UNASSIGNED: Electronic healthcare records (EHRs) are used to document diagnoses, symptoms, tests, and prescriptions. Though not primarily collected for research purposes, owing to the size of the data as well as the depth of information collected, they have been used extensively to conduct epidemiological research. The Clinical Practice Research Datalink (CPRD) is an EHR database containing representative data of the UK population with regard to age, sex, race, and social deprivation measures. Fibrotic conditions are characterised by excessive scarring, contributing towards organ dysfunction and eventual organ failure. Fibrosis is associated with ageing as well as many other factors, it is hypothesised that fibrotic conditions are caused by the same underlying pathological mechanism. We calculated the prevalence of fibrotic conditions (as defined in a previous Delphi survey of clinicians) as well as the prevalence of fibrotic multimorbidity (the proportion of people with multiple fibrotic conditions).
UNASSIGNED: We included a random sample of 993,370 UK adults, alive, and enrolled at a UK general practice, providing data to the CPRD Aurum database as of 1st of January 2015. Individuals had to be eligible for linkage to hospital episode statistics (HES) and ONS death registration. We calculated the point prevalence of fibrotic conditions and multi-morbid fibrosis on the 1st of January 2015. Using death records of those who died in 2015, we investigated the prevalence of fibrosis associated death. We explored the most commonly co-occurring fibrotic conditions and determined the settings in which diagnoses were commonly made (primary care, secondary care or after death).
UNASSIGNED: The point prevalence of any fibrotic condition was 21.46%. In total, 6.00% of people had fibrotic multimorbidity. Of the people who died in 2015, 34.82% had a recording of a fibrotic condition listed on their death certificate.
UNASSIGNED: The key finding was that fibrotic multimorbidity affects approximately 1 in 16 people.
Fibrotic conditions are scarring conditions which impact the way an organ functions and eventually lead to organ failure. We studied routinely collected health data from GPs, hospitals, and death certificates to estimate the percentage of UK adults who had fibrotic diseases. We found that 1 in 5 people had at least one fibrotic disease, and we also found that 1 in 16 people had more than one fibrotic disease.

The aim of this research was to describe the epidemiology, presentation and healthcare use in primary care for foot and ankle problems in children and young people (CYP) across England. We undertook a population-based cohort study using data from the Clinical Practice Research Datalink Aurum database, a database of anonymised electronic health records from general practices across England. Data was accessed for all CYP aged 0-18 years presenting to their general practitioner between January 2015 and December 2021 with a foot and/or ankle problem. Consultation rates were calculated and used to estimate numbers of consultations in an average practice. Hierarchical Poisson regression estimated relative rates of consultations across sociodemographic groups and logistic regression evaluated factors associated with repeat consultations. A total of 416,137 patients had 687,753 foot and ankle events, of which the majority were categorised as \"musculoskeletal\" (34%) and \"unspecified pain\" (21%). Rates peaked at 601 consultations per 10,000 patient-years among males aged 10-14 years in 2018. An average practice might observe 132 (95% CI 110 to 155) consultations annually. Odds for repeat consultations were higher among those with pre-existing diagnoses including juvenile arthritis (OR 1.73, 95% CI 1.48 to 2.03).    Conclusions: Consultations for foot and ankle problems were high among CYP, particularly males aged 10 to 14 years. These data can inform service provision to ensure CYP access appropriate health professionals for accurate diagnosis and treatment. What is Known: • Foot and ankle problems can have considerable impact on health-related quality of life in children and young people (CYP). • There is limited data describing the nature and frequency of foot and ankle problems in CYP. What is New: • Foot and ankle consultations were higher in English general practice among CYP aged 10 to 14 years compared to other age groups, and higher among males compared to females. • The high proportion of unspecified diagnoses and repeat consultations suggests there is need for greater integration between general practice and allied health professionals in community-based healthcare settings.

UNASSIGNED: Observational studies of polypharmacy and the risk of death or stroke in individuals with atrial fibrillation (AF) have produced inconsistent findings. By using propensity score matching (PSM) and Cox regression, this study aimed to determine whether polypharmacy (five to nine medicines) in the 3 months following AF diagnosis, is associated with an increased risk of death or ischemic stroke, compared to non-polypharmacy (one to four medicines).
UNASSIGNED: A prospective cohort study using data from the Clinical Practice Research Datalink (2006-2019). Data from 23 629 individuals with AF were analyzed. Cox regression models were adjusted for age, gender, morbidities, obesity, alcohol, smoking, and wealth. In the PSM models, cases and controls with near identical health profiles were selected from the study pool. The risk of death and stroke were presented as hazard ratios (HRs) with 95% confidence intervals (CIs).
UNASSIGNED: 68.9% (n = 16 271) of the participants had polypharmacy. PSM showed that polypharmacy was associated with an increased risk of death during follow-up (HR 1.32; 95% CI: 1.19-1.47, p < .01), but not ischemic stroke (HR 0.84; 95% CI: 0.69-1.02, p = .08).
UNASSIGNED: Polypharmacy was associated with an increased risk of death during follow-up, but not ischemic stroke, in individuals with AF. The effects of comorbidity and other confounding factors were reduced by using PSM. This study focused on the overall medication burden; however, further research is needed to identify which specific medications in polypharmacy regimens increase the risk of mortality in AF. These findings could inform prescribing practices in the future.

Calcitonin gene-related peptide monoclonal antibodies (CGRP mAbs) are recommended by the United Kingdom National Institute of Health and Care Excellence for the prevention of migraine as treatment beyond third line. We report migraine prevalence and preventive treatment patterns in the adult United Kingdom primary care population over a 7.5-year period, focusing on patients ceasing ≥ 3 oral preventive medication classes.
Study populations were retrieved from the Clinical Practice Research Datalink GOLD database (study period: 19 September 2012 to 1 January 2020; inclusion criteria: ≥12 months follow-up, current-in-dataset, adult on 1 January 2020). Patients who used ≥ 1 oral preventive medication with ≥ 3-year follow-up after first prescription were considered preventive treatment users; class cessation was defined as cessation without evidence of restart within 6 months from end-of-supply date.
On 1 January 2020, 3.0% of the total study population were diagnosed with migraine (n = 81,190/2,664,306); of these, 42.4% were preventive treatment users (n = 34,448/81,190). The most frequently used oral migraine preventive medication classes were beta-blockers (n = 14,713), tricyclic antidepressants (n = 14,415) and antiepileptics (n = 6497). Among preventive treatment users, 7.7% (n = 2653/34,448) ceased ≥ 3 oral preventive medication classes; of these, 21.7% (n = 576/2653) had been referred to a neurologist.
Compared to existing population-based estimates of migraine prevalence, our data further corroborates that a considerable proportion of patients with migraine do not seek treatment. Among those who sought primary care within a 7.5-year period, almost half received empirical oral preventive treatment. Importantly, nearly 1 of 10 preventive treatment users ceased ≥ 3 oral preventive medication classes, highlighting a need for additional therapeutic options. These patients may benefit from CGRP antagonists and/or injectable onabotulinumtoxinA; however, only a minority was referred to specialist care, where these options would be more available.
Not applicable.

UNASSIGNED: Risk factors for exacerbations of chronic obstructive pulmonary disease (COPD) have been previously characterized for patients with more severe cases of COPD. It is unclear how the risk of first exacerbation may best be identified in patients with less severe disease. This study investigated risk factors for first exacerbation among English patients with COPD classified as Global Initiative for Chronic Obstructive Lung Disease (GOLD) group A or B.
UNASSIGNED: A retrospective cohort study using data from the UK Clinical Practice Research Datalink (CPRD) AURUM linked to Hospital Episode Statistics. Patients with COPD aged ≥35 years and classified as GOLD group A or B (2020 criteria) from January 2013-December 2019 were eligible. Patients were required to have 24 months history in CPRD (baseline). Two cohorts were defined: cohort 1 included patients with no severe exacerbations during baseline; cohort 2 included patients with no moderate or severe exacerbations during baseline. Risk factors associated with severe, or combined moderate and severe exacerbation were examined for up to 5 years of follow-up.
UNASSIGNED: Overall, 194,948 patients were included in cohort 1 (mean age 66.2 years; 55.2% male), and 148,396 patients in cohort 2 (mean age 66.1 years; 56.6% male). Identified risk factors for exacerbation (and associated 1-year absolute risk of severe, or combined moderate and severe exacerbation, respectively) included: Medical Research Council dyspnea scale score (15.9%/28.4%); COPD Assessment Test score (9.6%/25.3%); GOLD grade of airflow limitation (forced expiratory volume in 1 second % predicted; 13.6%/27.5%); and lung cancer (8.1%/23.6%). After adjustment for risk factors, these factors remained independently associated with severe exacerbation at 1, 3, and 5 years of follow-up.
UNASSIGNED: The identified risk factors may aid physicians in the early recognition of patients with COPD classified as GOLD group A or B at risk of first exacerbation.

Electronic health records (EHRs) could identify long-term health effects of nicotine vaping. We characterised the extent to which vaping is recorded in primary care EHRs in the UK, on a population level.
We performed descriptive analysis of Clinical Practice Research Datalink (CPRD), primary care electronic health records of 25% of the UK population (~ 16 million patients). Patients aged ≥ 18 years whose vaping status was recorded using medical codes between 2006 and 2022 were identified. We reported the frequency of vaping codes; their distribution by patient age, gender, and ethnicity; trends in vaping recording over time (including interrupted time series analyses); and transitions in patient smoking status.
Seven medical codes indicated current or former vaping, from 150,114 patients. When their vaping status was first recorded, mean patient age was 50.2 years (standard deviation: 15.0), 52.4% were female, and 82.1% were White. Of those recorded as currently vaping, almost all (98.9%) had records of their prior smoking status: 55.0% had been smoking, 38.3% had stopped smoking, 5.6% had never smoked. Of those who were smoking prior to being recorded as vaping, more than a year after the vaping record, over a third (34.2%) were still smoking, under a quarter (23.7%) quit smoking, 1.7% received a \'never smoked\' status, and there was no smoking status for 40.4%. The \'e-cigarette or vaping product use-associated lung injury\' (EVALI) outbreak was significantly associated with a declining trend in new records of current vaping between September 2019 and March 2020; and an immediate significant increase in new records of former vaping, followed by a declining trend.
Few patients are being asked about vaping. Most who vape had smoked, and many quit smoking after starting vaping. To enable electronic health records to provide stronger evidence on health effects, we recommend improved completeness, accuracy and consistency.

BACKGROUND: There is limited evidence in humans as to whether antibiotics impact the effectiveness of cancer treatments. Rodent studies have shown that disruption in gut microbiota due to antibiotics decreases cancer therapy effectiveness. We evaluated the associations between the antibiotic treatment of different time periods before cancer diagnoses and long-term mortality.
METHODS: Using the Clinical Practice Research Datalink GOLD, linked to the Cancer Registry\'s and the Office for National Statistics\' mortality records, we delineated a study cohort that involved cancer patients who were prescribed antibiotics 0-3 months; 3-24 months; or more than 24 months before cancer diagnosis. Patients\' exposure to antibiotics was compared according to the recency of prescriptions and time-to-event (all-cause mortality) by applying Cox models.
RESULTS: 111,260 cancer patients from England were included in the analysis. Compared with antibiotic prescriptions that were issued in the past, patients who had been prescribed antibiotics shortly before cancer diagnosis presented an increased hazard ratio (HR) for mortality. For leukaemia, the HR in the Cancer Registry was 1.32 (95% CI 1.16-1.51), for lymphoma it was 1.22 (1.08-1.36), for melanoma it was 1.28 (1.10-1.49), and for myeloma it was 1.19 (1.04-1.36). Increased HRs were observed for cancer of the uterus, bladder, and breast and ovarian and colorectal cancer.
CONCLUSIONS: Antibiotics that had been issued within the three months prior to cancer diagnosis may reduce the effectiveness of chemotherapy and immunotherapy. Judicious antibiotic prescribing is needed among cancer patients.

BACKGROUND: Multiple sclerosis is a leading cause of non-traumatic neurological disability among young adults worldwide. Prior studies have identified modifiable risk factors for multiple sclerosis in cohorts of White ethnicity, such as infectious mononucleosis, smoking, and obesity during adolescence/early adulthood. It is unknown whether modifiable exposures for multiple sclerosis have a consistent impact on risk across ethnic groups.
OBJECTIVE: To determine whether modifiable risk factors for multiple sclerosis have similar effects across diverse ethnic backgrounds.
METHODS: We conducted a nested case-control study using data from the UK Clinical Practice Research Datalink. Multiple sclerosis cases diagnosed from 2001 until 2022 were identified from electronic healthcare records and matched to unaffected controls based on year of birth. We used stratified logistic regression models and formal statistical interaction tests to determine whether the effect of modifiable risk factors for multiple sclerosis differed by ethnicity.
RESULTS: We included 9662 multiple sclerosis cases and 118,914 age-matched controls. The cohort was ethnically diverse (MS: 277 South Asian [2.9%], 251 Black [2.6%]; Controls: 5043 South Asian [5.7%], 4019 Black [4.5%]). The age at MS diagnosis was earlier in the Black (40.5 [SD 10.9]) and Asian (37.2 [SD 10.0]) groups compared with White cohort (46.1 [SD 12.2]). There was a female predominance in all ethnic groups; however, the relative proportion of males was higher in the South Asian population (proportion of women 60.3% vs 71% [White] and 75.7% [Black]). Established modifiable risk factors for multiple sclerosis-smoking, obesity, infectious mononucleosis, low vitamin D, and head injury-were consistently associated with multiple sclerosis in the Black and South Asian cohorts. The magnitude and direction of these effects were broadly similar across all ethnic groups examined. There was no evidence of statistical interaction between ethnicity and any tested exposure, and no evidence to suggest that differences in area-level deprivation modifies these risk factor-disease associations. These findings were robust to a range of sensitivity analyses.
CONCLUSIONS: Established modifiable risk factors for multiple sclerosis are applicable across diverse ethnic backgrounds. Efforts to reduce the population incidence of multiple sclerosis by tackling these risk factors need to be inclusive of people from diverse ethnicities.

OBJECTIVE: Antipsychotics are first-line drug treatments for schizophrenia. When antipsychotic monotherapy is ineffective, combining two antipsychotic drugs is common although treatment guidelines warn of possible increases in side effects. Risks of metabolic side effects with antipsychotic polypharmacy have not been fully investigated. This study examined associations between antipsychotic polypharmacy and risk of developing diabetes, hypertension, or hyperlipidemia in adults with schizophrenia, and impact of co-prescription of first- and second-generation antipsychotics.
METHODS: A population-based prospective cohort study was conducted in the United Kingdom using linked primary care, secondary care, mental health, and social deprivation datasets. Cox proportional hazards models with stabilizing weights were used to estimate risk of metabolic disorders among adults with schizophrenia, comparing patients on antipsychotic monotherapy vs polypharmacy, adjusting for demographic and clinical characteristics, and antipsychotic dose.
RESULTS: Median follow-up time across the three cohorts was approximately 14 months. 6.6% developed hypertension in the cohort assembled for this outcome, with polypharmacy conferring an increased risk compared to monotherapy, (adjusted Hazard Ratio = 3.16; P = .021). Patients exposed to exclusive first-generation antipsychotic polypharmacy had greater risk of hypertension compared to those exposed to combined first- and second-generation polypharmacy (adjusted HR 0.29, P = .039). No associations between polypharmacy and risk of diabetes or hyperlipidemia were found.
CONCLUSIONS: Antipsychotic polypharmacy, particularly polypharmacy solely comprised of first-generation antipsychotics, increased the risk of hypertension. Future research employing larger samples, follow-up longer than the current median of 14 months, and more complex methodologies may further elucidate the association reported in this study.

There is considerable variation in reported chronic obstructive pulmonary disease (COPD) prevalence internationally, partly due to differing definitions in use. Accurate estimates of disease prevalence are important for allocation of health-care resources, yet UK estimates of COPD prevalence have not been updated for a decade. We calculated yearly COPD prevalence in England between 2000 and 2019 using different definitions of COPD.
We used routinely collected primary care electronic healthcare record (EHR) data from the Clinical Practice Research Datalink (CPRD) Aurum database linked with secondary care data from the Hospital Episode Statistics (HES) Admitted Patient Care (APC) database. Mid-year point prevalence was calculated yearly from 2000 to 2019 in English adults aged ≥40 years using 5 definitions: (i) validated COPD, (ii) Quality and Outcomes Framework (QOF) COPD, (iii) COPD symptoms, inhaler prescription, and no asthma diagnosis, (iv) hospitalisation with COPD as any diagnosis, (v) hospitalisation with COPD as primary or secondary diagnosis. Prevalence was further stratified by gender, age group, and region.
A total of 12,745,793 people were included over the 20-year period. Annual cohort sizes ranged from 4,373,538 in 2000 to 6,159,496 in 2019. Estimates of COPD prevalence increased every year from 2000 and the difference in estimated prevalence between the validated and QOF definitions has grown over time. In 2019, a COPD prevalence of 4.9% was found using validated events in either primary or secondary care (definition 1 or definition 5). Additionally, including potentially undiagnosed cases (definition 3) in the COPD definition produced an increased prevalence of 6.7%.
Common definitions of COPD (eg, QOF codes), may underestimate the true prevalence. The extent of this underestimate has increased over time and could lead to under-allocation of resources where need is estimated based on these definitions. Standardisation of COPD coding in routine EHRs and metrics such as spirometry is key to accurate disease monitoring.