Search

Abstract Background We aimed to identify and characterise the longitudinal patterns of multimorbidity associated with stroke. Methods We used an unsupervised patient-oriented clustering approach to analyse primary care electronic health records (EHR) of 30 common long-term conditions (LTC) in patients with stroke aged over 18, registered in 41 general practices in south London between 2005 and 2021. Results Of 849,968 registered patients, 9,847 (1.16%) had a record of stroke and 46.5% were female. The median age at record of stroke was 65.0 year (IQR: 51.5-77.0) and the median number of LTCs in addition to stroke was 3 (IQR: 2-5). We identified eight clusters of multimorbidity with contrasted socio-demographic characteristics (age, gender, and ethnicity) and risk factors. Beside a core of 3 clusters associated with conventional stroke risk-factors, minor clusters exhibited less common combinations of LTCs including mental health conditions, asthma, osteoarthritis and sickle cell anaemia. Importantly, complex profiles combining mental health conditions, infectious diseases and substance dependency emerged. Conclusion This novel longitudinal and patient-oriented perspective on multimorbidity addresses existing gaps in mapping the patterns of stroke-associated multimorbidity not only in terms of LTCs, but also socio-demographic characteristics, and suggests potential for more efficient and patient-oriented healthcare models.

Abstract Background Multiple long-term conditions (MLTCs), living with two or more long-term conditions (LTCs), often termed multimorbidity, has a high and increasing prevalence globally with earlier age of onset in people living in deprived communities. A holistic understanding of the patient’s perspective of the work associated with living with MLTCs is needed. This study aimed to synthesise qualitative evidence describing the experiences of people living with MLTCs (multimorbidity) and to develop a greater understanding of the effect on people’s lives and ways in which living with MLTCs is 'burdensome' for people. Methods Three concepts (multimorbidity, burden and lived experience) were used to develop search terms. A broad qualitative filter was applied. MEDLINE (Ovid), EMBASE (Ovid), PsycINFO (EBSCO), CINAHL (EBSCO) and the Cochrane Library were searched from January 2000-January 2023. We included studies where at least 50% of study participants were living with three or more LTCs and the lived experience of MLTCs was expressed from the patient perspective. Screening and quality assessment (CASP checklist) was undertaken by two independent researchers. Data was synthesised using an inductive approach. PPI (Patient and Public Involvement) input was included throughout. Results Of 30,803 references identified, 46 met the inclusion criteria. 31 studies (67%) did not mention ethnicity or race of participants and socioeconomic factors were inconsistently described. Only two studies involved low- and middle-income countries (LMICs). Eight themes of work were generated: learning and adapting; accumulation and complexity; symptoms; emotions; investigation and monitoring; health service and administration; medication; and finance. The quality of studies was generally high. 41 papers had no PPI involvement reported and none had PPI contributor co-authors. Conclusions The impact of living with MLTCs was experienced as a multifaceted and complex workload involving multiple types of work, many of which are reciprocally linked. Much of this work, and the associated impact on people, may not be apparent to healthcare staff, and current health systems and policies are poorly equipped to meet the needs of this growing population. There was a paucity of data from LMICs and insufficient information on how patient characteristics might influence experiences. Future research should involve patients as partners and focus on these evidence gaps.

Abstract Once the nature and number of patients with Long COVID was more fully understood, UK secondary care developed services to investigate, treat and support these patients. We aimed to identify evidence for demographic health inequalities based on general practitioner (GP) Long COVID referrals to available secondary care services. Despite Long COVID demographics broadly reflecting the multiethnic and socially disadvantaged profile of the study population, we found that secondary care referral was mainly focussed on older age patients and those born in the UK with co-morbid anxiety; although co-morbid diabetes was associated with reduced referrals.

BackgroundThis study estimated to what extent the number of measurements of cardiometabolic risk factors (e.g., blood pressure, cholesterol, glycated haemoglobin) were impacted by the COVID-19 pandemic and whether these have recovered to expected levels.Methods and findingsA cohort of individuals aged ≥18 years in England with records in the primary care-COVID-19 General Practice Extraction Service Data for Pandemic Planning and Research (GDPPR) were identified. Their records of 12 risk factor measurements were extracted between November 2018 and March 2024. Number of measurements per 1,000 individuals were calculated by age group, sex, ethnicity, and area deprivation quintile. The observed number of measurements were compared to a composite expectation band, derived as the union of the 95% confidence intervals of 2 estimates: (1) a projected trend based on data prior to the COVID-19 pandemic; and (2) an assumed stable trend from before pandemic. Point estimates were calculated as the mid-point of the expectation band. A cohort of 49,303,410 individuals aged ≥18 years were included. There was sharp drop in all measurements in March 2020 to February 2022, but overall recovered to the expected levels during March 2022 to February 2023 except for blood pressure, which had prolonged recovery. In March 2023 to March 2024, blood pressure measurements were below expectation by 16% (-19 per 1,000) overall, in people aged 18 to 39 (-23%; -18 per 1,000), 60 to 79 (-17%; -27 per 1,000), and ≥80 (-31%; -57 per 1,000). There was suggestion that recovery in blood pressure measurements was socioeconomically patterned. The second most deprived quintile had the highest deviation (-20%; -23 per 1,000) from expectation compared to least deprived quintile (-13%; -15 per 1,000).ConclusionsThere was a substantial reduction in routine measurements of cardiometabolic risk factors following the COVID-19 pandemic, with variable recovery. The implications for missed diagnoses, worse prognosis, and health inequality are a concern.

Objective To investigate the use of sodium valproate in England and Wales, including during pregnancy, compared with other antiseizure drug treatments, based on national level electronic health records.Design Quantitative analysis of nationwide linked electronic health records.Setting Individual level, population scale data from NHS England's Secure Data Environment, from the British Heart Foundation Data Science Centre's CVD-COVID-UK/COVID-IMPACT Consortium (for England), and the Secure Anonymised Information Linkage Databank (for Wales), 1 January 2019 to 31 December 2023.Participants 1 200 000 individuals dispensed any selected antiseizure drug treatment (ie, sodium valproate, lamotrigine, levetiracetam, carbamazepine, or topiramate); 304 000 women, aged 15-49 years, dispensed any selected antiseizure drug treatment and 28 400 women, aged 15-49 years, dispensed sodium valproate.Main outcome measures Prevalent (current) and incident (new) uses of sodium valproate and other antiseizure drug treatments before and during the covid-19 pandemic (1 January 2019 to 31 December 2023), grouped by age and sex. Pregnancy rates per 1000 women, aged 15-49 years, who used antiseizure drug treatments, and timing and dose of sodium valproate dispensed during pregnancy. Geographical variation in use of sodium valproate and disease indications (epilepsy and bipolar affective disorder). Trends in deaths related to epilepsy for 2015-22.Results Prevalent use of sodium valproate in women of childbearing potential decreased and use of most other antiseizure drug treatments increased between 2019 and 2023. Incident use of sodium valproate per 100 000 women decreased from seven to five in women aged 15-19 years, from 11 to seven in women aged 20-29 years, and from 14 to seven in women aged 30-39 years between 2019 and 2022. Incident use also decreased in men of the same age but remained at much higher levels (from 53 to 43 in men aged 15-19 years, 59 to 47 in men aged 20-29 years, and 57 to 42 in men aged 30-39 years, per 100 000 men). Pregnancy rates decreased from 6.0 to 5.2 per 1000 women of childbearing potential who were dispensed sodium valproate over the same period. The number of pregnant women who used sodium valproate during pregnancy decreased from 140 in 2019 to 85 in 2023. Epilepsy was the most common indication, followed by bipolar affective disorder (751 and 193 per 1000 women of childbearing potential dispensed sodium valproate, respectively, in 2023). No clear evidence was found that deaths related to epilepsy increased in women aged 15-49 during 2015-22, but a slight increase was found in men aged 15-49 during the later period between April 2018 and December 2022.Conclusions Based on comprehensive national records, changes in the dispensing of antiseizure drug treatments in response to regulatory actions were tracked. Rates for use of sodium valproate by women, including during pregnancy, decreased before and continued to slowly decrease during the covid-19 pandemic. Incident use was also reduced in men but remained at much higher levels than in women. This approach, linking national dispensing data to health records at the individual level, could help monitor changes to medicines affected by regulatory changes, including in specific population groups, such as pregnant individuals, and their potential effect on health outcomes.

Abstract Background Estimates of chronic pain prevalence using coded primary care data are likely to be substantially lower than estimates derived from community surveys. Most primary care studies have estimated chronic pain prevalence using data searches confined to analgesic medication prescriptions. Increasingly, following recent NICE guideline recommendations, patients and doctors opt for non-drug treatment of chronic pain thus excluding these patients from prevalence estimates based on medication codes. We aimed to develop and test an algorithm combining medication codes with selected diagnostic codes to estimate chronic pain prevalence using coded primary care data. Methods Following a scoping review 4 criteria were developed to identify cohorts of people with chronic pain. These were (1) people with one of 12 (‘tier 1’) conditions that almost always results in the individual having chronic pain (2) people with one of 20 (‘tier 2’) conditions included when there are also 3 or more prescription-only analgesics issued in the last 12 months (3) chronic neuropathic pain, or (4) 4 or more prescription-only analgesics issued in the last 12 months. These were translated into 8 logic rules which included 1,932 SNOMED CT codes. Results The algorithm was run on primary care data from 41 GP Practices in Lambeth. The total population consisted of 386,238 GP registered adults ≥ 18 years as of the 31st March 2021. 64,135 (16.6%) were identified as people with chronic pain. This definition demonstrated notably high rates in Black ethnicity females, and higher rates in the most deprived, and older population. Conclusions Estimates of chronic pain prevalence using structured healthcare data have previously shown lower prevalence estimates for chronic pain than reported in community surveys. This has limited the ability of researchers and clinicians to fully understand and address the complex multifactorial nature of chronic pain. Our study demonstrates that it may be possible to establish more representative prevalence estimates using structured data than previously possible. Use of logic rules offers the potential to move systematic identification and population-based management of chronic pain into mainstream clinical practice at scale and support improved management of symptom burden for people experiencing chronic pain.

Objective The objective of this study is to determine demographic and diagnostic distributions of physical pain recorded in clinical notes of a mental health electronic health records database by using natural language processing and examine the overlap in recorded physical pain between primary and secondary care.Design, setting and participants The data were extracted from an anonymised version of the electronic health records of a large secondary mental healthcare provider serving a catchment of 1.3 million residents in south London. These included patients under active referral, aged 18+ at the index date of 1 July 2018 and having at least one clinical document (≥30 characters) between 1 July 2017 and 1 July 2019. This cohort was compared with linked primary care records from one of the four local government areas.Outcome The primary outcome of interest was the presence of recorded physical pain within the clinical notes of the patients, not including psychological or metaphorical pain.Results A total of 27 211 patients were retrieved. Of these, 52% (14,202) had narrative text containing relevant mentions of physical pain. Older patients (OR 1.17, 95% CI 1.15 to 1.19), females (OR 1.42, 95% CI 1.35 to 1.49), Asians (OR 1.30, 95% CI 1.16 to 1.45) or black (OR 1.49, 95% CI 1.40 to 1.59) ethnicities, living in deprived neighbourhoods (OR 1.64, 95% CI 1.55 to 1.73) showed higher odds of recorded pain. Patients with severe mental illnesses were found to be less likely to report pain (OR 0.43, 95% CI 0.41 to 0.46, p

BackgroundMinoritised populations in the United Kingdom frequently identify in multiple ethnic groupings and therefore little is known of their health needs. There were 136,062 Latin American people recorded in the 2021 UK Census across six different ethnic groups.AimCharacterise the incidence of long-term conditions (LTCs) and multiple LTCs (mLTCs) amongst the Latin American community of London. Compare the incidence of LTCs in the Latin American population to other ethnic groups.Design and settingRetrospective cohort study using pseudonymised primary care data from 890,922 individuals in an urban, superdiverse area of London from 2005-2022.MethodLatin American individuals were identified using country of birth, language and ethnicity codes, and validated against Census findings. Multivariable competing risks regression models estimated the effect of being Latin American, compared to the White British ethnic group, on incidence of 32 LTCs and risk factors relevant to urban populations.Results28,617 Latin American people were identified in this cohort, 3.2% of total. In multivariable analysis, compared to the White British ethnic group, being Latin American was associated with twice the rate of HIV/AIDS (hazard ratio (HR) 2.00; 95% confidence interval (CI) 1.65-2.43), 60% increased rate of diabetes (HR 1.61; 95%CI 1.47-1.77) and almost twice the rate of systemic lupus erythematosus and rheumatoid arthritis (HRs 2.28; 95% CI 1.18-4.38 and 1.69; 95% CI 1.32-2.17 respectively).ConclusionUsing commonly-recorded primary care codes accurately and reliably identifies markedly higher risks of HIV/AIDS, diabetes and joint disease among London's Latin American population. These data can be used to target inclusive and equitable health interventions.

Abstract Background This descriptive study assessed the completeness, agreement, and representativeness of ethnicity recording in the United Kingdom (UK) Clinical Practice Research Datalink (CPRD) primary care databases alone and, for those patients registered with a GP in England, when linked to secondary care data from Hospital Episode Statistics (HES). Methods Ethnicity records were assessed for all patients in the May 2021 builds of the CPRD GOLD and CPRD Aurum databases for all UK patients. In analyses of the UK, English data was from combined CPRD-HES, whereas data from Northern Ireland, Scotland, and Wales drew from CPRD only. The agreement of ethnicity records per patient was assessed within each dataset (CPRD GOLD, CPRD Aurum, and HES datasets) and between datasets at the highest level ethnicity categorisation (‘Asian’, ‘black’, ‘mixed’, ‘white’, ‘other’). Representativeness was assessed by comparing the ethnic distributions at the highest-level categorisation of CPRD-HES to those from the Census 2011 across the UK’s devolved administrations. Additionally, CPRD-HES was compared to the experimental ethnic distributions for England and Wales from the Office for National Statistics in 2019 (ONS2019) and the English ethnic distribution from May 2021 from NHS Digital’s General Practice Extraction Service Data for Pandemic Planning and Research with HES data linkage (GDPPR-HES). Results In CPRD-HES, 81.7% of currently registered patients in the UK had ethnicity recorded in primary care. For patients with multiple ethnicity records, mismatched ethnicity within individual primary and secondary care datasets was

Abstract Background The COVID-19 pandemic caused rapid changes in primary care delivery in the UK, with concerns that certain groups of the population may have faced increased barriers to access. This study assesses the impact of the response to the COVID-19 pandemic on primary care consultations for individuals with multimorbidity and identifies ethnic inequalities. Methods A longitudinal study based on monthly data from primary care health records of 460,084 patients aged ≥18 years from 41 GP practices in South London, from February 2018 to March 2021. Descriptive analysis and interrupted time series (ITS) models were used to analyse the effect of the pandemic on primary care consultations for people with multimorbidity and to identify if the effect varied by ethnic groups and consultation type. Results Individuals with multimorbidity experienced a smaller initial fall in trend at the start of the pandemic. Their primary care consultation rates remained stable (879 (95% CI 869–890) per 1000 patients in February to 882 (870–894) March 2020), compared with a 7% decline among people without multimorbidity (223 consultations (95% CI 221–226) to 208 (205–210)). The gap in consultations between the two groups reduced after July 2020. The effect among individuals with multimorbidity varied by ethnic group. Ethnic minority groups experienced a slightly larger fall at the start of the pandemic. Individuals of Black, Asian, and Other ethnic backgrounds also switched from face-to-face to telephone at a higher rate than other ethnic groups. The largest fall in face-to-face consultations was observed among people from Asian backgrounds (their consultation rates declined from 676 (659–693) in February to 348 (338–359) in April 2020), which may have disproportionately affected their quality of care. Conclusions The COVID-19 pandemic significantly affected primary care utilisation in patients with multimorbidity. While there is evidence of a successful needs-based prioritisation of multimorbidity patients within primary care at the start of the pandemic, inequalities among ethnic minority groups were found. Strengthening disease management for these groups may be necessary to control widening inequalities in future health outcomes.

Background Most people living with multiple long-term condition multimorbidity (MLTC-M) are under 65 (defined as ‘early onset’). Earlier and greater accrual of long-term conditions (LTCs) may be influenced by the timing and nature of exposure to key risk factors, wider determinants or other LTCs at different life stages. We have established a research collaboration titled ‘MELD-B’ to understand how wider determinants, sentinel conditions (the first LTC in the lifecourse) and LTC accrual sequence affect risk of early-onset, burdensome MLTC-M, and to inform prevention interventions. Aim Our aim is to identify critical periods in the lifecourse for prevention of early-onset, burdensome MLTC-M, identified through the analysis of birth cohorts and electronic health records, including artificial intelligence (AI)-enhanced analyses. Design We will develop deeper understanding of ‘burdensomeness’ and ‘complexity’ through a qualitative evidence synthesis and a consensus study. Using safe data environments for analyses across large, representative routine healthcare datasets and birth cohorts, we will apply AI methods to identify early-onset, burdensome MLTC-M clusters and sentinel conditions, develop semi-supervised learning to match individuals across datasets, identify determinants of burdensome clusters, and model trajectories of LTC and burden accrual. We will characterise early-life (under 18 years) risk factors for early-onset, burdensome MLTC-M and sentinel conditions. Finally, using AI and causal inference modelling, we will model potential ‘preventable moments’, defined as time periods in the life course where there is an opportunity for intervention on risk factors and early determinants to prevent the development of MLTC-M. Patient and public involvement is integrated throughout.

Objective Social, biological and environmental factors in early-life, defined as the period from preconception until age 18, play a role in shaping the risk of multiple long-term condition multimorbidity. However, there is a need to conceptualise these early-life factors, how they relate to each other, and provide conceptual framing for future research on aetiology and modelling prevention scenarios of multimorbidity. We develop a conceptual framework to characterise the population-level domains of early-life determinants of future multimorbidity. Method This work was conducted as part of the Multidisciplinary Ecosystem to study Lifecourse Determinants and Prevention of Early-onset Burdensome Multimorbidity (MELD-B) study. The conceptualisation of multimorbidity lifecourse determinant domains was shaped by a review of existing research evidence and policy, and co-produced with public involvement via two workshops. Results Early-life risk factors incorporate personal, social, economic, behavioural and environmental factors, and the key domains discussed in research evidence, policy, and with public contributors included adverse childhood experiences, socioeconomics, the social and physical environment, and education. Policy recommendations more often focused on individual-level factors as opposed to the wider determinants of health discussed within the research evidence. Some domains highlighted through our co-production process with public contributors, such as religion and spirituality, health screening and check-ups, and diet, were not adequately considered within the research evidence or policy. Conclusions This co-produced conceptualisation can inform research directions using primary and secondary data to investigate the early-life characteristics of population groups at risk of future multimorbidity, as well as policy directions to target public health prevention scenarios of early-onset multimorbidity.

Objectives To develop and probe the first computerised decision-support tool to provide antidepressant treatment guidance to general practitioners (GPs) in UK primary care.Design A parallel group, cluster-randomised controlled feasibility trial, where individual participants were blind to treatment allocation.Setting South London NHS GP practices.Participants Ten practices and eighteen patients with treatment-resistant current major depressive disorder.Interventions Practices were randomised to two treatment arms: (a) treatment-as-usual, (b) computerised decision support tool.Results Ten GP practices participated in the trial, which was within our target range (8–20). However, practice and patient recruitment were slower than anticipated and only 18 of 86 intended patients were recruited. This was due to fewer than expected patients being eligible for the study, as well as disruption resulting from the COVID-19 pandemic. Only one patient was lost to follow-up. There were no serious or medically important adverse events during the trial. GPs in the decision tool arm indicated moderate support for the tool. A minority of patients fully engaged with the mobile app-based tracking of symptoms, medication adherence and side effects.Conclusions Overall, feasibility was not shown in the current study and the following modifications would be needed to attempt to overcome the limitations found: (a) inclusion of patients who have only tried one Selective Serotonin Reuptake Inhibitor, rather than two, to improve recruitment and pragmatic relevance of the study; (b) approaching community pharmacists to implement tool recommendations rather than GPs; (c) further funding to directly interface between the decision support tool and self-reported symptom app; (d) increasing the geographic reach by not requiring detailed diagnostic assessments and replacing this with supported remote self-report.Trial registration number NCT03628027.

Obesity is one of the major contributors to the excess mortality seen in people with severe mental illness (SMI) and in low- and middle-income countries people with SMI may be at an even greater risk. In this study, we aimed to determine the prevalence of obesity and overweight in people with SMI and investigate the association of obesity and overweight with sociodemographic variables, other physical comorbidities, and health-risk behaviours. This was a multi-country cross-sectional survey study where data were collected from 3989 adults with SMI from three specialist mental health institutions in Bangladesh, India, and Pakistan. The prevalence of overweight and obesity was estimated using Asian BMI thresholds. Multinomial regression models were then used to explore associations between overweight and obesity with various potential determinants. There was a high prevalence of overweight (17·3 %) and obesity (46·2 %). The relative risk of having obesity (compared to normal weight) was double in women (RRR = 2·04) compared with men. Participants who met the WHO recommendations for fruit and vegetable intake had 2·53 (95 % CI: 1·65–3·88) times greater risk of having obesity compared to those not meeting them. Also, the relative risk of having obesity in people with hypertension is 69 % higher than in people without hypertension (RRR = 1·69). In conclusion, obesity is highly prevalent in SMI and associated with chronic disease. The complex relationship between diet and risk of obesity was also highlighted. People with SMI and obesity could benefit from screening for non-communicable diseases, better nutritional education, and context-appropriate lifestyle interventions.

BackgroundLong-term exposure to air pollution concentrations is known to be adversely associated with a broad range of single non-communicable diseases, but its role in multimorbidity has not been investigated in the UK. We aimed to assess associations between long-term air pollution exposure and multimorbidity status, severity, and patterns using the UK Biobank cohort.MethodsMultimorbidity status was calculated based on 41 physical and mental conditions. We assessed cross-sectional associations between annual modeled particulate matter (PM)2.5, PMcoarse, PM10, and nitrogen dioxide (NO2) concentrations (μg/m3–modeled to residential address) and multimorbidity status at the baseline assessment (2006–2010) in 364,144 people (mean age: 52.2 ± 8.1 years, 52.6% female). Air pollutants were categorized into quartiles to assess dose-response associations. Among those with multimorbidity (≥2 conditions; n = 156,395) we assessed associations between air pollutant exposure levels and multimorbidity severity and multimorbidity patterns, which were identified using exploratory factor analysis. Associations were explored using generalized linear models adjusted for sociodemographic, behavioral, and environmental indicators.ResultsHigher exposures to PM2.5, and NO2 were associated with multimorbidity status in a dose-dependent manner. These associations were strongest when we compared the highest air pollution quartile (quartile 4: Q4) with the lowest quartile (Q1) [PM2.5: adjusted odds ratio (adjOR) = 1.21 (95% CI = 1.18, 1.24); NO2: adjOR = 1.19 (95 % CI = 1.16, 1.23)]. We also observed dose-response associations between air pollutant exposures and multimorbidity severity scores. We identified 11 multimorbidity patterns. Air pollution was associated with several multimorbidity patterns with strongest associations (Q4 vs. Q1) observed for neurological (stroke, epilepsy, alcohol/substance dependency) [PM2.5: adjOR = 1.31 (95% CI = 1.14, 1.51); NO2: adjOR = 1.33 (95% CI = 1.11, 1.60)] and respiratory patterns (COPD, asthma) [PM2.5: adjOR = 1.24 (95% CI = 1.16, 1.33); NO2: adjOR = 1.26 (95% CI = 1.15, 1.38)].ConclusionsThis cross-sectional study provides evidence that exposure to air pollution might be associated with having multimorbid, multi-organ conditions. Longitudinal studies are needed to further explore these associations.

Abstract Background Defining multimorbidity has proved elusive in spite of attempts to standardise definitions. For national studies, a broad definition is required to capture national diversity. For locally based studies, the definition may need to reflect demographic and morbidity patterns. We aimed to define multimorbidity for an inner city, multi-ethnic, deprived, young age community typical of many large cities. Methods We used a scoping literature review to identify the international literature, standards and guidelines on Long Term Condition (LTC) definitions for inclusion in our multimorbidity definition. Consensus was categorised into high, medium or low consensus, depending on the number of literature sources citing each LTC. Findings were presented to a workshop consisting of local health service stakeholders who were asked to select LTCs for inclusion in a second stage review. In the second stage, each LTC was tested against seven evaluation domains: prevalence, impact, preventability, treatment burden, progression to multiple LTCs, impact on younger people, data quality. These domains were used to create 12 target criteria. LTC rankings according to consensus group and target criteria scores were presented to a second workshop for a final decision about LTC inclusion. Results The literature review identified 18 literature sources citing 86 LTCs: 11 were excluded because they were LTC clusters. The remainder were allocated into consensus groupings: 13 LTCs were ‘high consensus’ (cited by ≥ 11 sources); 15 were ‘medium consensus’ (cited by 5–10 sources); 47 were ‘low consensus’ (cited by

Abstract Background Although the associations of outdoor air pollution exposure with mortality and hospital admissions are well established, few previous studies have reported on primary care clinical and prescribing data. We assessed the associations of short and long-term pollutant exposures with General Practitioner respiratory consultations and inhaler prescriptions. Methods Daily primary care data, for 2009–2013, were obtained from Lambeth DataNet (LDN), an anonymised dataset containing coded data from all patients (1.2 million) registered at general practices in Lambeth, an inner-city south London borough. Counts of respiratory consultations and inhaler prescriptions by day and Lower Super Output Area (LSOA) of residence were constructed. We developed models for predicting daily PM2.5, PM10, NO2 and O3 per LSOA. We used spatio-temporal mixed effects zero inflated negative binomial models to investigate the simultaneous short- and long-term effects of exposure to pollutants on the number of events. Results The mean concentrations of NO2, PM10, PM2.5 and O3 over the study period were 50.7, 21.2, 15.6, and 49.9 μg/m3 respectively, with all pollutants except NO2 having much larger temporal rather than spatial variability. Following short-term exposure increases to PM10, NO2 and PM2.5 the number of consultations and inhaler prescriptions were found to increase, especially for PM10 exposure in children which was associated with increases in daily respiratory consultations of 3.4% and inhaler prescriptions of 0.8%, per PM10 interquartile range (IQR) increase. Associations further increased after adjustment for weekly average exposures, rising to 6.1 and 1.2%, respectively, for weekly average PM10 exposure. In contrast, a short-term increase in O3 exposure was associated with decreased number of respiratory consultations. No association was found between long-term exposures to PM10, PM2.5 and NO2 and number of respiratory consultations. Long-term exposure to NO2 was associated with an increase (8%) in preventer inhaler prescriptions only. Conclusions We found increases in the daily number of GP respiratory consultations and inhaler prescriptions following short-term increases in exposure to NO2, PM10 and PM2.5. These associations are more pronounced in children and persist for at least a week. The association with long term exposure to NO2 and preventer inhaler prescriptions indicates likely increased chronic respiratory morbidity.

Summary: Background: Uptake of health checks among women has not been examined in relation to patient and General Practitioner (GP) practice level factors. We investigated patient and practice level factors associated with differential uptake of health checks. Methods: Primary care records from 44 practices in Lambeth for women aged 40-74 years old (N = 62,967) from 2000-2018 were analysed using multi-level logistic regression models. An odds ratio (OR) >1 indicates increased occurrence of no health check. Findings: The mean age (IQR) of the included female sample (aged 40-74 years) was 52.9 years (45.0-59.0). Adjusted for patient-level factors (age, ethnicity, English as first language, overweight/obesity, smoking, attendance to GP practices, and co-morbidity), the odds of non-uptake of health checks were higher for Other White (OR 1.24, 95% confidence interval 1.17-1.33), and Other ethnicity (1.20, 1.07-1.35) vs. White British. It was also higher for 50-69 year olds (1.55, 1.47-1.62), 70-74 year olds (1.60, 1.49-1.72) vs. 40-49 year olds. These ORs did not change on adjustments for practice level factors (proportion of patients living in deprived areas, proportion of patients with ≥1 chronic condition, ≥3 emergency diabetes admissions annually, GP density/1000 patients, quality outcome framework score of ≥ 95%, and patient satisfaction scores of ≥80%). Non-uptake was lower for Black Caribbeans, Bangladeshis, overweight/obese patients, frequent practice attenders and comorbid patients. Interpretation: Differential uptake in health checks remained after adjustment for patient and practice level factors. Better measures of social determinants of health and of practice context are needed. Funding: NIHR Research for Patient Benefit Programme (NIHR202769).

Objectives Explore inequalities in risk factors, mental and physical health morbidity in non-pregnant women of reproductive age in contact with mental health services and how these vary per ethnicity.Design Retrospective cohort study.Setting Data from Lambeth DataNet, anonymised primary care records of this ethnically diverse London borough, linked to anonymised electronic mental health records (‘CRIS secondary care database’).Participants Women aged 15–40 years with an episode of secondary mental health care between January 2008 and December 2018 and no antenatal or postnatal Read codes (n=3817) and a 4:1 age-matched comparison cohort (n=14 532).Main outcome measures Preconception risk factors including low/high body mass index, smoking, alcohol, substance misuse, micronutrient deficiencies and physical diagnoses.Results Women in contact with mental health services (whether with or without severe mental illness (SMI)) had a higher prevalence of all risk factors and physical health diagnoses studied. Women from minority ethnic groups were less likely to be diagnosed with depression in primary care compared with white British women (adjusted OR 0.66 (0.55–0.79) p

Abstract Background Patients continue to suffer from medically unexplained symptoms otherwise referred to as persistent physical symptoms (PPS). General practitioners (GPs) play a key role in the management of PPS and require further training. Patients are often frustrated with the care they receive. This study aims to assess the acceptability of an ‘integrated GP care’ approach which consists of offering self-help materials to patients with PPS and offering their GPs training on how to utilise cognitive behavioural skills within their consultations, as well as assessing the feasibility of conducting a future trial in primary care to evaluate its benefit. Methods A feasibility cluster randomised controlled trial was conducted in primary care, South London, UK. GP practices (clusters) were randomly allocated to ‘integrated GP care plus treatment as usual’ or ‘treatment as usual’. Patients with PPS were recruited from participating GP practices before randomisation. Feasibility parameters, process variables and potential outcome measures were collected at pre-randomisation and at 12- and 24-weeks post-randomisation at cluster and individual participant level. Results Two thousand nine hundred seventy-eight patients were identified from 18 GP practices. Out of the 424 patients who responded with interest in the study, 164 fully met the eligibility criteria. One hundred sixty-one patients provided baseline data before cluster randomisation and therefore were able to participate in the study. Most feasibility parameters indicated that the intervention was acceptable and a future trial feasible. 50 GPs from 8 GP practices (randomised to intervention) attended the offer of training and provided positive feedback. Scores in GP knowledge and confidence increased post-training. Follow-up rate of patients at 24 weeks was 87%. However estimated effect sizes on potential clinical outcomes were small. Conclusions It was feasible to identify and recruit patients with PPS. Retention rates of participants up to 24 weeks were high. A wide range of health services were used. The intervention was relatively low cost and low risk. This complex intervention should be further developed to improve patients’/GPs’ utilisation of audio/visual and training resources before proceeding to a full trial evaluation. Trial registration NCT02444520 (ClinicalTrials.gov).

Abstract Background Research is fundamental to high-quality care, but concerns have been raised about whether health research is conducted in the populations most affected by high disease prevalence. Geographical distribution of research activity is important for many reasons. Recruitment is a major barrier to research delivery, and undertaking recruitment in areas of high prevalence could be more efficient. Regional variability exists in risk factors and outcomes, so research done in healthier populations may not generalise. Much applied health research evaluates interventions, and their impact may vary by context (including geography). Finally, fairness dictates that publically funded research should be accessible to all, so that benefits of participating can be fairly distributed. We explored whether recruitment of patients to health research is aligned with disease prevalence in England. Methods We measured disease prevalence using the Quality and Outcomes Framework in England (total long-term conditions, mental health and diabetes). We measured research activity using data from the NIHR Clinical Research Network. We presented descriptive data on geographical variation in recruitment rates. We explored associations between the recruitment rate and disease prevalence rate. We calculated the share of patient recruitment that would need to be redistributed to align recruitment with prevalence. We assessed whether associations between recruitment rate and disease prevalence varied between conditions, and over time. Results There was significant geographical variation in recruitment rates. When areas were ranked by disease prevalence, recruitment was not aligned with prevalence, with disproportionately low recruitment in areas with higher prevalence of total long-term and mental health conditions. At the level of 15 local networks, analyses suggested that around 12% of current recruitment activity would need to be redistributed to align with disease prevalence. Overall, alignment showed little change over time, but there was variation in the trends over time in individual conditions. Conclusions Geographical variations in recruitment do not reflect the suitability of the population for research. Indicators should be developed to assess the fit between research and need, and to allow assessment of interventions among funders, researchers and patients to encourage closer alignment between research activity and burden.

Summary: Background: Social and material deprivation accelerate the development of multimorbidity, yet the mechanisms which drive multimorbidity pathways and trajectories remain unclear. We aimed to examine the association between health inequality, risk factors and accumulation or resolution of LTCs, taking disease sequences into consideration. Methods: We conducted a retrospective cohort of adults aged 18 years and over, registered between April 2005 and May 2020 in general practices in one inner London borough (n = 826,936). Thirty-two long term conditions (LTCs) were selected using a consensus process, based on a definition adapted to the demographic characteristics of the local population. sThe development and resolution of these LTCs were examined according to sociodemographic and clinical risk factors (hypertension; moderate obesity (BMI 30·0–39·9 kg/m2), high cholesterol (total cholesterol > 5 mmol/L), smoking, high alcohol consumption (>14 units per week), and psychoactive substance use), through the application of multistate Markov chain models. Findings: Participants were followed up for a median of 4.2 years (IQR = 1·8 - 8·4); 631,760 (76%) entered the study with no LTCs, 121,424 (15%) with 1 LTC, 41,720 (5%) with 2 LTCs, and 31,966 (4%) with three or more LTCs. At the end of follow-up, 194,777 (24%) gained one or more LTCs, while 45,017 (5%) had resolved LTCs and 27,021 (3%) died. In multistate models, deprivation (hazard ratio [HR] between 1·30 to 1·64), female sex (HR 1·13 to 1·20), and Black ethnicity (HR 1·20 to 1·30; vs White) were independently associated with increased risk of transition from one to two LTCs, and shorter time spent in a healthy state. Substance use was the strongest risk factor for multimorbidity with an 85% probability of gaining LTCs over the next year. First order Markov chains identified consistent disease sequences including: chronic pain or osteoarthritis followed by anxiety and depression; alcohol and substance dependency followed by HIV, viral hepatitis, and liver disease; and morbid obesity followed by diabetes, hypertension, and chronic pain. Interpretation: We examined the relations among 32 LTCs, taking the order of disease occurrence into consideration. Distinctive patterns for the development and accumulation of multimorbidity have emerged, with increased risk of transitioning from no conditions to multimorbidity and mortality related to ethnicity, deprivation and gender. Musculoskeletal disorders, morbid obesity and substance abuse represent common entry points to multimorbidity trajectories.

BackgroundThe effect of antibiotics on the human microbiome is now well established, but their indirect effect on the related immune response is less clear. The possible association of Herpes zoster, which involves a reactivation of a previous varicella zoster virus infection, with prior antibiotic exposure might indicate a potential link with the immune response.MethodsA case-control study was carried out using a clinical database, the UK's Clinical Practice Research Datalink. A total of 163,754 patients with varicella zoster virus infection and 331,559 age/sex matched controls were identified and their antibiotic exposure over the previous 10 years, and longer when data permitted, was identified. Conditional logistic regression was used to identify the association between antibiotic exposure and subsequent infection in terms of volume and timing.ResultsThe study found an association of antibiotic prescription and subsequent risk of varicella zoster virus infection (adjusted odds ratio of 1.50; 95%CIs: 1.42-1.58). The strongest association was with a first antibiotic over 10 years ago (aOR: 1.92; 95%CIs: 1.88-1.96) which was particularly pronounced in the younger age group of 18 to 50 (aOR 2.77; 95%CIs: 1.95-3.92).ConclusionsBy finding an association between prior antibiotics and Herpes zoster this study has shown that antibiotics may be involved in the reactivation of the varicella zoster virus. That effect, moreover, may be relatively long term. This indirect effect of antibiotics on viruses, possibly mediated through their effect on the microbiome and immune system, merits further study.

Objectives Sickness absence is strongly associated with poor mental health, and mental disorders often go untreated. In this population-based cohort study, we identified people receiving fit notes from their general practitioner (GP) and determined access to mental health treatment stratified by health complaint and demographic variables.Design Longitudinal study of health records.Setting Primary care and secondary mental health care in the borough of Lambeth, South London. Forty-five GP practices in Lambeth and the local secondary mental healthcare trust.Participants The analytical sample included 293 933 working age adults (16–60 years) registered at a Lambeth GP practice between 1 January 2014 and 30 April 2016.Primary and secondary outcome measures Three indicators of mental healthcare in the year after first fit note were antidepressant prescription, contact with Improving Access to Psychological Therapy (IAPT) services and contact with secondary mental health services.Results 75% of people with an identified mental health condition at first fit note had an indicator of mental healthcare in the following year. Black Caribbean and Black African groups presenting with mental disorders were less likely to have a mental healthcare indicator compared with White British groups.Conclusions The majority of those with an identified mental health need receive some treatment in the year following a fit note; however, our results suggest Black African and Black Caribbean groups with an identified mental healthcare need have less complete access compared to the White British group.

Objectives People with epilepsy (PWE) have a higher mortality rate than the general population. Epilepsy-related deaths have increased despite all-cause mortality decreasing in the general population pre-COVID-19. We hypothesised that clinical and lifestyle factors may identify people more at risk.Design We used a retrospective cohort study to explore cause of death and a nested case–control study to identify risk factors.Setting We explored factors associated with mortality using primary care population data from 1 April 2004 to 31 March 2014. Data were obtained from the Clinical Practice Research Datalink which compiles anonymised patient data from primary care in the UK. Cause of death data was supplemented from the Office of National Statistics when available.Participants The analysis included 70 431 PWE, with 11 241 registered deaths.Results The number of deaths within the database increased by 69% between the first and last year of the study. Epilepsy was considered as a contributing cause in approximately 45% of deaths of PWE under 35. Factors associated with increased risk of death included attendance at emergency departments and/or emergency admissions (OR 3.48, 95% CI 3.19 to 3.80), antiepileptic drug (AED) polytherapy (2 AEDs: OR 1.60, 95% CI 1.51 to 1.71; 3 AEDs: OR 2.06, 95% CI 1.86 to 2.29; 4+AEDs: OR 2.62, 95% CI 2.23 to 3.08), status epilepticus (OR 2.78, 95% CI 1.64 to 4.71), depression (OR 1.67, 95% CI 1.57 to 1.76) and injuries (OR 1.54, 95% CI 1.43 to 1.67). No seizures in the prior year (OR 0.52, 95% CI 0.41 to 0.65).Conclusion Our results add to existing evidence that deaths in epilepsy are increasing. Future studies could focus on identifying PWE at high risk and addressing them with clinical interventions or better self-management. Identifying specific risk factors for younger people should be a priority as epilepsy may be a factor in close to half of deaths of PWE under 35 years of age.

Abstract Background Persistent physical symptoms (PPS), also known as medically unexplained symptoms (MUS), affect approximately 50% of patients in secondary care and are often associated with disability, psychological distress and increased health care costs. Cognitive behavioural therapy (CBT) has demonstrated both short- and long-term efficacy with small to medium effect sizes for PPS, with larger treatment effects for specific PPS syndromes, including non-cardiac chest pain, irritable bowel syndrome (IBS) and chronic fatigue syndrome (CFS). Research indicates that PPS conditions share similar cognitive and behavioural responses to symptoms, such as avoidance and unhelpful beliefs. This suggests that a transdiagnostic approach may be beneficial for patients with PPS. Methods A randomised controlled trial (RCT) will be conducted to evaluate the efficacy and cost-effectiveness of a transdiagnostic CBT-based intervention for PPS. 322 participants with PPS will be recruited from secondary care clinics. Participants stratified by clinic and disability level will be randomised to CBT plus standard medical care (SMC) versus SMC alone. The intervention consists of 8 CBT sessions delivered by a qualified therapist over a period of 20 weeks. Outcomes will be assessed at 9, 20, 40- and 52-weeks post randomisation. Efficacy will be assessed by examining the difference between arms in the primary outcome Work and Social Adjustment Scale (WSAS) at 52 weeks after randomisation. Secondary outcomes will include mood, symptom severity and clinical global impression at 9, 20, 40 and 52 weeks. Cost-effectiveness will be evaluated by combining measures of health service use, informal care, loss of working hours and financial benefits at 52 weeks. Discussion This trial will provide a powered evaluation of the efficacy and cost-effectiveness of a transdiagnostic CBT approach versus SMC for patients with PPS. It will also provide valuable information about potential healthcare pathways for patients with PPS within the National Health Service (NHS). Trial registration ClinicalTrials.gov NCT02426788. Registered 27 April 2015. Overall trial status: Ongoing; Recruitment status: No longer recruiting.

Background The Patient Health Questionnaire-9 (PHQ-9) is a widely used measure of depression in primary care. It was, however, originally designed as a diagnostic screening tool, and not for measuring change in response to antidepressant treatment. Although the Quick Inventory of Depressive Symptomology (QIDS-SR-16) has been extensively validated for outcome measurement, it is poorly adopted in UK primary care, and, although free for clinicians, has licensing restrictions for healthcare organisation use. Aims We aimed to develop a modified version of the PHQ-9, the Maudsley Modified PHQ-9 (MM-PHQ-9), for tracking symptom changes in primary care. We tested the measure's validity, reliability and factor structure. Method A sample of 121 participants was recruited across three studies, and comprised 78 participants with major depressive disorder and 43 controls. MM-PHQ-9 scores were compared with the QIDS-SR-16 and Clinical Global Impressions improvement scale, for concurrent validity. Internal consistency of the scale was assessed, and principal component analysis was conducted to determine the items’ factor structure. Results The MM-PHQ-9 demonstrated good concurrent validity with the QIDS-SR-16, and excellent internal consistency. Sensitivity to change over a 14-week period was d = 0.41 compared with d = 0.61 on the QIDS-SR-16. Concurrent validity between the paper and mobile app versions of the MM-PHQ-9 was r = 0.67. Conclusions These results indicate that the MM-PHQ-9 is a valid and reliable measure of depressive symptoms in paper and mobile app format, although further validation is required. The measure was sensitive to change, demonstrating suitability for use in routine outcome assessment.

Background NHS Practitioner Health is the England wide programme providing mental health and addiction healthcare to doctors and dentists. Outcomes are assessed using five measures. Aims To contribute to a service evaluation of NHS Practitioner Health. To determine responsiveness to change and compare outcome measures. Method Measures were completed at baseline and 6 months: Generalized Anxiety Disorder Assessment (GAD-7), Perceived Stress Scale (PSS), Patient Health Questionaire-9 (PHQ-9), Warwick-Edinburgh Mental Wellbeing scale (WEMWBS), Psychological Outcome Profiles (PSYCHLOPS). Responsiveness to change was determined using effect size with improvement threshold ≥0.80. Instruments were compared using Bland–Altman plots. Results Our sample, n = 402; with 14 (3.5%) excluded for missing data; final sample, n = 388. All measures showed strong mean effect sizes: PSYCHLOPS 1.86 (95%CI 1.73–1.99), 75.8% ≥0.80; PSS 1.48 (1.34–1.62), 64.4% ≥0.80; WEMWBS 1.24 (1.13–1.35), 58.2% ≥0.80; GAD-7 1.07 (0.96–1.18), 52.8% ≥0.80; PHQ-9 0.86 (0.76–0.96), 52.8% ≥0.80. Findings were largely unchanged after stratification by diagnosis, presenting problem or therapy type. Fifty (12.9%) participants did not reach the threshold for improvement on any instrument. Bland–Altman plots indicated generally strong agreement between measures; combining PSYCHLOPS with WEMWBS maximised capture of improvement with only 3.6% of patients lying outside limits of agreement; GAD-7 was most likely to duplicate recovery scores of other measures. Conclusions Patients attending the NHS Practitioner Health service demonstrated high levels of improvement in mental health scores. The patient-generated instrument produced higher change scores than standardised instruments. Combining PSYCHLOPS and WEMWBS captured 96% of patients with above threshold improvement; GAD-7 added little to overall recovery measurement.

Introduction This short article summarises findings about reduced physical activity of adults with progressive muscle disease as a result of COVID-19 lockdown.Methods As part of an ongoing longitudinal cohort study, we prospectively and objectively measured physical activity using accelerometry at baseline in 2019 and follow-up in 2020. A subset of 85 participants incidentally had follow-up data collected during the first UK COVID-19 lockdown from 23 March to 4 July 2020. Thus, for this cohort we had activity data from before and during the COVID-19 pandemic and we were able to prospectively and accurately quantify the changes in their physical activity.Results Our data highlighted reduced overall activity intensity and reduced light activity time in particular.Conclusions From our findings, we can infer specific evidence-based recommendations about how to redress inactivity secondary to COVID-19 restrictions for adults with progressive muscle diseases. These recommendations are likely to be generalisable to other groups who are vulnerable to functional decline secondary to prolonged inactivity.

Background: The threat of antimicrobial resistance has led to intensified efforts to reduce antibiotic utilisation, but serious bacterial infections are increasing in frequency. Objectives: To estimate the risks of serious bacterial infections in association with lower antibiotic prescribing and understand stakeholder views with respect to safe antibiotic reduction. Design: Mixed-methods research was undertaken, including a qualitative interview study of patient and prescriber views that informed a cohort study and a decision-analytic model, using primary care electronic health records. These three work packages were used to design an application (app) for primary care prescribers. Data sources: The Clinical Practice Research Datalink. Setting: This took place in UK general practices. Participants: A total of 706 general practices with 66.2 million person-years of follow-up from 2002 to 2017 and antibiotic utilisation evaluated for 671,830 registered patients. The qualitative study included 31 patients and 30 health-care professionals from primary care. Main outcome measures: Sepsis and localised bacterial infections. Results: Patients were concerned about antimicrobial resistance and the side effects, as well as the benefits, of antibiotic treatment. Prescribers viewed the onset of sepsis as the most concerning potential outcome of reduced antibiotic prescribing. More than 40% of antibiotic prescriptions in primary care had no coded indication recorded across both Vision® and EMIS® practice systems. Antibiotic prescribing rates varied widely between general practices, but there was no evidence that serious bacterial infections were less frequent at higher prescribing practices (adjusted rate ratio for 20% increase in prescribing 1.03, 95% confidence interval 1.00 to 1.06; p = 0.074). The probability of sepsis was lower if an antibiotic was prescribed at an infection consultation, and the number of antibiotic prescriptions required to prevent one episode of sepsis (i.e. the number needed to treat) decreased with age. For those aged 0–4 years, the number needed to treat was 29,773 (95% uncertainty interval 18,458 to 71,091) in boys and 27,014 (95% uncertainty interval 16,739 to 65,709) in girls. For those aged > 85 years, the number needed to treat was 262 (95% uncertainty interval 236 to 293) in men and 385 (95% uncertainty interval 352 to 421) in women. Frailty was associated with a greater risk of sepsis and a smaller number needed to treat. For severely frail patients aged 55–64 years, the number needed to treat was 247 (95% uncertainty interval 156 to 459) for men and 343 (95% uncertainty interval 234 to 556) for women. At all ages, the probability of sepsis was greatest for urinary tract infection, followed by skin infection and respiratory tract infection. The numbers needed to treat were generally smaller for the period 2014–17, when sepsis was diagnosed more frequently. The results are available using an app that we developed to provide primary care prescribers with stratified risk estimates during infection consultations. Limitations: Analyses were based on non-randomised comparisons. Infection episodes and antibiotic prescribing are poorly documented in primary care. Conclusions: Antibiotic treatment is generally associated with lower risks, but the most serious bacterial infections remain infrequent even without antibiotic treatment. This research identifies risk strata in which antibiotic prescribing can be more safely reduced. Future work: The software developed from this research may be further developed and investigated for antimicrobial stewardship effect. Funding: This project was funded by the National Institute for Health Research (NIHR) Health Services and Delivery Research programme and will be published in full in Health Services and Delivery Research; Vol. 9, No. 9. See the NIHR Journals Library website for further project information.

Background: Globally, there is increasing research on clusters of multimorbidity, but few studies have investigated multimorbidity in urban contexts characterised by a young, multi-ethnic, deprived populations. This study identified clusters of associative multimorbidity in an urban setting. Methods: This is a population-based retrospective cross-sectional study using electronic health records of all adults aged 18 years and over, registered between April 2005 to May 2020 in general practices in one inner London borough. Multiple correspondence analysis and cluster analysis was used to identify groups of multimorbidity from 32 long-term conditions (LTCs). Results: The population included 41 general practices with 826,936 patients registered between 2005 and 2020, with mean age 40 (SD15·6) years. The prevalence of multimorbidity was 21% (n = 174,881), with the median number of conditions being three and increasing with age. Analysis identified five consistent LTC clusters: 1) anxiety and depression (Ratio of within- to between- sum of squares (WSS/BSS

Objectives The fit note replaced the sick note in the UK in 2010, with the aim of improving support for patients requiring sickness absence, yet there has been very little research into fit note use. This study aims to describe number of fit notes by condition, to improve our understanding of patterns of fit note use in primary care. Previous fit note research has relied on extracting diagnoses directly from fit notes, rather than extracting information from clinical records. In this paper, we extract information from clinical records to explore demographic factors and conditions associated with number of fit notes issued.Design This is a longitudinal study of clinical data. We analysed individual-level anonymised data from general practitioner consultations, including demographic information and condition recorded at first fit note. The latter encompassed diagnoses, individual symptoms and psychosocial issues.Setting A database called Lambeth DataNet, containing electronic clinical records on 326 415 adults (ages 16–60) from all 45 general practices within the London Borough of Lambeth from 1 January 2014 to 30 April 2017.Participants Our analytical sample contained 40 698 people with a condition recorded at first fit note.Primary outcome measure Predicted number of fit notes in the period January 2014–April 2017Results Of all studied diagnostic groups, mental illness had the highest predicted number of fit notes (n=3.3; 95% CI: 3.1 to 3.4) after controlling for demographic factors and long-term conditions. The highest predicted number of fit notes for any condition subgroup was among patients presenting for drug and/or alcohol misuse (n=4.5; 95% CI: 4.1 to 4.8).Conclusions For the first time, we show drug and/or alcohol misuse at first fit note are associated with the highest number of fit notes. Research is needed to understand the trajectories of individuals at highest risk of long-term sickness absence, in particular, people presenting with drug and/or alcohol misuse.

Antibiotics in childhood have been linked with diseases including asthma, juvenile arthritis, type 1 diabetes, Crohn’s disease and mental illness. The underlying mechanisms are thought related to dysbiosis of the gut microbiome. We conducted a systematic review of the association between antibiotics and disruption of the pediatric gut microbiome. Searches used MEDLINE, EMBASE and Web of Science. Eligible studies: association between antibiotics and gut microbiome dysbiosis; children 0–18 years; molecular techniques of assessment; outcomes of microbiome richness, diversity or composition. Quality assessed by Newcastle–Ottawa Scale or Cochrane Risk of Bias Tool. Meta-analysis where possible. A total of 4,668 publications identified: 12 in final analysis (5 randomized controlled trials (RCTs), 5 cohort studies, 2 cross-sectional studies). Microbiome richness was measured in 3 studies, species diversity in 6, and species composition in 10. Quality of evidence was good or fair. 5 studies found a significant reduction in diversity and 3 a significant reduction in richness. Macrolide exposure was associated with reduced richness for twice as long as penicillin. Significant reductions were seen in Bifidobacteria (5 studies) and Lactobacillus (2 studies), and significant increases in Proteobacteria such as E. coli (4 studies). A meta-analysis of RCTs of the effect of macrolide (azithromycin) exposure on the gut microbiome found a significant reduction in alpha-diversity (Shannon index: mean difference −0.86 (95% CI −1.59, −0.13). Antibiotic exposure was associated with reduced microbiome diversity and richness, and with changes in bacterial abundance. The potential for dysbiosis in the microbiome should be taken into account when prescribing antibiotics for children. Systematic review registration number: CRD42018094188

Background: Primary care in England is contracted to provide essential services. Many practices also provide additional services, termed ‘directed enhanced services’ (DES), for extra income. The optional nature of DES may result in inequitable service delivery. Aim: To determine the range of DES activity and equity of service provision. Design & setting: A cross-sectional analysis of data from general practices in England took place from 2018–2019. Method: DES were defined in terms of activity level and measured as total DES funding per registered patient. Linear regression modelling was used to explore the relationship between DES activity, practice, and population characteristics. Results: Data were available for 6873 practices providing up to 10 DES in the initial sample. Due to negative funding amounts and a list size of ≤750 registered patients, 24 practices were excluded. Of the final sample (n = 6849), highest DES provision was for influenza and pneumococcal immunisation (99.9%), pertussis immunisation (97.9%), rotavirus and shingles immunisation (99.9%), meningitis immunisation (99.7%), and childhood immunisation (99.6%); lowest provision was for extended hours access (72.4%), violent patient services (2.0%), and out-of-area urgent care (1.3%). Mean DES funding was £6.25 per patient. In deprived areas, DES funding was £0.35 lower (95% confidence interval [CI] = £0.60 to £0.10) per patient (most versus least deprived quintiles); ethnic group-related differences were not significant. DES funding was higher in practices with more GPs or practice nurses per patient. In deprived communities, there was less immunisation activity (including influenza, pneumococcal, meningitis, childhood, and rotavirus and shingles immunisation) and provision of extended hours access; however, learning disability checks provision was greater in these communities. Conclusion: DES provision is lower in deprived areas (notably for immunisations and some aspects of access) but higher in better staffed practices. Voluntary quality schemes may contribute to widening health inequalities.

Background: People of minority ethnic backgrounds may be disproportionately affected by severe COVID-19. Whether this relates to increased infection risk, more severe disease progression, or worse in-hospital survival is unknown. The contribution of comorbidities or socioeconomic deprivation to ethnic patterning of outcomes is also unclear. Methods: We conducted a case-control and a cohort study in an inner city primary and secondary care setting to examine whether ethnic background affects the risk of hospital admission with severe COVID-19 and/or in-hospital mortality. Inner city adult residents admitted to hospital with confirmed COVID-19 (n = 872 cases) were compared with 3,488 matched controls randomly sampled from a primary healthcare database comprising 344,083 people residing in the same region. For the cohort study, we studied 1827 adults consecutively admitted with COVID-19. The primary exposure variable was self-defined ethnicity. Analyses were adjusted for socio-demographic and clinical variables. Findings: The 872 cases comprised 48.1% Black, 33.7% White, 12.6% Mixed/Other and 5.6% Asian patients. In conditional logistic regression analyses, Black and Mixed/Other ethnicity were associated with higher admission risk than white (OR 3.12 [95% CI 2.63–3.71] and 2.97 [2.30–3.85] respectively). Adjustment for comorbidities and deprivation modestly attenuated the association (OR 2.24 [1.83–2.74] for Black, 2.70 [2.03–3.59] for Mixed/Other). Asian ethnicity was not associated with higher admission risk (adjusted OR 1.01 [0.70–1.46]). In the cohort study of 1827 patients, 455 (28.9%) died over a median (IQR) of 8 (4–16) days. Age and male sex, but not Black (adjusted HR 1.06 [0.82–1.37]) or Mixed/Other ethnicity (adjusted HR 0.72 [0.47–1.10]), were associated with in-hospital mortality. Asian ethnicity was associated with higher in-hospital mortality but with a large confidence interval (adjusted HR 1.71 [1.15–2.56]). Interpretation: Black and Mixed ethnicity are independently associated with greater admission risk with COVID-19 and may be risk factors for development of severe disease, but do not affect in-hospital mortality risk. Comorbidities and socioeconomic factors only partly account for this and additional ethnicity-related factors may play a large role. The impact of COVID-19 may be different in Asians. Funding: British Heart Foundation; the National Institute for Health Research; Health Data Research UK.

Purpose The emergence of antimicrobial resistance has led to increasing efforts to reduce unnecessary use of antibiotics in primary care, but potential hazards from bacterial infection continue to cause concern. This study investigated how primary care prescribers perceive risk and safety concerns associated with reduced antibiotic prescribing.Methods Qualitative study using semistructured interviews conducted with primary care prescribers from 10 general practices in an urban area and a shire town in England. A thematic analysis was conducted.Results Thirty participants were recruited, including twenty-three general practitioners, five nurses and two pharmacists. Three main themes were identified: risk assessment, balancing treatment risks and negotiating decisions and risks. Respondents indicated that their decisions were grounded in clinical risk assessment, but this was informed by different approaches to antibiotic use, with most leaning towards reduced prescribing. Prescribers’ perceptions of risk included the consequences of both inappropriate prescribing and inappropriate withholding of antibiotics. Sepsis was viewed as the most concerning potential outcome of non-prescribing, leading to possible patient harm and potential litigation. Risks of antibiotic prescribing included antibiotic resistant and Clostridium difficile infections, as well as side effects, such as rashes, that might lead to possible mislabelling as antibiotic allergy. Prescribers elicited patient preferences for use or avoidance of antibiotics to inform management strategies, which included educational advice, advice on self-management including warning signs, use of delayed prescriptions and safety netting.Conclusions Attitudes towards antibiotic prescribing are evolving, with reduced antibiotic prescribing now being approached more systematically. The safety trade-offs associated with either use or non-use of antibiotics present difficulties especially when prescribing decisions are inconsistent with patients’ expectations.

BackgroundEfforts to reduce unnecessary antibiotic prescribing have coincided with increasing awareness of sepsis. We aimed to estimate the probability of sepsis following infection consultations in primary care when antibiotics were or were not prescribed.Methods and findingsWe conducted a cohort study including all registered patients at 706 general practices in the United Kingdom Clinical Practice Research Datalink, with 66.2 million person-years of follow-up from 2002 to 2017. There were 35,244 first episodes of sepsis (17,886, 51%, female; median age 71 years, interquartile range 57-82 years). Consultations for respiratory tract infection (RTI), skin or urinary tract infection (UTI), and antibiotic prescriptions were exposures. A Bayesian decision tree was used to estimate the probability (95% uncertainty intervals [UIs]) of sepsis following an infection consultation. Age, gender, and frailty were evaluated as association modifiers. The probability of sepsis was lower if an antibiotic was prescribed, but the number of antibiotic prescriptions required to prevent one episode of sepsis (number needed to treat [NNT]) decreased with age. At 0-4 years old, the NNT was 29,773 (95% UI 18,458-71,091) in boys and 27,014 (16,739-65,709) in girls; over 85 years old, NNT was 262 (236-293) in men and 385 (352-421) in women. Frailty was associated with greater risk of sepsis and lower NNT. For severely frail patients aged 55-64 years, the NNT was 247 (156-459) in men and 343 (234-556) in women. At all ages, the probability of sepsis was greatest for UTI, followed by skin infection, followed by RTI. At 65-74 years, the NNT following RTI was 1,257 (1,112-1,434) in men and 2,278 (1,966-2,686) in women; the NNT following skin infection was 503 (398-646) in men and 784 (602-1,051) in women; following UTI, the NNT was 121 (102-145) in men and 284 (241-342) in women. NNT values were generally smaller for the period from 2014 to 2017, when sepsis was diagnosed more frequently. Lack of random allocation to antibiotic therapy might have biased estimates; patients may sometimes experience sepsis or receive antibiotic prescriptions without these being recorded in primary care; recording of sepsis has increased over the study period.ConclusionsThese stratified estimates of risk help to identify groups in which antibiotic prescribing may be more safely reduced. Risks of sepsis and benefits of antibiotics are more substantial among older adults, persons with more advanced frailty, or following UTIs.

Introduction The Antidepressant Advisor Study is a feasibility trial of a computerised decision-support tool which uses an algorithm to provide antidepressant treatment guidance for general practitioners (GPs) in the UK primary care service. The tool is the first in the UK to implement national guidelines on antidepressant treatment guidance into a computerised decision-support tool.Methods and analysis The study is a parallel group, cluster-randomised controlled feasibility trial where participants are blind to treatment allocation. GPs were assigned to two treatment arms: (1) treatment-as-usual (TAU) and (2) computerised decision-support tool to assist with antidepressant choices. The study will assess recruitment and lost to follow-up rates, GP satisfaction with the tool and impact on health service use. A meaningful long-term roll-out unit cost will be calculated for the tool, and service use data will be collected at baseline and follow-up to inform a full economic evaluation of a future trial.Ethics and dissemination The study has received National Health Service ethical approval from the London—Camberwell St Giles Research Ethics Committee (ref: 17/LO/2074). The trial was pre-registered in the Clinical Trials.gov registry. The results of the study will be published in a pre-publication archive within 1 year of completion of the last follow-up assessment.Trial registration number NCT03628027.

ObjectiveThis study evaluated whether serious bacterial infections are more frequent at family practices with lower antibiotic prescribing rates.DesignCohort study.Setting706 UK family practices in the Clinical Practice Research Datalink from 2002 to 2017.Participants10.1 million registered patients with 69.3 million patient-years’ follow-up.ExposuresAll antibiotic prescriptions, subgroups of acute and repeat antibiotic prescriptions, and proportion of antibiotic prescriptions associated with specific-coded indications.Main outcome measuresFirst episodes of serious bacterial infections. Poisson models were fitted adjusting for age group, gender, comorbidity, deprivation, region and calendar year, with random intercepts representing family practice-specific estimates.ResultsThe age-standardised antibiotic prescribing rate per 1000 patient-years increased from 2002 (male 423; female 621) to 2012 (male 530; female 842) before declining to 2017 (male 449; female 753). The median family practice had an antibiotic prescribing rate of 648 per 1000 patient-years with 95% range for different practices of 430–1038 antibiotic prescriptions per 1000 patient-years. Specific coded indications were recorded for 58% of antibiotic prescriptions at the median family practice, the 95% range at different family practices was from 10% to 75%. There were 139 759 first episodes of serious bacterial infection. After adjusting for covariates and the proportion of coded consultations, there was no evidence that serious bacterial infections were lower at family practices with higher total antibiotic prescribing. The adjusted rate ratio for 20% higher total antibiotic prescribing was 1.03, (95% CI 1.00 to 1.06, p=0.074).ConclusionsWe did not find population-level evidence that family practices with lower total antibiotic prescribing might have more frequent occurrence of serious bacterial infections overall. Improving the recording of infection episodes has potential to inform better antimicrobial stewardship in primary care.

Abstract Background Medications targeting stroke risk factors have shown good efficacy, yet adherence is suboptimal. A lack of underlying theory may contribute to the ineffectiveness of eliciting or sustaining behaviour change in many existing interventions targeting medication adherence in stroke. Intervention effectiveness and implementation could be enhanced by consideration of evidence base and theory to drive development. The purpose of this study is to identify appropriate components for a theory-driven and evidence-based medication adherence intervention for stroke survivors. Methods The Behaviour Change Wheel (BCW), a guide to intervention development, informed our systematic process of intervention development. Our earlier systematic review had identified important determinants of medication adherence that were mapped into the Theoretical Domains Framework (TDF), with Knowledge, Beliefs about consequences and Emotions found to be more influential. Utilising the BCW facilitated selection of intervention options and behaviour change techniques (BCTs); the active ingredients within an intervention. To further refine BCT selection, APEASE criteria were employed, allowing evaluation of potential BCTs within context: The National Health Service (NHS), United Kingdom (UK). Results Five intervention functions (Education, Persuasion, Training, Environmental Restructuring and Enablement) and five policy categories (Communication/marketing, Guidelines, Regulation, Environmental/social planning and Service provision) were identified as potential intervention options, underpinned by our systematic review findings. Application of APEASE criteria led to an initial pool of 21 BCTs being reduced to 11 (e.g. Habit Formation, Information about Health Consequences and Action Planning) identified as potential intervention components that would both be feasible and directly target the underlying determinants of stroke survivors’ medication adherence. Conclusions Careful consideration of underlying evidence and theory to drive intervention design, facilitated by the BCW, enabled identification of appropriate intervention components. BCTs including Habit Formation, Information about Health Consequences and Self-monitoring of Behaviour were considered potentially effective and appropriate to deliver within the NHS. Having reduced the pool of potential intervention components to a manageable number, it will now be possible to explore the perceived acceptability of selected BCTs in interviews with stroke survivors and healthcare professionals. This approach to intervention development should be generalisable to other chronic conditions and areas of behaviour change (e.g. exercise adherence).