Three-dimensional (3D) mesh reconstruction of the cardiac anatomy from medical images is useful for shape and motion measurements and biophysics simulations. However, 3D medical images are often acquired as 2D slices that are sparsely sampled (e.g., large slice spacing) and noisy, and 3D mesh reconstruction on such data is a challenging task. Traditional voxel-based approaches utilize non-differentiable pre- and post-processing that compromises fidelity to images, while mesh-level deep learning approaches require large 3D mesh annotations that are difficult to obtain. Differentiable cross-domain supervision from 2D images to 3D meshes is therefore crucial for enabling end-to-end optimization in medical imaging. While there have been attempts to approximate the voxelization and slicing of meshes that are being optimized, there has not yet been a method for directly using 2D slices to supervise 3D mesh reconstruction in a differentiable manner. Here, we propose a novel explicit differentiable voxelization and slicing (DVS) algorithm allowing gradient backpropagation to a 3D mesh from its slices, which facilitates refined mesh optimization directly supervised by the losses defined on 2D images. Further, we propose an innovative framework for extracting patient-specific left ventricle (LV) meshes from medical images by coupling DVS with a graph harmonic deformation (GHD) mesh morphing descriptor of cardiac shape that naturally preserves mesh quality and smoothness during optimization. The proposed framework achieves state-of-the-art performance in cardiac mesh reconstruction tasks from densely sampled (CT) as well as sparsely sampled (MRI stack with few slices) images, outperforming alternatives, including Marching Cubes, statistical shape models, algorithms with vertex-based mesh morphing algorithms and alternative methods for image-supervision of mesh reconstruction. Experimental results demonstrate that our method achieves an overall Dice score of 90% during a sparse fitting on multi-datasets. The proposed method can further quantify clinically useful parameters such as ejection fraction and global myocardial strains, closely matching the ground truth and outperforming the traditional voxel-based approach in sparse images.

Background The Scottish Computed Tomography of the Heart (SCOT-HEART) trial demonstrated that management guided by coronary CT angiography (CCTA) improved the diagnosis, management, and outcome of patients with stable chest pain. We aimed to assess whether CCTA-guided care results in sustained long-term improvements in management and outcomes. Methods SCOT-HEART was an open-label, multicentre, parallel group trial for which patients were recruited from 12 outpatient cardiology chest pain clinics across Scotland. Eligible patients were aged 18-75 years with symptoms of suspected stable angina due to coronary heart disease. Patients were randomly assigned (1:1) to standard of care plus CCTA or standard of care alone. In this prespecified 10-year analysis, prescribing data, coronary procedural interventions, and clinical outcomes were obtained through record linkage from national registries. The primary outcome was coronary heart disease death or non-fatal myocardial infarction on an intention-to-treat basis. This trial is registered at ClinicalTrials.gov (NCT01149590) and is complete. Findings Between Nov 18, 2010, and Sept 24, 2014, 4146 patients were recruited (mean age 57 years [SD 10], 2325 [561%] male, 1821 [439%] female), with 2073 randomly assigned to standard care and CCTA and 2073 to standard care alone. After a median of 100 years (IQR 93-110), coronary heart disease death or non-fatal myocardial infarction was less frequent in the CCTA group compared with the standard care group (137 [66%] vs 171 [82%]; hazard ratio [HR] 079 [95% CI 063-099], p=0044). Rates of all-cause, cardiovascular, and coronary heart disease death, and non-fatal stroke, were similar between the groups (p>005 for all), but non-fatal myocardial infarctions (90 [43%] vs 124 [60%]; HR 072 [055-094], p=0017) and major adverse cardiovascular events (172 [83%] vs 214 [103%]; HR 080 [065-097], p=0026) were less frequent in the CCTA group. Rates of coronary revascularisation procedures were similar (315 [152%] vs 318 [153%]; HR 100 [086-117], p=099) but preventive therapy prescribing remained more frequent in the CCTA group (831 [559%] of 1486 vs 728 [490%] of 1485 patients with available data; odds ratio 117 [95% CI 101-136], p=0034). Interpretation After 10 years, CCTA-guided management of patients with stable chest pain was associated with a sustained reduction in coronary heart disease death or non-fatal myocardial infarction. Identification of coronary atherosclerosis by CCTA improves long-term cardiovascular disease prevention in patients with stable chest pain. Copyright (c) 2025 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.

BACKGROUND:Well-organised electronic health records (EHR) are essential for high quality patient care, but EHR user interfaces can be cumbersome for entry of structured information, resulting in the majority of information being in free text rather than a structured form. This makes it difficult to retrieve information for clinical purposes and limits the research potential of the data. Natural language processing (NLP) at the point of care has been suggested as a way of improving data quality and completeness, but there is little evidence as to its effectiveness. We sought to generate such evidence by developing an open source, modular, configurable NLP system called MiADE, which is designed to integrate with an EHR. This paper describes the design of MiADE and the deployment at University College London Hospitals (UCLH), and is intended to benefit those who may wish to develop or implement a similar system elsewhere. RESULTS:The MiADE system includes components to extract diagnoses, medications and allergies from a clinical note, and communicate with an EHR system in real time using Health Level 7 Clinical Document Architecture (HL7 CDA) messaging. This enables NLP results to be displayed to a clinician for verification before saving them to the patient's record. MiADE utilises the MedCAT library (part of the Cogstack family of NLP tools) for named entity recognition (NER) and linking to SNOMED CT, as well as context detection. MedCAT models underwent unsupervised and supervised training on patient notes from UCLH, achieving precision of 83.2% (95% CI 77.0, 88.1), and recall of 85.2% (95% CI 79.1, 89.8) for detection of diagnosis concepts. In simulation testing we found that MiADE reduced the time taken for clinicians to enter structured problem lists by 89%. We have commenced a trial implementation of MiADE at UCLH in live clinical use, integrated with the Epic EHR at UCLH. CONCLUSIONS:We have developed an open source point of care NLP system and successfully integrated it with the EHR in live clinical use at a major hospital. Simulation testing has shown that our system significantly reduces the time taken for clinicians to enter structured diagnosis codes.

Accurate and reproducible phenotyping is essential for large-scale biomedical research. However, developing robust phenotype definitions in biobanks is challenging due to diverse data sources and varying medical ontologies. As a result, the current phenotyping landscape is fragmented. We developed a computational framework to harmonize electronic health record (EHR) data, participant questionnaires, and clinical registry information, defining 313 disease phenotypes among 502,356 UK Biobank (UKB) participants. Our method integrated four medical ontologies (Read v2, CTV3, ICD-10, OPCS-4) across seven data sources, including primary care, hospital admissions, cancer and death registries, and self-reported data on diseases, procedures, and medication. Phenotypes underwent multi-layered validation, assessing data source concordance, age-sex incidence and prevalence patterns, external comparison to a representative UK EHR dataset, modifiable risk factor associations, and genetic correlations with external genome-wide association studies (GWAS). Results indicated consistent disease distributions by age and sex, high correlation with non-selected general population data prevalence estimates, confirmed risk factor associations, and significant genetic correlations with external GWAS for nine of ten evaluated diseases. Our approach establishes comprehensive disease validation profiles, improving phenotype generalizability despite inherent UKB demographic biases. The modular, reproducible framework can be extended to additional diseases and populations, supporting federated analyses across diverse biobanks, and facilitating research in underrepresented populations.

NLM reports research grants awarded to the University of Edinburgh from Abbott Diagnostics, Siemens Healthineers and Roche Diagnostics outside the submitted work and honoraria from Abbott Diagnostics, Siemens Healthineers, Roche Diagnostics, LumiraDx, and Psyros Diagnostics. The other authors declare no conflicts of interest. Figure S1. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Introduction There is uncertainty about the effectiveness of oral fluid restriction in patients with acute heart failure treated with intravenous loop diuretics, due to a lack of high-quality evidence from randomised controlled trials (RCTs). RCTs of non-pharmacological therapies are challenging and costly to undertake in the acute setting using conventional approaches. We sought to investigate the feasibility of conducting a pragmatic RCT that was integrated into the electronic health record (EHR), in the setting of acute unplanned care. Our primary aim was to determine the feasibility of using an automated, interruptive alert to invite clinicians to enrol patients into an RCT of fluid restriction in patients presenting with fluid overload. Methods THIRST Alert was a single-centre parallel group, open-label, randomised controlled trial conducted to pilot a novel and efficient approach to trial conduct in a hospital setting. Patient screening, recruitment, randomisation, and outcome ascertainment were all conducted through the EHR and routine care processes. A proportionate model of verbal opt-out consent was used. Over a 6-month period, clinicians who prescribed more than one dose of intravenous furosemide within 48 hours of an unplanned patient admission were exposed to an alert which invited them to assess whether their patient was suitable for inclusion into the trial. Patients <18 and those admitted to the care of surgical or maternity teams were excluded. Enrolled patients underwent simple 1:1 randomisation by the EHR, and were allocated to either oral fluid restriction of 1L/ day or no oral fluid restriction. The co-primary outcome measures were the number of patients enrolled and the documented difference in oral fluid intake between the intervention and control group in the 48 hours after randomised allocation. The trial did not involve any additional investigator input or patient follow-up. Results Between 3 May 2023 and 1 November 2023, a total of 1,191 alerts were triggered. 23 of 141 eligible patients (16%) were enrolled on the trial by routine care clinicians (table 1). In 21 of 23 patients (91%), there was evidence of adherence to the randomised treatment allocation: a clinical order concordant with the randomised allocation was recorded in the health record in 12/12 patients allocated to fluid restriction arm and 9/11 patients allocated to no restriction (figure 1). For 19/23 (83%) of the patients enrolled in the study, heart failure was included in the hospital episode statistics for the admission. In the intention to treat (ITT) analysis, the documented oral intake of the restricted group was 1170 ml (930–1620 ml IQR) and 650 ml (75–1100 ml IQR) in the unrestricted group. The mean number of documented entries for the primary outcome measure of fluid intake was 6.6 for the restricted group and 4.9 for the unrestricted group. Conclusions To our knowledge, the THIRST Alert trial is one of the first pragmatic RCTs delivered entirely through the electronic health record system and without the direct intervention of a research team. Our study demonstrates the feasibility of conducting low-cost and efficient trials during the routine care process to generate evidence that can inform practice and improve patient outcomes. Paradoxically, we observed a higher documented fluid intake in the fluid restriction group which may indicate differences in measurement and documentation in patients with active treatments. Further studies are required to determine whether oral fluid restriction is an effective adjunct to diuretic treatment in this setting or if it is a low-value intervention that contributes to care complexity and patient thirst without clinical benefit. Trial registration: NCT05869656. Funded by NIHR UCLH Biomedical Research Centre. Conflict of Interest None

Abstract Background A raised stress hyperglycaemia ratio (SHR) has been associated with all-cause mortality and may better discriminate than an absolute glucose value. The aim of this meta analysis and systematic review is to synthesise the evidence assessing the relationship between the SHR and all-cause mortality across three common cardiovascular presentations. Methods We undertook a comprehensive search of Medline, Embase, Cochrane CENTRAL and Web of Science from the date of inception to 1st March 2024, and selected articles meeting the following criteria: studies of patients hospitalised for acute myocardial infarction, ischaemic stroke or acute heart failure reporting the risk (odds ratio or hazard ratio) for all-cause mortality associated with the SHR. A random effects model was used for primary analysis. Subgroup analysis by diabetes status and of mortality in the short and long term was undertaken. Risk of bias assessment was performed using the Newcastle Ottawa quality assessment scale. Results A total of 32 studies were included: 26 studies provided 31 estimates for the meta-analysis. The total study population in the meta analysis was 80,010. Six further studies were included in the systematic review. Participants admitted to hospital with cardiovascular disease and an SHR in the highest category had a significantly higher risk ratio of all-cause mortality in both the short and longer term compared with those with a lower SHR (RR = 1.67 [95% CI 1.46–1.91], p < 0.001). This finding was driven by studies in the myocardial infarction (RR = 1.75 [95% CI 1.52–2.01]), and ischaemic stroke cohorts (RR = 1.78 [95% CI 1.26–2.50]). The relationship was present amongst those with and without diabetes (diabetes: RR 1.49 [95% CI 1.14–1.94], p < 0.001, no diabetes: RR 1.85 [95% CI 1.49–2.30], p < 0.001) with p = 0.21 for subgroup differences, and amongst studies that reported mortality as a single outcome (RR of 1.51 ([95% CI 1.29–1.77]; p < 0.001) and those that reported mortality as part of a composite outcome (RR 2.02 [95% CI 1.58–2.59]; p < 0.001). On subgroup analysis by length of follow up, higher SHR values were associated with increased risk of mortality at 90 day, 1 year and > 1year follow up, with risk ratios of 1.84 ([95% CI 1.32–2.56], p < 0.001), 1.69 ([95% CI 1.32–2.16], p < 0.001) and 1.58 ([95% CI 1.34–1.86], p < 0.001) respectively. Conclusions A raised SHR is associated with an increased risk of all-cause mortality following myocardial infarction and ischaemic stroke. Further work is required to define reference values for the SHR, and to investigate the potential effects of relative hypoglycaemia. Interventional trials targeting to the SHR rather than the absolute glucose value should be undertaken. PROSPERO database registration CRD 42023456421 https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023456421

Background:Electronic health records (EHRs) have the potential to be used to produce detailed disease burden estimates. In this study we created disease estimates using national EHR for three high burden conditions, compared estimates between linked and unlinked datasets and produced stratified estimates by age, sex, ethnicity, socio-economic deprivation and geographical region. Methods:EHRs containing primary care (Clinical Practice Research Datalink), secondary care (Hospital Episode Statistics) and mortality records (Office for National Statistics) were used. We used existing disease phenotyping algorithms to identify cases of cancer (breast, lung, colorectal and prostate), type 1 and 2 diabetes, and lower back pain. We calculated age-standardised incidence of first cancer, point prevalence for diabetes, and primary care consultation prevalence for low back pain. Results:7.2 million people contributing 45.3 million person-years of active follow-up between 2000-2014 were included. CPRD-HES combined and CPRD-HES-ONS combined lung and bowel cancer incidence estimates by sex were similar to cancer registry estimates. Linked CPRD-HES estimates for combined Type 1 and Type 2 diabetes were consistently higher than those of CPRD alone, with the difference steadily increasing over time from 0.26% (2.99% for CPRD-HES vs. 2.73 for CPRD) in 2002 to 0.58% (6.17% vs. 5.59) in 2013. Low back pain prevalence was highest in the most deprived quintile and when compared to the least deprived quintile the difference in prevalence increased over time between 2000 and 2013, with the largest difference of 27% (558.70 per 10,000 people vs 438.20) in 2013. Conclusions:We use national EHRs to produce estimates of burden of disease to produce detailed estimates by deprivation, ethnicity and geographical region. National EHRs have the potential to improve disease burden estimates at a local and global level and may serve as more automated, timely and precise inputs for policy making and global burden of disease estimation.

Objective: The burden of hypertension in rural sub-Saharan Africa (SSA) has been on the rise. In rural SSA, screening, diagnosis and treatment monitoring for hypertension is typically through attended office blood pressure (OBP) conducted by a trained health worker. A community-centered approach where community health workers (CHWs) conduct out-of-office blood pressure (BP) measurements at the homes of community members may increase the proportion of patients diagnosed early and improve monitoring during treatment. However, the diagnostic performance of these BP measurements when conducted by CHWs remains unclear. Design and method: We are conducting a cross-sectional study to determine the diagnostic performance of OBP performed by CHWs in identifying individuals with hypertension in rural Kenya and The Gambia. A random age-stratified random sample of 1250 participants aged 30 years and above from the Kilifi Health and Demographic Surveillance System and the Kiang West Demographic Surveillance System are being enrolled into the study. Participants undergo randomly assigned attended and unattended OBP measurement and 24-hour ambulatory BP monitoring (reference standard) conducted by trained CHWs at their homes. Results: Recruitment is ongoing. We have enrolled and completed BP measurements for 166 participants, all from the Kenya study site (13% of the total sample). Of these, 114 (69%) are female with an average age of 57 years (standard deviation 15 years). Based on ambulatory BP, 71 (43%) of included participants are hypertensive. The preliminary sensitivity of attended and unattended OBP is 0.50 (0.38, 0.62) and 0.47 (0.35, 0.59) respectively with both measurement methods having a high specificity of 0.93 (0.85, 0.97). The diagnostic odds ratio (DOR) for attended OBP (DOR 13.6; likelihood ratio (LR) positive 7.33 (3.26, 16.47)) is higher than that of unattended OBP (DOR 12.1; LR positive 6.89 (3.05, 15.54)). Diagnostic performance does not appear to differ by age or sex. Further analyses will be conducted when recruitment is complete. Conclusions: Attended OBP appears to have better diagnostic performance than unattended OBP when conducted at participants’ homes by CHWs, but the sensitivity of both methods for detecting hypertension is low.

Abstract Background Heart failure (HF) with preserved or mildly reduced ejection fraction includes a heterogenous group of patients. Reclassification into distinct phenogroups to enable targeted interventions is a priority. This study aimed to identify distinct phenogroups, and compare phenogroup characteristics and outcomes, from electronic health record data. Methods 2,187 patients admitted to five UK hospitals with a diagnosis of HF and a left ventricular ejection fraction ≥ 40% were identified from the NIHR Health Informatics Collaborative database. Partition-based, model-based, and density-based machine learning clustering techniques were applied. Cox Proportional Hazards and Fine-Gray competing risks models were used to compare outcomes (all-cause mortality and hospitalisation for HF) across phenogroups. Results Three phenogroups were identified: (1) Younger, predominantly female patients with high prevalence of cardiometabolic and coronary disease; (2) More frail patients, with higher rates of lung disease and atrial fibrillation; (3) Patients characterised by systemic inflammation and high rates of diabetes and renal dysfunction. Survival profiles were distinct, with an increasing risk of all-cause mortality from phenogroups 1 to 3 (p < 0.001). Phenogroup membership significantly improved survival prediction compared to conventional factors. Phenogroups were not predictive of hospitalisation for HF. Conclusions Applying unsupervised machine learning to routinely collected electronic health record data identified phenogroups with distinct clinical characteristics and unique survival profiles.

Background Cardiac troponin is commonly raised in patients presenting with malignancy. The prognostic significance of raised troponin in these patients is unclear. Objectives We sought to investigate the relation between troponin and mortality in a large, well characterised cohort of patients with a routinely measured troponin and a primary diagnosis of malignancy. Methods We used the National Institute for Health Research (NIHR) Health Informatics Collaborative data of 5571 patients, who had troponin levels measured at 5 UK cardiac centres between 2010 and 2017 and had a primary diagnosis of malignancy. Patients were classified into solid tumour or haematological malignancy subgroups. Peak troponin levels were standardised as a multiple of each laboratory's 99th -percentile upper limit of normal (xULN). Results 4649 patients were diagnosed with solid tumours and 922 patients with haematological malignancies. Raised troponin was an independent predictor of mortality in all patients (Troponin > 10 vs. <1 adjusted HR 2.01, 95% CI 1.73 to 2.34), in solid tumours (HR 1.84, 95% CI 1.55 to 2.19), and in haematological malignancy (HR 2.72, 95% CI 1.99 to 3.72). There was a significant trend in increasing mortality risk across troponin categories in all three subgroups (p < 0.001). Conclusion Raised troponin level is associated with increased mortality in patients with a primary diagnosis of malignancy regardless of cancer subtype. Mortality risk is stable for patients with a troponin level below the ULN but increases as troponin level increases above the ULN in the absence of acute coronary syndrome.

Background Air pollution is a significant environmental risk factor for cardiovascular diseases (CVDs), but its impact on African populations is under-researched due to limited air quality data and health studies. Objectives The purpose of this study was to synthesize available research on the effects of air pollution on CVDs outcomes in African populations, identify knowledge gaps, and suggest areas for research and policy intervention. Methods A systematic search of PubMed was conducted using terms capturing criteria ambient air pollutants (for example particulate matter, nitrogen dioxide, ozone, and sulfur dioxide) and CVDs and countries in Africa. Exclusions were studies on tobacco smoking, household air pollution, and occupational exposures. Results Six studies met the full inclusion criteria. Most studies were conducted in urban settings and most investigated on particulate matter, nitrogen dioxide and sulfur dioxide. Five of the 6 studies were performed in South Africa. The studies showed positive associations between exposure to air pollutants and increased incidence of stroke and overall cardiovascular hospitalization and mortality. However, there was considerable variation in study design, pollutant measurement methods, and adjustment for confounders. Conclusions This review highlights a critical need for standardized research on air pollution and cardiovascular health in Africa. The extremely limited numbers of studies make it difficult to ascertain the true impact of air pollution across the African continent. Future research should include longitudinal studies in different African populations with standardized methods. There is an urgent need to improve pollution monitoring networks, ascertain key sources of exposure, and implement air quality standards.

Objective: Self-home blood pressure (BP) measurement has been reported to be superior to office BP measurements (attended or unattended) in diagnosing hypertension. However, it is not readily available in rural sub-Saharan Africa (SSA) due to the cost of the measurement devices and the literacy it requires to correctly measure and record BP. Consequently, the diagnostic performance of self-home BP measurement in rural sub-Saharan Africa remains unclear. Trained community health workers (CHWs) with home BP measurement devices may improve the availability and use of these devices by providing and training community members to use them Design and method: We are conducting a cross-sectional study to determine the diagnostic performance of self-home BP measurement in identifying individuals with hypertension in rural Kenya and The Gambia. A random age-stratified random sample of 1250 participants aged 30 years and above from the Kilifi Health and Demographic Surveillance System and the Kiang West Demographic Surveillance System are being enrolled into the study. Trained CHWs avail the measurement devices to enrolled participants and train them to measure and record their BP for seven consecutive days. Primary data of BP measurements are then downloaded from the measurement devices. Additionally, participants undergo ambulatory BP monitoring (reference standard). Results: Recruitment is ongoing. We have enrolled and completed BP measurements for 154 participants, all from the Kenya study site (12% of the total sample). Of these 106 (69%) are female with an average age of 57 years (standard deviation 15 years). Based on home and ambulatory BP respectively, 49 (32%) and 66 (43%) of included participants are hypertensive. Of the included participants, 26 (17%) have masked hypertension and were not detected by home BP while 9(6%) are normotensive but considered hypertensive based on home BP. The preliminary sensitivity and specificity of self-home BP measurement is 0.61 (0.49, 0.72) and 0.90 (0.81, 0.95) respectively while its diagnostic odds ratio (DOR) is 13.5 (likelihood ratio positive 5.93 (3.10, 11.34)). Further analyses will be conducted when recruitment is complete. Conclusions: Self-home BP measurement has modest diagnostic utility in the general population in rural SSA.

Cardiac abnormalities were identified early in the epidemic of AIDS, predating the isolation and characterization of the etiologic agent, HIV. Several decades later, the causation and pathogenesis of cardiovascular disease (CVD) linked to HIV infection continue to be the focus of intense speculation. Before the widespread use of antiretroviral therapy, HIV-associated CVD was primarily characterized by HIV-associated cardiomyopathy linked to profound immunodeficiency. With increasing antiretroviral therapy use, viral load suppression, and establishment of immune competency, the effects of HIV on the cardiovascular system are more subtle. Yet, people living with HIV still face an increased incidence of cardiovascular pathology. Advances in cardiac imaging modalities and immunology have deepened our understanding of the pathogenesis of HIV-associated CVD. This review provides an overview of the pathogenesis of HIV-associated CVD integrating data from imaging and immunologic studies with particular relevance to the HIV population originating from high-endemic regions, such as sub-Saharan Africa. The review highlights key evidence gaps in the field and suggests future directions for research to better understand the complex HIV-CVD interactions.

AbstractBackgroundDespite the growing interest in the use of human genomic data for drug target identification and validation, the extent to which the spectrum of human disease has been addressed by genome-wide association studies (GWAS), or by drug development, and the degree to which these efforts overlap remain unclear.MethodsIn this study we harmonize and integrate different data sources to create a sample space of all the human drug targets and diseases and identify points of convergence or divergence of GWAS and drug development efforts.ResultsWe show that only 612 of 11,158 diseases listed in Human Disease Ontology have an approved drug treatment in at least one region of the world. Of the 1414 diseases that are the subject of preclinical or clinical phase drug development, only 666 have been investigated in GWAS. Conversely, of the 1914 human diseases that have been the subject of GWAS, 1121 have yet to be investigated in drug development.ConclusionsWe produce target-disease indication lists to help the pharmaceutical industry to prioritize future drug development efforts based on genetic evidence, academia to prioritize future GWAS for diseases without effective treatments, and both sectors to harness genetic evidence to expand the indications for licensed drugs or to identify repurposing opportunities for clinical candidates that failed in their originally intended indication.

ObjectiveThe COVID-19 pandemic was associated with a reduction in the incidence of myocardial infarction (MI) diagnosis, in part because patients were less likely to present to hospital. Whether changes in clinical decision making with respect to the investigation and management of patients with suspected MI also contributed to this phenomenon is unknown.MethodsMulticentre retrospective cohort study in three UK centres contributing data to the National Institute for Health Research Health Informatics Collaborative. Patients presenting to the Emergency Department (ED) of these centres between 1st January 2020 and 1st September 2020 were included. Three time epochs within this period were defined based on the course of the first wave of the COVID-19 pandemic: pre-pandemic (epoch 1), lockdown (epoch 2), post-lockdown (epoch 3).ResultsDuring the study period, 10,670 unique patients attended the ED with chest pain or dyspnoea, of whom 6,928 were admitted. Despite fewer total ED attendances in epoch 2, patient presentations with dyspnoea were increased (p < 0.001), with greater likelihood of troponin testing in both chest pain (p = 0.001) and dyspnoea (p < 0.001). There was a dramatic reduction in elective and emergency cardiac procedures (both p < 0.001), and greater overall mortality of patients (p < 0.001), compared to the pre-pandemic period. Positive COVID-19 and/or troponin test results were associated with increased mortality (p < 0.001), though the temporal risk profile differed.ConclusionsThe first wave of the COVID-19 pandemic was associated with significant changes not just in presentation, but also the investigation, management, and outcomes of patients presenting with suspected myocardial injury or MI.