office of National Statistics. Negative binomial regressions were used to model death counts based on pre-pandemic trends for deaths caused directly by COVID-19 (and other respiratory causes) and those caused indirectly by it (cardiovascular disease or diabetes, cancers, and all other indirect causes) over the first 30 weeks of the pandemic (7/3/2020-2/10/2020). FINDINGS: There were 62,321 (95% CI: 58,849 to 65,793) excess deaths in England and Wales in the first 30 weeks of the pandemic. Of these, 46,221 (95% CI: 45,439 to 47,003) were attributable to respiratory causes, including COVID-19, and 16,100 (95% CI: 13,410 to 18,790) to other causes. Rates of all-cause excess mortality ranged from 78 per 100,000 in the South West of England and in Wales to 130 per 100,000 in the West Midlands; and from 93 per 100,000 in the most affluent fifth of areas to 124 per 100,000 in the most deprived. The most deprived areas had the highest rates of death attributable to COVID-19 and other indirect deaths, but there was no socioeconomic gradient for excess deaths from cardiovascular disease/diabetes and cancer. INTERPRETATION: During the first 30 weeks of the COVID-19 pandemic there was significant geographic and socioeconomic variation in excess deaths for respiratory causes, but not for cardiovascular disease, diabetes and cancer. Pandemic recovery plans, including vaccination programmes, should take account of individual characteristics including health, socioeconomic status and place of residence. FUNDING: None.

Effects of the COVID-19 pandemic on primary care-recorded mental illness and self-harm episodes in the UK: a population-based cohort study.

BACKGROUND: The COVID-19 pandemic has adversely affected population mental health. We aimed to assess temporal trends in primary care-recorded common mental illness, episodes of self-harm, psychotropic medication prescribing, and general practitioner (GP) referrals to mental health services during the COVID-19 emergency in the UK. METHODS: We did a population-based cohort study using primary care electronic health records from general practices registered on the UK Clinical Practice Research Datalink (CPRD). We included patient records from Jan 1, 2010, to Sept 10, 2020, to establish long-term trends and patterns of seasonality, but focused primarily on the period January, 2019-September, 2020. We extracted data on clinical codes entered into patient records to estimate the incidence of depression and anxiety disorders, self-harm, prescriptions for antidepressants and benzodiazepines, and GP referrals to mental health services, and assessed event rates of all psychotropic prescriptions and self-harm. We used mean-dispersion negative binomial regression models to predict expected monthly incidence and overall event rates, which were then compared with observed rates to assess the percentage reduction in incidence and event rates after March, 2020. We also stratified analyses by sex, age group, and practice-level Index of Multiple Deprivation quintiles. FINDINGS: We identified 14 210 507 patients from 1697 UK general practices registered in the CPRD databases. In April, 2020, compared with expected rates, the incidence of primary care-recorded depression had reduced by 43·0% (95% CI 38·3-47·4), anxiety disorders by 47·8% (44·3-51·2), and first antidepressant prescribing by 36·4% (33·9-38·8) in English general practices. Reductions in first diagnoses of depression and anxiety disorders were largest for adults of working age (18-44 and 45-64 years) and for patients registered at practices in more deprived areas. The incidence of self-harm was 37·6% (34·8-40·3%) lower than expected in April, 2020, and the reduction was greatest for women and individuals aged younger than 45 years. By September, 2020, rates of incident depression, anxiety disorder, and self-harm were similar to expected levels. In Northern Ireland, Scotland, and Wales, rates of incident depression and anxiety disorder remained around a third lower than expected to September, 2020. In April, 2020, the rate of referral to mental health services was less than a quarter of the expected rate for the time of year (75·3% reduction [74·0-76·4]). INTERPRETATION: Consequences of the considerable reductions in primary care-recorded mental illness and self-harm could include more patients subsequently presenting with greater severity of mental illness and increasing incidence of non-fatal self-harm and suicide. Addressing the effects of future lockdowns and longer-term impacts of economic instability on mental health should be prioritised. FUNDING: National Institute for Health Research and Medical Research Council.

Diagnosis of physical and mental health conditions in primary care during the COVID-19 pandemic: a retrospective cohort study.

BACKGROUND: To date, research on the indirect impact of the COVID-19 pandemic on the health of the population and the health-care system is scarce. We aimed to investigate the indirect effect of the COVID-19 pandemic on general practice health-care usage, and the subsequent diagnoses of common physical and mental health conditions in a deprived UK population. METHODS: We did a retrospective cohort study using routinely collected primary care data that was recorded in the Salford Integrated Record between Jan 1, 2010, and May 31, 2020. We extracted the weekly number of clinical codes entered into patient records overall, and for six high-level categories: symptoms and observations, diagnoses, prescriptions, operations and procedures, laboratory tests, and other diagnostic procedures. Negative binomial regression models were applied to monthly counts of first diagnoses of common conditions (common mental health problems, cardiovascular and cerebrovascular disease, type 2 diabetes, and cancer), and corresponding first prescriptions of medications indicative of these conditions. We used these models to predict the expected numbers of first diagnoses and first prescriptions between March 1 and May 31, 2020, which were then compared with the observed numbers for the same time period. FINDINGS: Between March 1 and May 31, 2020, 1073 first diagnoses of common mental health problems were reported compared with 2147 expected cases (95% CI 1821 to 2489) based on preceding years, representing a 50·0% reduction (95% CI 41·1 to 56·9). Compared with expected numbers, 456 fewer diagnoses of circulatory system diseases (43·3% reduction, 95% CI 29·6 to 53·5), and 135 fewer type 2 diabetes diagnoses (49·0% reduction, 23·8 to 63·1) were observed. The number of first prescriptions of associated medications was also lower than expected for the same time period. However, the gap between observed and expected cancer diagnoses (31 fewer; 16·0% reduction, -18·1 to 36·6) during this time period was not statistically significant. INTERPRETATION: In this deprived urban population, diagnoses of common conditions decreased substantially between March and May 2020, suggesting a large number of patients have undiagnosed conditions. A rebound in future workload could be imminent as COVID-19 restrictions ease and patients with undiagnosed conditions or delayed diagnosis present to primary and secondary health-care services. Such services should prioritise the diagnosis and treatment of these patients to mitigate potential indirect harms to protect public health. FUNDING: National Institute of Health Research.