Antiplatelet therapy with aspirin, clopidogrel, and dipyridamole versus clopidogrel alone or aspirin and dipyridamole in patients with acute cerebral ischaemia (TARDIS): a randomised, open-label, phase 3 superiority trial

Background: Intensive antiplatelet therapy with three agents might be more effective than guideline treatment for preventing recurrent events in patients with acute cerebral ischaemia. We aimed to compare the safety and efficacy of intensive antiplatelet therapy (combined aspirin, clopidogrel, and dipyridamole) with that of guideline-based antiplatelet therapy. Methods: We did an international, prospective, randomised, open-label, blinded-endpoint trial in adult participants with ischaemic stroke or transient ischaemic attack (TIA) within 48 h of onset. Participants were assigned in a 1:1 ratio using computer randomisation to receive loading doses and then 30 days of intensive antiplatelet therapy (combined aspirin 75 mg, clopidogrel 75 mg, and dipyridamole 200 mg twice daily) or guideline-based therapy (comprising either clopidogrel alone or combined aspirin and dipyridamole). Randomisation was stratified by country and index event, and minimised with prognostic baseline factors, medication use, time to randomisation, stroke-related factors, and thrombolysis. The ordinal primary outcome was the combined incidence and severity of any recurrent stroke (ischaemic or haemorrhagic; assessed using the modified Rankin Scale) or TIA within 90 days, as assessed by central telephone follow-up with masking to treatment assignment, and analysed by intention to treat. This trial is registered with the ISRCTN registry, number ISRCTN47823388. Findings: 3096 participants (1556 in the intensive antiplatelet therapy group, 1540 in the guideline antiplatelet therapy group) were recruited from 106 hospitals in four countries between April 7, 2009, and March 18, 2016. The trial was stopped early on the recommendation of the data monitoring committee. The incidence and severity of recurrent stroke or TIA did not differ between intensive and guideline therapy (93 [6%] participants vs 105 [7%]; adjusted common odds ratio [cOR] 0·90, 95% CI 0·67–1·20, p=0·47). By contrast, intensive antiplatelet therapy was associated with more, and more severe, bleeding (adjusted cOR 2·54, 95% CI 2·05–3·16, p<0·0001). Interpretation: Among patients with recent cerebral ischaemia, intensive antiplatelet therapy did not reduce the incidence and severity of recurrent stroke or TIA, but did significantly increase the risk of major bleeding. Triple antiplatelet therapy should not be used in routine clinical practice

AI-based derivation of atrial fibrillation phenotypes in the general and critical care populations

Background Atrial fibrillation (AF) is the most common heart arrhythmia worldwide and is linked to a higher risk of mortality and morbidity. To predict AF and AF-related complications, clinical risk scores are commonly employed, but their predictive accuracy is generally limited, given the inherent complexity and heterogeneity of patients with AF. By classifying different presentations of AF into coherent and manageable clinical phenotypes, the development of tailored prevention and treatment strategies can be facilitated. In this study, we propose an artificial intelligence (AI)-based methodology to derive meaningful clinical phenotypes of AF in the general and critical care populations. Methods Our approach employs generative topographic mapping, a probabilistic machine learning method, to identify micro-clusters of patients with similar characteristics. It then identifies macro-cluster regions (clinical phenotypes) in the latent space using Ward’s minimum variance method. We applied it to two large cohort databases (UK-Biobank and MIMIC-IV) representing general and critical care populations. Findings The proposed methodology showed its ability to derive meaningful clinical phenotypes of AF. Because of its probabilistic foundations, it can enhance the robustness of patient stratification. It also produced interpretable visualisation of complex high-dimensional data, enhancing understanding of the derived phenotypes and their key characteristics. Using our methodology, we identified and characterised clinical phenotypes of AF across diverse patient populations. Interpretation Our methodology is robust to noise, can uncover hidden patterns and subgroups, and can elucidate more specific patient profiles, contributing to more robust patient stratification, which could facilitate the tailoring of prevention and treatment programs specific to each phenotype. It can also be applied to other datasets to derive clinically meaningful phenotypes of other conditions

Closing the attainment gap in Scottish schools:Three challenges in an unequal society

Scotland’s First Minister Nicola Sturgeon has recently said, ‘Improving school attainment is arguably the single most important objective in this programme for Government (Parliamentary address, 1 September 2015). Scotland’s levels of academic attainment have become an increasing focus for debate amid continuing concerns that children living in the most deprived areas in Scotland are ‘6 to 13 months behind their peers in problem-solving at age 5; 11 to 18 months behind their peers in expressive vocabulary at age 5; and around two years of schooling behind their peers at age 15’ (Scottish Government, 2014a: 5). The link between educational disadvantage and low levels of attainment is well documented in many countries, but particularly troubling in the UK, where overall levels of inequality are greater than in many other OECD countries, including Sweden. This paper draws on recent research in three fields of interest, namely student participation, home-school relationships and relationships within school, to explore the challenges for education in improving overall attainment. It considers how these fields of interest connect with each other and with issues of inequality and, finally, argues that they each has the potential to offer a new set of ‘guidewires’ for tackling this challenge

Reasons for non-recruitment of eligible patients to a randomised controlled trial of secondary prevention after intracerebral haemorrhage: observational study.

Recruitment to randomised prevention trials is challenging, not least for intracerebral haemorrhage (ICH) associated with antithrombotic drug use. We investigated reasons for not recruiting apparently eligible patients at hospital sites that keep screening logs in the ongoing REstart or STop Antithrombotics Randomised Trial (RESTART), which seeks to determine whether to start antiplatelet drugs after ICH.EDGE project number 14013British Heart Foundation Special Project (SP/12/2/29422) & Project (PG/14/50/30891) fundin

Effect of repurposed simvastatin on disability progression in secondary progressive multiple sclerosis (MS-STAT2): a phase 3, randomised, double-blind, placebo-controlled trial

Background Despite the success of immune modulation in the treatment of relapsing multiple sclerosis, disability progression is a major problem driven by multiple mechanisms. Comorbidities (eg, vascular risk) and ageing are thought to augment these neurodegenerative pathologies. In the phase 2b MS-STAT trial of simvastatin (80 mg) versus placebo in secondary progressive multiple sclerosis (SPMS), the adjusted difference in brain atrophy rate between groups was −0·254% per year: a 43% reduction. In this phase 3 MS-STAT2 trial, we aimed to assess the efficacy of simvastatin versus placebo in slowing the progression of disability in SPMS. Methods This phase 3, randomised, double-blind, parallel group, placebo-controlled clinical trial was conducted at 31 neuroscience centres and district general hospitals in the UK. Participants aged 18–65 years with a diagnosis of SPMS and an Expanded Disability Status Scale (EDSS) of between 4·0 and 6·5 were eligible and randomly assigned (1:1) to oral simvastatin (80 mg) or matched placebo for up to 4·5 years, based on a minimisation algorithm within an independent and secure online randomisation service. All participants, site investigators, and the trial coordinating team were masked to treatment allocation. The primary outcome was time to 6-month EDSS confirmed disability progression (an increase of at least 1 point if EDSS score at baseline visit was less than 6·0 or an increase of 0·5 point if EDSS score at baseline visit was 6·0 or more) assessed in all randomly assigned participants (intention-to-treat analysis) without imputation. This study is registered with ClinicalTrials.gov (NCT03387670) and is on the ISRCTN registry (ISRCTN82598726). The study is completed. Findings Between May 10, 2018, and July 26, 2024, 1079 patients were screened for eligibility and 964 participants were randomly assigned, with 482 (50%) in the placebo group and 482 (50%) in the simvastatin group. Of all 964 participants, 704 (73%) were female and 260 (27%) were male, with a mean age of 54 years (SD 7). 173 (36%) of 482 participants in the placebo group and 192 (40%) of 482 participants in the simvastatin group had 6-month confirmed disability progression (adjusted hazard ratio 1·13 [95% CI 0·91 to 1·39], p=0·26). Although no emergent safety issues were seen, there was one serious adverse reaction (rhabdomyolysis) in the simvastatin group. 12 (2%) of 482 participants in the placebo group and five (1%) of 482 participants in the simvastatin group had a cardiovascular serious adverse event. Interpretation The MS-STAT2 trial did not show a treatment effect of simvastatin in slowing disability progression in SPMS. Simvastatin use in multiple sclerosis should be confined to existing vascular indications. Funding National Institute for Health and Care Research Health Technology Assessment Programme, UK Multiple Sclerosis Society, and the US National Multiple Sclerosis Society

Prehospital transdermal glyceryl trinitrate in patients with ultra-acute presumed stroke (RIGHT-2): an ambulance-based, randomised, sham-controlled, blinded, phase 3 trial

Background High blood pressure is common in acute stroke and is a predictor of poor outcome; however, large trials of lowering blood pressure have given variable results, and the management of high blood pressure in ultra-acute stroke remains unclear. We investigated whether transdermal glyceryl trinitrate (GTN; also known as nitroglycerin), a nitric oxide donor, might improve outcome when administered very early after stroke onset. Methods We did a multicentre, paramedic-delivered, ambulance-based, prospective, randomised, sham-controlled, blinded-endpoint, phase 3 trial in adults with presumed stroke within 4 h of onset, face-arm-speech-time score of 2 or 3, and systolic blood pressure 120 mm Hg or higher. Participants were randomly assigned (1:1) to receive transdermal GTN (5 mg once daily for 4 days; the GTN group) or a similar sham dressing (the sham group) in UK based ambulances by paramedics, with treatment continued in hospital. Paramedics were unmasked to treatment, whereas participants were masked. The primary outcome was the 7-level modified Rankin Scale (mRS; a measure of functional outcome) at 90 days, assessed by central telephone follow-up with masking to treatment. Analysis was hierarchical, first in participants with a confirmed stroke or transient ischaemic attack (cohort 1), and then in all participants who were randomly assigned (intention to treat, cohort 2) according to the statistical analysis plan. This trial is registered with ISRCTN, number ISRCTN26986053. Findings Between Oct 22, 2015, and May 23, 2018, 516 paramedics from eight UK ambulance services recruited 1149 participants (n=568 in the GTN group, n=581 in the sham group). The median time to randomisation was 71 min (IQR 45–116). 597 (52%) patients had ischaemic stroke, 145 (13%) had intracerebral haemorrhage, 109 (9%) had transient ischaemic attack, and 297 (26%) had a non-stroke mimic at the final diagnosis of the index event. In the GTN group, participants’ systolic blood pressure was lowered by 5·8 mm Hg compared with the sham group (p<0·0001), and diastolic blood pressure was lowered by 2·6 mm Hg (p=0·0026) at hospital admission. We found no difference in mRS between the groups in participants with a final diagnosis of stroke or transient ischaemic stroke (cohort 1): 3 (IQR 2–5; n=420) in the GTN group versus 3 (2–5; n=408) in the sham group, adjusted common odds ratio for poor outcome 1·25 (95% CI 0·97–1·60; p=0·083); we also found no difference in mRS between all patients (cohort 2: 3 [2–5]; n=544, in the GTN group vs 3 [2–5]; n=558, in the sham group; 1·04 [0·84–1·29]; p=0·69). We found no difference in secondary outcomes, death (treatment-related deaths: 36 in the GTN group vs 23 in the sham group [p=0·091]), or serious adverse events (188 in the GTN group vs 170 in the sham group [p=0·16]) between treatment groups. Interpretation Prehospital treatment with transdermal GTN does not seem to improve functional outcome in patients with presumed stroke. It is feasible for UK paramedics to obtain consent and treat patients with stroke in the ultraacute prehospital setting. Funding British Heart Foundation

Effects of fluoxetine on functional outcomes after acute stroke (FOCUS): a pragmatic, double-blind, randomised, controlled trial

Background Results of small trials indicate that fluoxetine might improve functional outcomes after stroke. The FOCUS trial aimed to provide a precise estimate of these effects. Methods FOCUS was a pragmatic, multicentre, parallel group, double-blind, randomised, placebo-controlled trial done at 103 hospitals in the UK. Patients were eligible if they were aged 18 years or older, had a clinical stroke diagnosis, were enrolled and randomly assigned between 2 days and 15 days after onset, and had focal neurological deficits. Patients were randomly allocated fluoxetine 20 mg or matching placebo orally once daily for 6 months via a web-based system by use of a minimisation algorithm. The primary outcome was functional status, measured with the modified Rankin Scale (mRS), at 6 months. Patients, carers, health-care staff, and the trial team were masked to treatment allocation. Functional status was assessed at 6 months and 12 months after randomisation. Patients were analysed according to their treatment allocation. This trial is registered with the ISRCTN registry, number ISRCTN83290762. Findings Between Sept 10, 2012, and March 31, 2017, 3127 patients were recruited. 1564 patients were allocated fluoxetine and 1563 allocated placebo. mRS data at 6 months were available for 1553 (99·3%) patients in each treatment group. The distribution across mRS categories at 6 months was similar in the fluoxetine and placebo groups (common odds ratio adjusted for minimisation variables 0·951 [95% CI 0·839–1·079]; p=0·439). Patients allocated fluoxetine were less likely than those allocated placebo to develop new depression by 6 months (210 [13·43%] patients vs 269 [17·21%]; difference 3·78% [95% CI 1·26–6·30]; p=0·0033), but they had more bone fractures (45 [2·88%] vs 23 [1·47%]; difference 1·41% [95% CI 0·38–2·43]; p=0·0070). There were no significant differences in any other event at 6 or 12 months. Interpretation Fluoxetine 20 mg given daily for 6 months after acute stroke does not seem to improve functional outcomes. Although the treatment reduced the occurrence of depression, it increased the frequency of bone fractures. These results do not support the routine use of fluoxetine either for the prevention of post-stroke depression or to promote recovery of function. Funding UK Stroke Association and NIHR Health Technology Assessment Programme

Antiplatelet therapy with aspirin, clopidogrel, and dipyridamole versus clopidogrel alone or aspirin and dipyridamole in patients with acute cerebral ischaemia (TARDIS): a randomised, open-label, phase 3 superiority trial

Background: Intensive antiplatelet therapy with three agents might be more effective than guideline treatment for preventing recurrent events in patients with acute cerebral ischaemia. We aimed to compare the safety and efficacy of intensive antiplatelet therapy (combined aspirin, clopidogrel, and dipyridamole) with that of guideline-based antiplatelet therapy.Methods: We did an international, prospective, randomised, open-label, blinded-endpoint trial in adult participants with ischaemic stroke or transient ischaemic attack (TIA) within 48 h of onset. Participants were assigned in a 1:1 ratio using computer randomisation to receive loading doses and then 30 days of intensive antiplatelet therapy (combined aspirin 75 mg, clopidogrel 75 mg, and dipyridamole 200 mg twice daily) or guideline-based therapy (comprising either clopidogrel alone or combined aspirin and dipyridamole). Randomisation was stratified by country and index event, and minimised with prognostic baseline factors, medication use, time to randomisation, stroke-related factors, and thrombolysis. The ordinal primary outcome was the combined incidence and severity of any recurrent stroke (ischaemic or haemorrhagic; assessed using the modified Rankin Scale) or TIA within 90 days, as assessed by central telephone follow-up with masking to treatment assignment, and analysed by intention to treat. This trial is registered with the ISRCTN registry, number ISRCTN47823388.Findings: 3096 participants (1556 in the intensive antiplatelet therapy group, 1540 in the guideline antiplatelet therapy group) were recruited from 106 hospitals in four countries between April 7, 2009, and March 18, 2016. The trial was stopped early on the recommendation of the data monitoring committee. The incidence and severity of recurrent stroke or TIA did not differ between intensive and guideline therapy (93 [6%] participants vs 105 [7%]; adjusted common odds ratio [cOR] 0·90, 95% CI 0·67–1·20, p=0·47). By contrast, intensive antiplatelet therapy was associated with more, and more severe, bleeding (adjusted cOR 2·54, 95% CI 2·05–3·16,

Development of Machine Learning Models with Applications in Cardiovascular Research

Cardiovascular disease (CVD) is one of the leading burdens on modern healthcare globally in terms of mortality, loss of health and healthcare costs. CVD covers all conditions that affect the heart and circulatory systems. Artificial intelligence (AI) and machine learning (ML) are being increasingly leveraged to help improve diagnosis, prognosis, treatment, and management of CVDs. This thesis aims to develop ML approaches that can generate novel, meaningful insights into several aspects of cardiovascular research. First, in Chapter 3 we use convolutional neural networks (CNN) to quantify the effect ECG data format has on ML predictive performance, through the clinical task of detecting myocardial infarction, providing the first results in determining the optimal ECG data format for ML modelling. The remaining analysis leverages the unsupervised, probabilistic ML technique generative topographic mapping (GTM). The analysis aims to generate 2-dimensional representations of data and propose different approaches that can identify large macro-clusters within the reduced dimension. Doing this gives an understanding of which patients/participants within a data set are clinically similar, along with interpretable visualisations that explain the rationale behind each cluster. Chapter 4 contains the first outline of this methodology, developed on a noncardiovascular dataset, to demonstrate the generalisability of such a methodology. Through this approach, we propose a novel freedom of expression index that provides an understanding of the level of restrictions placed on the population of a country. This index is defined by macro clusters generated through aggregating the normalised information contained in the GTM reference vector outputs. Chapter 5 applies this methodology to generate clinically relevant AF phenotypes for specific patient cohorts, from the general and the critical care populations. We propose a new methodological approach to achieve this that implements hierarchical clustering, again on the GTM reference vector outputs, to generate the phenotypes. Finally, Chapters 6 and 7 investigate the athlete’s heart, defined as the physiological changes that the heart undergoes due to exercising for prolonged periods. Chapter 6 contains an in-depth scoping review, evaluating the current ML applications in athlete’s heart and identifying the gaps for future research. Chapter 7 investigates features automatically extracted from ECG recordings from elite footballers, cyclists, rugby league players, and ultra runners to further the understanding of healthy athlete’s hearts. The methodology in Chapter 5 was further developed here to define a novel approach that uses magnification factors to define neighbourhoods in the 2-dimensional data representation, to carry out constrained hierarchical clustering on the reference vectors