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Objective Methods Results Significance The incidence of late‐onset epilepsy (LOE) is rising, and these patients may use an excess of health care resources. This study aimed to measure pre‐/post‐diagnostic health care use (HCU) for patients with LOE compared to controls.This was an observational open cohort study covering years 1998–2019 using UK population‐based linked primary care (Clinical Practice Research Datalink [CPRD]) and hospital (HES) electronic health records. The participants included patients with incident LOE enrolled in CPRD and 1:10 age‐, sex‐, and general practice–matched controls. The exposure was incident LOE (diagnosed at age ≥65) using a 5‐year washout. The main outcome was all HCU (primary care [PC], accident and emergency [A&E], admitted patient and outpatient care) using inverse proportional weighting to PC use and HCU by setting. An interrupted time‐series analysis was used to examine pre‐/post‐diagnostic HCU between patients with LOE and controls over 4 years either side of diagnosis/matching date. An adjusted mixed‐effects negative binomial regression was used for post‐diagnosis HCU interactions.Of 2 569 874 people ≥65 years of age, 1048 (4%) developed incident LOE. Mean weighted total HCU increased by 32 visits per patient‐year (95% confidence interval [95% CI]: 13–50, p = .003) until LOE diagnosis, and then dropped by a mean of 60 visits per patient‐year (95% CI: −81 to −40). There was an acute rise and fall over the 1–2 years immediately pre‐/post‐diagnosis. Incident HCU remained higher for LOE compared to controls post‐diagnosis (adjusted incidence rate ratio: 1.72; 95% CI: 1.65–1.70; p < .001), including A&E, outpatient, and admitted care.Health care use demonstrates an acute on chronic rise over the 4 years before diagnosis of LOE. To what extent the partial reversal of the acute pre‐diagnosis rise, and the mediators of the accelerated increase compared to controls are attributed to epilepsy, comorbid and bidirectional disease states, or a combination of both warrants further exploration. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background Hospitalisation for adversity-related injury (violent, drug/alcohol-related, or self-inflicted injury) has been described as a 'teachable moment', when intervention may reduce risks of further harm. Which adolescents are likely to benefit most from intervention strongly depends on their long-term risks of harm. We compared 10-y risks of mortality and readmission after adversity-related injury with risks after accident-related injury. Methods and Findings We analysed National Health Service admissions data for England (1 April 1997-31 March 2012) for 10-19 y olds with emergency admissions for adversity-related injury (violent, drug/alcohol-related, or self-inflicted injury; n = 333,009) or for accident-related injury (n = 649,818). We used Kaplan-Meier estimates and Cox regression to estimate and compare 10-y post-discharge risks of death and emergency re-admission. Among adolescents discharged after adversity-related injury, one in 137 girls and one in 64 boys died within 10 y, and 54.2% of girls and 40.5% of boys had an emergency re-admission, with rates being highest for 18-19 y olds. Risks of death were higher than in adolescents discharged after accident-related injury (girls: age-adjusted hazard ratio 1.61,95% CI 1.43-1.82; boys: 2.13, 95% CI 1.98-2.29), as were risks of re-admission (girls: 1.76, 95% CI 1.74-1.79; boys: 1.41,95% C11.39-1.43). Risks of death and re-admission were increased after all combinations of violent, drug/alcohol-related, and self-inflicted injury, but particularly after any drug/ alcohol-related or self-inflicted injury (i.e., with/without violent injury), for which age-adjusted hazard ratios for death in boys ranged from 1.67 to 5.35, compared with 1.25 following violent injury alone (girls: 1.09 to 3.25, compared with 1.27). The main limitation of the study was under-recording of adversity-related injuries and misclassification of these cases as accident-related injuries. This misclassification would attenuate the relative risks of death and re-admission for adversity-related compared with accident-related injury. Conclusions Adolescents discharged after an admission for violent, drug/alcohol-related, or self-inflicted injury have increased risks of subsequent harm up to a decade later. Introduction of preventive strategies for reducing subsequent harm after admission should be considered for all types of adversity-related injury, particularly for older adolescents., Introduction Adolescents (10-19 y olds) are a vulnerable population [1]. Community surveys of adolescents in high-income countries have estimated that up to 50%-60% are exposed to violence, drug/ alcohol misuse, [...]