Associations Between Midlife Anticholinergic Medication Use and Subsequent Cognitive Decline: A British Birth Cohort Study.

BACKGROUND: Anticholinergic medication use is associated with cognitive decline and incident dementia. Our study, a prospective birth cohort analysis, aimed to determine if repeated exposure to anticholinergic medications was associated with greater decline, and whether decline was reversed with medication reduction. METHODS: From the Medical Research Council (MRC) National Survey of Health and Development, a British birth cohort with all participants born in a single week of March 1946, we quantified anticholinergic exposure between ages 53 and 69 years using the Anticholinergic Cognitive Burden Scale (ACBS). We used multinomial regression to estimate associations with global cognition, quantified by the Addenbrooke's Cognitive Examination, 3rd Edition (ACE-III). Longitudinal associations between ACBS and cognitive test results (Verbal memory quantified by the Word Learning Test [WLT], and processing speed quantified by the Timed Letter Search Task [TLST]) at three time points (age 53, 60-64 and 69) were assessed using mixed and fixed effects linear regression models. Analyses were adjusted for sex, childhood cognition, education, chronic disease count and severity, and mental health symptoms. RESULTS: Anticholinergic exposure was associated cross-sectionally with lower ACE-III scores at age 69, with the greatest effects in those with high exposure at ages 60-64 (mean difference - 2.34, 95% confidence interval [CI] - 3.51 to - 1.17). Longitudinally, both mild-moderate and high ACBS scores were linked to lower WLT scores, again with high exposure showing larger effects (mean difference with contemporaneous exposure - 0.90, 95% CI - 1.63 to - 0.17; mean difference with lagged exposure - 1.53, 95% CI - 2.43 to - 0.64). Associations remained in fixed effects models (mean difference with contemporaneous exposure -1.78, 95% CI -2.85 to - 0.71; mean difference with lagged exposure - 2.23, 95% CI - 3.33 to - 1.13). Associations with TLST were noted only in isolated contemporaneous exposure (mean difference - 13.14, 95% CI - 19.04 to - 7.23; p < 0.01). CONCLUSIONS: Anticholinergic exposure throughout mid and later life was associated with lower cognitive function. Reduced processing speed was associated only with contemporaneous anticholinergic medication use, and not historical use. Associations with lower verbal recall were evident with both historical and contemporaneous use of anticholinergic medication, and associations with historical use persisted in individuals even when their anticholinergic medication use decreased over the course of the study.

Sexual and reproductive health and rights of migrant women attending primary care in England: A population-based cohort study of 1.2 million individuals of reproductive age (2009-2018).

Background: Evidence on the sexual and reproductive health and rights (SRHR) of migrants is lacking globally. We describe SRHR healthcare resource use and long-acting reversible contraceptives (LARCs) prescriptions for migrant versus non-migrant women attending primary care in England (2009-2018). Methods: This population-based observational cohort study, using Clinical Practice Research Datalink (CPRD) GOLD, included females living in England aged 15 to 49. Migration was defined using a validated codelist. Rates per 100 person years at risk (pyar) and adjusted rate ratios (RRs) were measured in migrants versus non-migrants for consultations related to all-causes, six exemplar SRHR outcomes, and LARC prescriptions. Proportions of migrants and non-migrants ever prescribed LARC were calculated. Findings: There were 25,112,116 consultations across 1,246,353 eligible individuals. 98,214 (7.9 %) individuals were migrants. All-cause consultation rates were lower in migrants versus non-migrants (509 vs 583/100pyar;RR 0.9;95 %CI 0.9-0.9), as were consultations rates for emergency contraception (RR 0.7;95 %CI 0.7-0.7) and cervical screening (RR 0.96;95 %CI 0.95-0.97). Higher rates of consultations were found in migrants for abortion (RR 1.2;95 %CI 1.1-1.2) and management of fertility problems (RR 1.39;95 %CI 1.08-1.79). No significant difference was observed for chlamydia testing and domestic violence. Of 1,205,258 individuals eligible for contraception, the proportion of non-migrants ever prescribed LARC (12.2 %;135,047/1,107,894) was almost double that of migrants (6.91 %;6,728/97,364). Higher copper intrauterine devices prescription rates were found in migrants (RR 1.53;95 %CI 1.45-1.61), whilst hormonal LARC rates were lower for migrants: levonorgestrel intrauterine device (RR 0.63;95 %CI 0.60-0.66), subdermal implant (RR 0.72;95 %CI 0.69-0.75), and progesterone-only injection (RR 0.35;95 %CI 0.34-0.36). Interpretation: Healthcare resource use differs between migrant and non-migrant women of reproductive age. Opportunities identified for tailored interventions include access to primary care, LARCs, emergency contraception and cervical screening. An inclusive approach to examining health needs is essential to actualise sexual and reproductive health as a human right.

The association between atrial fibrillation and dementia: A UK linked electronic health records cohort study.

BACKGROUND: We investigated the association between atrial fibrillation (AF) and dementia, and its subtypes (vascular-VaD, Alzheimer, mixed and rare dementia), and identified predictors for dementia in AF patients. METHODS: The analysis was based on 183,610 patients with new-onset AF and 367,220 non-AF controls in the United Kingdom between 1998 and 2016, identified in three prospectively collected, linked electronic health records sources. Time-to-event (dementia or subtypes) analyses were performed using Cox proportional hazards and weighted Cox. Sub-analyses performed: including & censoring stroke and age (median used as cut-off). RESULTS: Over a median follow-up of 2.67 years (IQR .65-6.02) for AF patients and 5.84 years for non-AF patients (IQR 2.26-11.80), incidence of dementia in the AF cohort was 2.65 per 100 person-years, compared to 2.02 in the non-AF cohort. After adjustment, a significant association was observed between AF and all-cause dementia (HR = 1.38, 95% CI: 1.31-1.45), driven by a strong association with VaD (HR = 1.55, 95% CI: 1.41-1.70). AF was also associated with mixed dementia (HR = 1.26, 95% CI: 1.01-1.56), but we could not confirm an association with Alzheimer (HR = 1.05, 95% CI: .94-1.16) and rare dementia forms (HR = 1.19, 95% CI: .90-1.56). Ischemic stroke (HR = 1.40, 95% CI: 1.26-1.56), subarachnoid haemorrhage (HR = 2.08, 95% CI: 1.47-2.96), intracerebral haemorrhage (HR = 1.95, 95% CI: 1.54-2.48) and diabetes (HR = 1.32, 95% CI: 1.24-1.41) were identified as the strongest predictors of dementia in AF patients. CONCLUSIONS: AF patients have an increased risk of dementia, independent of stroke, with highest risk of VaD. Management and prevention of the identified risk factors could be crucial to reduce the increasing burden of dementia.

Association of comorbid-socioeconomic clusters with mortality in late onset epilepsy derived through unsupervised machine learning.

BACKGROUND AND OBJECTIVES: Late-onset epilepsy is a heterogenous entity associated with specific aetiologies and an elevated risk of premature mortality. Specific multimorbid-socioeconomic profiles and their unique prognostic trajectories have not been described. We sought to determine if specific clusters of late onset epilepsy exist, and whether they have unique hazards of premature mortality. METHODS: We performed a retrospective observational cohort study linking primary and hospital-based UK electronic health records with vital statistics data (covering years 1998-2019) to identify all cases of incident late onset epilepsy (from people aged ≥65) and 1:10 age, sex, and GP practice-matched controls. We applied hierarchical agglomerative clustering using common aetiologies identified at baseline to define multimorbid-socioeconomic profiles, compare hazards of early mortality, and tabulating causes of death stratified by cluster. RESULTS: From 1,032,129 people aged ≥65, we identified 1048 cases of late onset epilepsy who were matched to 10,259 controls. Median age at epilepsy diagnosis was 68 (interquartile range: 66-72) and 474 (45%) were female. The hazard of premature mortality related to late-onset epilepsy was higher than matched controls (hazard ratio [HR] 1.73; 95% confidence interval [95%CI] 1.51-1.99). Ten unique phenotypic clusters were identified, defined by 'healthy' males and females, ischaemic stroke, intracerebral haemorrhage (ICH), ICH and alcohol misuse, dementia and anxiety, anxiety, depression in males and females, and brain tumours. Cluster-specific hazards were often similar to that derived for late-onset epilepsy as a whole. Clusters that differed significantly from the base late-onset epilepsy hazard were 'dementia and anxiety' (HR 5.36; 95%CI 3.31-8.68), 'brain tumour' (HR 4.97; 95%CI 2.89-8.56), 'ICH and alcohol misuse' (HR 2.91; 95%CI 1.76-4.81), and 'ischaemic stroke' (HR 2.83; 95%CI 1.83-4.04). These cluster-specific risks were also elevated compared to those derived for tumours, dementia, ischaemic stroke, and ICH in the whole population. Seizure-related cause of death was uncommon and restricted to the ICH, ICH and alcohol misuse, and healthy female clusters. SIGNIFICANCE: Late-onset epilepsy is an amalgam of unique phenotypic clusters that can be quantitatively defined. Late-onset epilepsy and cluster-specific comorbid profiles have complex effects on premature mortality above and beyond the base rates attributed to epilepsy and cluster-defining comorbidities alone.

Hospital admissions linked to SARS-CoV-2 infection in children and adolescents: cohort study of 3.2 million first ascertained infections in England.

OBJECTIVE: To describe hospital admissions associated with SARS-CoV-2 infection in children and adolescents. DESIGN: Cohort study of 3.2 million first ascertained SARS-CoV-2 infections using electronic health care record data. SETTING: England, July 2020 to February 2022. PARTICIPANTS: About 12 million children and adolescents (age <18 years) who were resident in England. MAIN OUTCOME MEASURES: Ascertainment of a first SARS-CoV-2 associated hospital admissions: due to SARS-CoV-2, with SARS-CoV-2 as a contributory factor, incidental to SARS-CoV-2 infection, and hospital acquired SARS-CoV-2. RESULTS: 3 226 535 children and adolescents had a recorded first SARS-CoV-2 infection during the observation period, and 29 230 (0.9%) infections involved a SARS-CoV-2 associated hospital admission. The median length of stay was 2 (interquartile range 1-4) days) and 1710 of 29 230 (5.9%) SARS-CoV-2 associated admissions involved paediatric critical care. 70 deaths occurred in which covid-19 or paediatric inflammatory multisystem syndrome was listed as a cause, of which 55 (78.6%) were in participants with a SARS-CoV-2 associated hospital admission. SARS-CoV-2 was the cause or a contributory factor in 21 000 of 29 230 (71.8%) participants who were admitted to hospital and only 380 (1.3%) participants acquired infection as an inpatient and 7855 (26.9%) participants were admitted with incidental SARS-CoV-2 infection. Boys, younger children (<5 years), and those from ethnic minority groups or areas of high deprivation were more likely to be admitted to hospital (all P<0.001). The covid-19 vaccination programme in England has identified certain conditions as representing a higher risk of admission to hospital with SARS-CoV-2: 11 085 (37.9%) of participants admitted to hospital had evidence of such a condition, and a further 4765 (16.3%) of participants admitted to hospital had a medical or developmental health condition not included in the vaccination programme's list. CONCLUSIONS: Most SARS-CoV-2 associated hospital admissions in children and adolescents in England were due to SARS-CoV-2 or SARS-CoV-2 was a contributory factor. These results should inform future public health initiatives and research.

Independent Associations of Incident Epilepsy and Enzyme-Inducing and Non-Enzyme-Inducing Antiseizure Medications With the Development of Osteoporosis.

Importance: Both epilepsy and enzyme-inducing antiseizure medications (eiASMs) having varying reports of an association with increased risks for osteoporosis. Objective: To quantify and model the independent hazards for osteoporosis associated with incident epilepsy and eiASMS and non-eiASMs. Design, Setting, and Participants: This open cohort study covered the years 1998 to 2019, with a median (IQR) follow-up of 5 (1.7-11.1) years. Data were collected for 6275 patients enrolled in the Clinical Practice Research Datalink and from hospital electronic health records. No patients who met inclusion criteria (Clinical Practice Research Datalink-acceptable data, aged 18 years or older, follow-up after the Hospital Episode Statistics patient care linkage date of 1998, and free of osteoporosis at baseline) were excluded or declined. Exposure: Incident adult-onset epilepsy using a 5-year washout and receipt of 4 consecutive ASMs. Main Outcomes and Measures: The outcome was incident osteoporosis as determined through Cox proportional hazards or accelerated failure time models where appropriate. Incident epilepsy was treated as a time-varying covariate. Analyses controlled for age, sex, socioeconomic status, cancer, 1 or more years of corticosteroid use, body mass index, bariatric surgery, eating disorders, hyperthyroidism, inflammatory bowel disease, rheumatoid arthritis, smoking status, falls, fragility fractures, and osteoporosis screening tests. Subsequent analyses (1) excluded body mass index, which was missing in 30% of patients; (2) applied propensity score matching for receipt of an eiASM; (3) restricted analyses to only those with incident onset epilepsy; and (4) restricted analyses to patients who developed epilepsy at age 65 years or older. Analyses were performed between July 1 and October 31, 2022, and in February 2023 for revisions. Results: Of 8 095 441 adults identified, 6275 had incident adult-onset epilepsy (3220 female [51%] and 3055 male [49%]; incidence rate, 62 per 100 000 person-years) with a median (IQR) age of 56 (38-73) years. When controlling for osteoporosis risk factors, incident epilepsy was independently associated with a 41% faster time to incident osteoporosis (time ratio [TR], 0.59; 95% CI, 0.52-0.67; P < .001). Both eiASMs (TR, 0.91; 95% CI, 0.87-0.95; P < .001) and non-eiASMs (TR, 0.77; 95% CI, 0.76-0.78; P < .001) were also associated with significant increased risks independent of epilepsy, accounting for 9% and 23% faster times to development of osteoporosis, respectively. The independent associations among epilepsy, eiASMs, and non-eiASMs remained consistent in propensity score-matched analyses, cohorts restricted to adult-onset epilepsy, and cohorts restricted to late-onset epilepsy. Conclusions and Relevance: These findings suggest that epilepsy is independently associated with a clinically meaningful increase in the risk for osteoporosis, as are both eiASMs and non-eiASMs. Routine screening and prophylaxis should be considered in all people with epilepsy.

Incidence of 12 common cardiovascular diseases and subsequent mortality risk in the general population.

BACKGROUND: Incident events of cardiovascular diseases (CVDs) are heterogenous and may result in different mortality risks. Such evidence may help inform patient and physician decisions in CVD prevention and risk factor management. AIMS: This study aimed to determine the extent to which incident events of common CVD show heterogeneous associations with subsequent mortality risk in the general population. METHODS AND RESULTS: Based on England-wide linked electronic health records, we established a cohort of 1 310 518 people ≥30 years of age initially free of CVD and followed up for non-fatal events of 12 common CVD and cause-specific mortality. The 12 CVDs were considered as time-varying exposures in Cox's proportional hazards models to estimate hazard rate ratios (HRRs) with 95% confidence intervals (CIs). Over the median follow-up of 4.2 years (2010-16), 81 516 non-fatal CVD, 10 906 cardiovascular deaths, and 40 843 non-cardiovascular deaths occurred. All 12 CVDs were associated with increased risk of cardiovascular mortality, with HRR (95% CI) ranging from 1.67 (1.47-1.89) for stable angina to 7.85 (6.62-9.31) for haemorrhagic stroke. All 12 CVDs were also associated with increased non-cardiovascular and all-cause mortality risk but to a lesser extent: HRR (95% CI) ranged from 1.10 (1.00-1.22) to 4.55 (4.03-5.13) and from 1.24 (1.13-1.35) to 4.92 (4.44-5.46) for transient ischaemic attack and sudden cardiac arrest, respectively. CONCLUSION: Incident events of 12 common CVD show significant adverse and markedly differential associations with subsequent cardiovascular, non-cardiovascular, and all-cause mortality risk in the general population.

We linked data available for 1.31 million people seen by English general practitioners in 2010 with data from hospital admissions and death certificates up to 2016 to investigate the risk of death in people who suffered from any of 12 common cardiovascular diseases (CVDs) compared with those who did not. The results show heterogeneously increased risks of death in people who suffered from any of 12 common CVD when compared with people who remained CVD free. The results support efforts of prevention for the entire spectrum of CVD including alleged minor types such as stable angina and transient ischaemic attack.

Identifying and visualising multimorbidity and comorbidity patterns in patients in the English National Health Service: a population-based study.

BACKGROUND: Globally, there is a paucity of multimorbidity and comorbidity data, especially for minority ethnic groups and younger people. We estimated the frequency of common disease combinations and identified non-random disease associations for all ages in a multiethnic population. METHODS: In this population-based study, we examined multimorbidity and comorbidity patterns stratified by ethnicity or race, sex, and age for 308 health conditions using electronic health records from individuals included on the Clinical Practice Research Datalink linked with the Hospital Episode Statistics admitted patient care dataset in England. We included individuals who were older than 1 year and who had been registered for at least 1 year in a participating general practice during the study period (between April 1, 2010, and March 31, 2015). We identified the most common combinations of conditions and comorbidities for index conditions. We defined comorbidity as the accumulation of additional conditions to an index condition over an individual's lifetime. We used network analysis to identify conditions that co-occurred more often than expected by chance. We developed online interactive tools to explore multimorbidity and comorbidity patterns overall and by subgroup based on ethnicity, sex, and age. FINDINGS: We collected data for 3 872 451 eligible patients, of whom 1 955 700 (50·5%) were women and girls, 1 916 751 (49·5%) were men and boys, 2 666 234 (68·9%) were White, 155 435 (4·0%) were south Asian, and 98 815 (2·6%) were Black. We found that a higher proportion of boys aged 1-9 years (132 506 [47·8%] of 277 158) had two or more diagnosed conditions than did girls in the same age group (106 982 [40·3%] of 265 179), but more women and girls were diagnosed with multimorbidity than were boys aged 10 years and older and men (1 361 232 [80·5%] of 1 690 521 vs 1 161 308 [70·8%] of 1 639 593). White individuals (2 097 536 [78·7%] of 2 666 234) were more likely to be diagnosed with two or more conditions than were Black (59 339 [60·1%] of 98 815) or south Asian individuals (93 617 [60·2%] of 155 435). Depression commonly co-occurred with anxiety, migraine, obesity, atopic conditions, deafness, soft-tissue disorders, and gastrointestinal disorders across all subgroups. Heart failure often co-occurred with hypertension, atrial fibrillation, osteoarthritis, stable angina, myocardial infarction, chronic kidney disease, type 2 diabetes, and chronic obstructive pulmonary disease. Spinal fractures were most strongly non-randomly associated with malignancy in Black individuals, but with osteoporosis in White individuals. Hypertension was most strongly associated with kidney disorders in those aged 20-29 years, but with dyslipidaemia, obesity, and type 2 diabetes in individuals aged 40 years and older. Breast cancer was associated with different comorbidities in individuals from different ethnic groups. Asthma was associated with different comorbidities between males and females. Bipolar disorder was associated with different comorbidities in younger age groups compared with older age groups. INTERPRETATION: Our findings and interactive online tools are a resource for: patients and their clinicians, to prevent and detect comorbid conditions; research funders and policy makers, to redesign service provision, training priorities, and guideline development; and biomedical researchers and manufacturers of medicines, to provide leads for research into common or sequential pathways of disease and inform the design of clinical trials. FUNDING: UK Research and Innovation, Medical Research Council, National Institute for Health and Care Research, Department of Health and Social Care, Wellcome Trust, British Heart Foundation, and The Alan Turing Institute.

Translating and evaluating historic phenotyping algorithms using SNOMED CT.

OBJECTIVE: Patient phenotype definitions based on terminologies are required for the computational use of electronic health records. Within UK primary care research databases, such definitions have typically been represented as flat lists of Read terms, but Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT) (a widely employed international reference terminology) enables the use of relationships between concepts, which could facilitate the phenotyping process. We implemented SNOMED CT-based phenotyping approaches and investigated their performance in the CPRD Aurum primary care database. MATERIALS AND METHODS: We developed SNOMED CT phenotype definitions for 3 exemplar diseases: diabetes mellitus, asthma, and heart failure, using 3 methods: "primary" (primary concept and its descendants), "extended" (primary concept, descendants, and additional relations), and "value set" (based on text searches of term descriptions). We also derived SNOMED CT codelists in a semiautomated manner for 276 disease phenotypes used in a study of health across the lifecourse. Cohorts selected using each codelist were compared to "gold standard" manually curated Read codelists in a sample of 500 000 patients from CPRD Aurum. RESULTS: SNOMED CT codelists selected a similar set of patients to Read, with F1 scores exceeding 0.93, and age and sex distributions were similar. The "value set" and "extended" codelists had slightly greater recall but lower precision than "primary" codelists. We were able to represent 257 of the 276 phenotypes by a single concept hierarchy, and for 135 phenotypes, the F1 score was greater than 0.9. CONCLUSIONS: SNOMED CT provides an efficient way to define disease phenotypes, resulting in similar patient populations to manually curated codelists.

Identifying adverse childhood experiences with electronic health records of linked mothers and children in England: a multistage development and validation study.

BACKGROUND: Electronic health records (EHRs) of mothers and children provide an opportunity to identify adverse childhood experiences (ACEs) during crucial periods of childhood development, yet well developed indicators of ACEs remain scarce. We aimed to develop clinically relevant indicators of ACEs for linked EHRs of mothers and children using a multistage prediction model of child maltreatment and maternal intimate partner violence (IPV). METHODS: In this multistage development and validation study, we developed a representative population-based birth cohort of mothers and children in England, followed from up to 2 years before birth to up to 5 years after birth across the Clinical Practice Research Datalink (CPRD) GOLD (primary care), Hospital Episode Statistics (secondary care), and the Office for National Statistics mortality register. We included livebirths in England between July 1, 2004, and June 30, 2016, to mothers aged 16-55 years, who had registered with a general practitioner (GP) that met CPRD quality standards before 21 weeks of gestation. The primary outcome (reference standard) was any child maltreatment or maternal IPV in either the mother's or child's record from 2 years before birth (maternal IPV only) to 5 years after birth. We used seven prediction models, combined with expert ratings, to systematically develop indicators. We validated the final indicators by integrating results from machine learning models, survival analyses, and clustering analyses in the validation cohort. FINDINGS: We included data collected between July 1, 2002, and June 27, 2018. Of 376 006 eligible births, we included 211 393 mother-child pairs (422 786 patients) from 400 practices, of whom 126 837 mother-child pairs (60·0%; 240 practices) were randomly assigned to a derivation cohort and 84 556 pairs (40·0%; 160 practices) to a validation cohort. We included 63 indicators in six ACE domains: maternal mental health problems, maternal substance misuse, adverse family environments, child maltreatment, maternal IPV, and high-risk presentations of child maltreatment. Excluding the seven indicators in the reference standard, 56 indicators showed high discriminative validity for the reference standard of any child maltreatment or maternal IPV between 2 years before and 5 years after birth (validation cohort, area under the receiver operating characteristic curve 0·85 [95% CI 0·84-0·86]). During the 2 years before birth and 5 years after birth, the overall period prevalence of maternal IPV and child maltreatment (reference standard) was 2·3% (2876 of 126 837 pairs) in the derivation cohort and 2·3% (1916 of 84 556 pairs) in the validation cohort. During the 2 years before and after birth, the period prevalence was 39·1% (95% CI 38·7-39·5; 34 773 pairs) for any of the 63 ACE indicators, 22·2% (21·8-22·5%; 20 122 pairs) for maternal mental health problems, 15·7% (15·4-16·0%; 14 549 pairs) for adverse family environments, 8·1% (7·8-8·3%; 6808 pairs) for high-risk presentations of child maltreatment, 6·9% (6·7-7·2%; 7856 pairs) for maternal substance misuse, and 3·0% (2·9-3·2%; 2540 pairs) for any child maltreatment (2·4% [2·3-5·6%; 2051 pairs]) and maternal IPV (1·0% [0·8-1·0%; 875 pairs]). 62·6% (21 785 of 34 773 pairs) of ACEs were recorded in primary care only, and 72·3% (25 140 cases) were recorded in the maternal record only. INTERPRETATION: We developed clinically relevant indicators for identifying ACEs using the EHRs of mothers and children presenting to general practices and hospital admissions. Over 70% of ACEs were identified via maternal records and were recorded in primary care by GPs within 2 years of birth, reinforcing the importance of reviewing parental and carer records to inform clinical responses to children. ACE indicators can contribute to longitudinal surveillance informing public health policy and resource allocation. Further evaluation is required to determine how ACE indicators can be used in clinical practice. FUNDING: None.

Linkage of National Congenital Heart Disease Audit data to hospital, critical care and mortality national data sets to enable research focused on quality improvement.

OBJECTIVES: To link five national data sets (three registries, two administrative) and create longitudinal healthcare trajectories for patients with congenital heart disease (CHD), describing the quality and the summary statistics of the linked data set. DESIGN: Bespoke linkage of record-level patient identifiers across five national data sets. Generation of spells of care defined as periods of time-overlapping events across the data sets. SETTING: National Congenital Heart Disease Audit (NCHDA) procedures in public (National Health Service; NHS) hospitals in England and Wales, paediatric and adult intensive care data sets (Paediatric Intensive Care Audit Network; PICANet and the Case Mix Programme from the Intensive Care National Audit & Research Centre; ICNARC-CMP), administrative hospital episodes (hospital episode statistics; HES inpatient, outpatient, accident and emergency; A&E) and mortality registry data. PARTICIPANTS: Patients with any CHD procedure recorded in NCHDA between April 2000 and March 2017 from public hospitals. PRIMARY AND SECONDARY OUTCOME MEASURES: Primary: number of linked records, number of unique patients and number of generated spells of care. Secondary: quality and completeness of linkage. RESULTS: There were 143 862 records in NCHDA relating to 96 041 unique patients. We identified 65 797 linked PICANet patient admissions, 4664 linked ICNARC-CMP admissions and over 6 million linked HES episodes of care (1.1M inpatient, 4.7M outpatient). The linked data set had 4 908 153 spells of care after quality checks, with a median (IQR) of 3.4 (1.8-6.3) spells per patient-year. Where linkage was feasible (in terms of year and centre), 95.6% surgical procedure records were linked to a corresponding HES record, 93.9% paediatric (cardiac) surgery procedure records to a corresponding PICANet admission and 76.8% adult surgery procedure records to a corresponding ICNARC-CMP record. CONCLUSIONS: We successfully linked four national data sets to the core data set of all CHD procedures performed between 2000 and 2017. This will enable a much richer analysis of longitudinal patient journeys and outcomes. We hope that our detailed description of the linkage process will be useful to others looking to link national data sets to address important research priorities.

Cardiovascular outcomes associated with treatment of type 2 diabetes in patients with ischaemic heart failure.

AIM: The optimal strategy for diabetes control in patients with heart failure (HF) following myocardial infarction (MI) remains unknown. Metformin, a guideline-recommended therapy for patients with chronic HF and type 2 diabetes mellitus (T2DM), is associated with reduced mortality and HF hospitalizations. However, worse outcomes have been reported when used at the time of MI. We compared outcomes of patients with T2DM and HF of ischaemic aetiology according to antidiabetic treatment. METHODS AND RESULTS: This study used linked data from primary care, hospital admissions, and death registries for 4.7 million inhabitants in England, as part of the CALIBER resource. The primary endpoint was a composite of cardiovascular mortality and HF hospitalization. The secondary endpoints were the individual components of the primary endpoint and all-cause mortality. To evaluate the effect of temporal changes in diabetes treatment, antidiabetic medication was included as time-dependent covariates in survival analyses. The study included 1172 patients with T2DM and prior MI and incident HF between 3 January 1998 and 26 February 2010. Five hundred and ninety-six patients had the primary outcome over median follow-up of 2.53 (IQR: 0.98-4.92) years. Adjusted analyses showed a reduced hazard of the composite endpoint for exposure to all antidiabetic medication with hazard ratios (HRs) of 0.50 [95% confidence interval (CI): 0.42-0.59], 0.66 (95% CI: 0.55-0.80), and 0.53 (95% CI: 0.43-0.65), respectively. A similar effect was seen for all-cause mortality [HRs of 0.43 (95% CI: 0.35-0.52), 0.57 (95% CI: 0.46-0.70), and 0.34 (95% CI: 0.27-0.43), respectively]. CONCLUSIONS: When considering changes in antidiabetic treatment over time, all drug classes were associated with reduced risk of cardiovascular mortality and HF hospitalization.

Risk of cancer following primary care presentation with fatigue: a population-based cohort study of a quarter of a million patients.

BACKGROUND: The management of adults presenting with fatigue presents a diagnostic challenge, particularly regarding possible underlying cancer. METHODS: Using electronic health records, we examined cancer risk in patients presenting to primary care with new-onset fatigue in England during 2007-2013, compared to general population estimates. We examined variation by age, sex, deprivation, and time following presentation. FINDINGS: Of 250,606 patients presenting with fatigue, 12-month cancer risk exceeded 3% in men aged 65 and over and women aged 80 and over, and 6% in men aged 80 and over. Nearly half (47%) of cancers were diagnosed within 3 months from first fatigue presentation. Site-specific cancer risk was higher than the general population for most cancers studied, with greatest relative increases for leukaemia, pancreatic and brain cancers. CONCLUSIONS: In older patients, new-onset fatigue is associated with cancer risk exceeding current thresholds for urgent specialist referral. Future research should consider how risk is modified by the presence or absence of other signs and symptoms. Excess cancer risk wanes rapidly after 3 months, which could inform the duration of a 'safety-netting' period. Fatigue presentation is not strongly predictive of any single cancer, although certain cancers are over-represented; this knowledge can help prioritise diagnostic strategies.

Development and Validation of a Primary Care Electronic Health Record Phenotype to Study Migration and Health in the UK.

International migrants comprised 14% of the UK's population in 2020; however, their health is rarely studied at a population level using primary care electronic health records due to difficulties in their identification. We developed a migration phenotype using country of birth, visa status, non-English main/first language and non-UK-origin codes and applied it to the Clinical Practice Research Datalink (CPRD) GOLD database of 16,071,111 primary care patients between 1997 and 2018. We compared the completeness and representativeness of the identified migrant population to Office for National Statistics (ONS) country-of-birth and 2011 census data by year, age, sex, geographic region of birth and ethnicity. Between 1997 to 2018, 403,768 migrants (2.51% of the CPRD GOLD population) were identified: 178,749 (1.11%) had foreign-country-of-birth or visa -status codes, 216,731 (1.35%) non-English-main/first-language codes, and 8288 (0.05%) non-UK-origin codes. The cohort was similarly distributed versus ONS data by sex and region of birth. Migration recording improved over time and younger migrants were better represented than those aged ≥50. The validated phenotype identified a large migrant cohort for use in migration health research in CPRD GOLD to inform healthcare policy and practice. The under-recording of migration status in earlier years and older ages necessitates cautious interpretation of future studies in these groups.

Association of Enzyme-Inducing Antiseizure Drug Use With Long-term Cardiovascular Disease.

Importance: Enzyme-inducing antiseizure medications (eiASMs) have been hypothesized to be associated with long-term risks of cardiovascular disease. Objective: To quantify and model the putative hazard of cardiovascular disease secondary to eiASM use. Design, Setting, and Participants: This cohort study covered January 1990 to March 2019 (median [IQR] follow-up, 9 [4-15], years). The study linked primary care and hospital electronic health records at National Health Service hospitals in England. People aged 18 years or older diagnosed as having epilepsy after January 1, 1990, were included. All eligible patients were included with a waiver of consent. No patients were approached who withdrew consent. Analysis began January 2021 and ended August 2021. Exposures: Receipt of 4 consecutive eiASMs (carbamazepine, eslicarbazepine, oxcarbazepine, phenobarbital, phenytoin, primidone, rufinamide, or topiramate) following an adult-onset (age ≥18 years) epilepsy diagnosis or repeated exposure in a weighted cumulative exposure model. Main Outcomes and Measures: Three cohorts were isolated, 1 of which comprised all adults meeting a case definition for epilepsy diagnosed after 1990, 1 comprised incident cases diagnosed after 1998 (hospital linkage date), and 1 was limited to adults diagnosed with epilepsy at 65 years or older. Outcome was incident cardiovascular disease (ischemic heart disease or ischemic or hemorrhagic stroke). Hazard of incident cardiovascular disease was evaluated using adjusted propensity-matched survival analyses and weighted cumulative exposure models. Results: Of 10 916 166 adults, 50 888 (0.6%) were identified as having period-prevalent cases (median [IQR] age, 32 [19-50] years; 16 584 [53%] female), of whom 31 479 (62%) were diagnosed on or after 1990 and were free of cardiovascular disease at baseline. In a propensity-matched Cox proportional hazards model adjusted for age, sex, baseline socioeconomic status, and cardiovascular risk factors, the hazard ratio for incident cardiovascular disease was 1.21 (95% CI, 1.06-1.39) for those receiving eiASMs. The absolute difference in cumulative hazard diverges by more than 1% and greater after 10 years. For those with persistent exposure beyond 4 prescriptions, the median hazard ratio increased from amedian (IQR) of 1.54 (1.28-1.79) when taking a relative defined daily dose of an eiASM of 1 to 2.38 (1.52-3.56) with a relative defined daily dose of 2 throughout a maximum of 25 years' follow-up compared with those not receiving an eiASM. The hazard was elevated but attenuated when restricting analyses to incident cases or those diagnosed when older than 65 years. Conclusions and Relevance: The hazard of incident cardiovascular disease is higher in those receiving eiASMs. The association is dose dependent and the absolute difference in hazard seems to reach clinical significance by approximately 10 years from first exposure.

Identifying symptoms associated with diagnosis of pancreatic exocrine and neuroendocrine neoplasms: a nested case-control study of the UK primary care population.

BACKGROUND: Pancreatic cancer has the worst survival rate among all cancers. Almost 70% of patients in the UK were diagnosed at Stage IV. AIM: This study aimed to investigate the symptoms associated with the diagnoses of pancreatic ductal adenocarcinoma (PDAC) and pancreatic neuroendocrine neoplasms (PNEN), and comparatively characterise the symptomatology between the two tumour types to inform earlier diagnosis. DESIGN AND SETTING: A nested case-control study in primary care was conducted using data from the QResearch® database. Patients aged ≥25 years and diagnosed with PDAC or PNEN during 2000 to 2019 were included as cases. Up to 10 controls from the same general practice were matched with each case by age, sex, and calendar year using incidence density sampling. METHOD: Conditional logistic regression was used to investigate the association between the 42 shortlisted symptoms and the diagnoses of PDAC and (or) PNEN in different timeframes relative to the index date, adjusting for patients' sociodemographic characteristics, lifestyle, and relevant comorbidities. RESULTS: A total of 23 640 patients were identified as diagnosed with PDAC and 596 with PNEN. Of the symptoms identified, 23 were significantly associated with PDAC, and nine symptoms with PNEN. The two alarm symptoms for both tumours were jaundice and gastrointestinal bleeding. The two newly identified symptoms for PDAC were thirst and dark urine. The risk of unintentional weight loss may be longer than 2 years before the diagnosis of PNEN. CONCLUSION: PDAC and PNEN have overlapping symptom profiles. The QCancer® (pancreas) risk prediction model could be updated by including the newly identified symptoms and comorbidities, which could help GPs identify high-risk patients for timely investigation in primary care.

Identifying counties at risk of high overdose mortality burden during the emerging fentanyl epidemic in the USA: a predictive statistical modelling study.

BACKGROUND: The emergence of fentanyl around 2013 represented a new, deadly stage of the opioid epidemic in the USA. We aimed to develop a statistical regression approach to identify counties at the highest risk of high overdose mortality in the subsequent years by predicting annual county-level overdose death rates across the contiguous USA and to validate our approach against observed overdose mortality data collected between 2013 and 2018. METHODS: We fit mixed-effects negative binomial regression models to predict overdose death rates in the subsequent year for 2013-18 for all contiguous state counties in the USA (ie, excluding Alaska and Hawaii). We used publicly available county-level data related to health-care access, drug markets, socio-demographics, and the geographical spread of opioid overdose as model predictors. The crude number of county-level overdose deaths was extracted from restricted US Centers for Disease Control and Prevention mortality records. To predict county-level overdose rates for the year 201X: (1) a model was trained on county-level predictor data for the years 2010-201(X-2) paired with county-level overdose deaths for the year 2011-201(X-1); (2) county-level predictor data for the year 201(X-1) was fed into the model to predict the 201X county-level crude number of overdose deaths; and (3) the latter were converted to a population-adjusted rate. For comparison, we generated a benchmark set of predictions by applying the observed slope of change in overdose death rates in the previous year to 201(X-1) rates. To assess the predictive performance of the model, we compared predicted values (of both the model and benchmark) to observed values by (1) calculating the mean average error, root mean squared error, and Spearman's correlation coefficient and (2) assessing the proportion of counties in the top decile (10%) of overdose death rates that were correctly predicted as such. Finally, in a post-hoc analysis, we sought to identify variables with greatest predictive utility. FINDINGS: Between 2013 and 2018, among the 3106 US counties included, our modelling approach outperformed the benchmark strategy across all metrics. The observed average county-level overdose death rate rose from 11·8 per 100 000 people in 2013 to 15·4 in 2017 before falling to 14·6 in 2018. Our negative binomal modelling approach similarly identified an increasing trend, predicting an average 11·8 deaths per 100 000 in 2013, up to 15·1 in 2017, and increasing further to 16·4 in 2018. The benchmark model over-predicted average death rates each year, ranging from 13·0 per 100 000 in 2013 to 18·3 in 2018. Our modelling approach successfully ranked counties by overdose death rate identifying between 42% and 57% of counties in the top decile of overdose mortality (compared with 29% and 43% using the benchmark) each year and identified 194 of the 808 counties with emergent overdose outbreaks (ie, newly entered the top decile) across the study period, versus 31 using the benchmark. In the post-hoc analysis, we identified geospatial proximity of overdose in nearby counties, opioid prescription rate, presence of an urgent care facility, and several economic indicators as the variables with the greatest predictive utility. INTERPRETATION: Our model shows that a regression approach can effectively predict county-level overdose death rates and serve as a risk assessment tool to identify future high mortality counties throughout an emerging drug use epidemic. FUNDING: National Institute on Drug Abuse.

Risk factors for dementia development, frailty, and mortality in older adults with epilepsy - A population-based analysis.

OBJECTIVE: Although the prevalence of comorbid epilepsy and dementia is expected to increase, the impact is not well understood. Our objectives were to examine risk factors associated with incident dementia and the impact of frailty and dementia on mortality in older adults with epilepsy. METHODS: The CALIBER scientific platform was used. People with incident epilepsy at or after age 65 were identified using Read codes and matched by age, sex, and general practitioner to a cohort without epilepsy (10:1). Baseline cohort characteristics were compared using conditional logistic regression models. Multivariate Cox proportional hazard regression models were used to examine the impact of frailty and dementia on mortality, and to assess risk factors for dementia development. RESULTS: One thousand forty eight older adults with incident epilepsy were identified. The odds of having dementia at baseline were 7.39 [95% CI 5.21-10.50] times higher in older adults with epilepsy (n = 62, 5.92%) compared to older adults without epilepsy (n = 88, 0.86%). In the final multivariate Cox model (n = 326), age [HR: 1.20, 95% CI 1.09-1.32], Charlson comorbidity index score [HR: 1.26, 95% CI 1.10-1.44], and sleep disturbances [HR: 2.41, 95% CI 1.07-5.43] at baseline epilepsy diagnosis were significantly associated with an increased hazard of dementia development over the follow-up period. In a multivariate Cox model (n = 1047), age [HR: 1.07, 95% CI 1.03-1.11], baseline dementia [HR: 2.66, 95% CI 1.65-4.27] and baseline e-frailty index score [HR: 11.55, 95% CI 2.09-63.84] were significantly associated with a higher hazard of death among those with epilepsy. Female sex [HR: 0.77, 95% CI 0.59-0.99] was associated with a lower hazard of death. SIGNIFICANCE: The odds of having dementia were higher in older adults with incident epilepsy. A higher comorbidity burden acts as a risk factor for dementia, while prevalent dementia and increasing frailty were associated with mortality.

Data-driven identification of ageing-related diseases from electronic health records.

Reducing the burden of late-life morbidity requires an understanding of the mechanisms of ageing-related diseases (ARDs), defined as diseases that accumulate with increasing age. This has been hampered by the lack of formal criteria to identify ARDs. Here, we present a framework to identify ARDs using two complementary methods consisting of unsupervised machine learning and actuarial techniques, which we applied to electronic health records (EHRs) from 3,009,048 individuals in England using primary care data from the Clinical Practice Research Datalink (CPRD) linked to the Hospital Episode Statistics admitted patient care dataset between 1 April 2010 and 31 March 2015 (mean age 49.7 years (s.d. 18.6), 51% female, 70% white ethnicity). We grouped 278 high-burden diseases into nine main clusters according to their patterns of disease onset, using a hierarchical agglomerative clustering algorithm. Four of these clusters, encompassing 207 diseases spanning diverse organ systems and clinical specialties, had rates of disease onset that clearly increased with chronological age. However, the ages of onset for these four clusters were strikingly different, with median age of onset 82 years (IQR 82-83) for Cluster 1, 77 years (IQR 75-77) for Cluster 2, 69 years (IQR 66-71) for Cluster 3 and 57 years (IQR 54-59) for Cluster 4. Fitting to ageing-related actuarial models confirmed that the vast majority of these 207 diseases had a high probability of being ageing-related. Cardiovascular diseases and cancers were highly represented, while benign neoplastic, skin and psychiatric conditions were largely absent from the four ageing-related clusters. Our framework identifies and clusters ARDs and can form the basis for fundamental and translational research into ageing pathways.

Predictive value of indicators for identifying child maltreatment and intimate partner violence in coded electronic health records: a systematic review and meta-analysis.

OBJECTIVE: Electronic health records (EHRs) are routinely used to identify family violence, yet reliable evidence of their validity remains limited. We conducted a systematic review and meta-analysis to evaluate the positive predictive values (PPVs) of coded indicators in EHRs for identifying intimate partner violence (IPV) and child maltreatment (CM), including prenatal neglect. METHODS: We searched 18 electronic databases between January 1980 and May 2020 for studies comparing any coded indicator of IPV or CM including prenatal neglect defined as neonatal abstinence syndrome (NAS) or fetal alcohol syndrome (FAS), against an independent reference standard. We pooled PPVs for each indicator using random effects meta-analyses. RESULTS: We included 88 studies (3 875 183 individuals) involving 15 indicators for identifying CM in the prenatal period and childhood (0-18 years) and five indicators for IPV among women of reproductive age (12-50 years). Based on the International Classification of Disease system, the pooled PPV was over 80% for NAS (16 studies) but lower for FAS (<40%; seven studies). For young children, primary diagnoses of CM, specific injury presentations (eg, rib fractures and retinal haemorrhages) and assaults showed a high PPV for CM (pooled PPVs: 55.9%-87.8%). Indicators of IPV in women had a high PPV, with primary diagnoses correctly identifying IPV in >85% of cases. CONCLUSIONS: Coded indicators in EHRs have a high likelihood of correctly classifying types of CM and IPV across the life course, providing a useful tool for assessment, support and monitoring of high-risk groups in health services and research.