AIMS:To conduct a contemporary cost-effectiveness analysis examining the use of implantable cardioverter defibrillators (ICDs) for primary prevention in patients with hypertrophic cardiomyopathy (HCM). METHODS:A discrete-time Markov model was used to determine the cost-effectiveness of different ICD decision-making rules for implantation. Several scenarios were investigated, including the reference scenario of implantation rates according to observed real-world practice. A 12-year time horizon with an annual cycle length was used. Transition probabilities used in the model were obtained using Bayesian analysis. The study has been reported according to the Consolidated Health Economic Evaluation Reporting Standards checklist. RESULTS:Using a 5-year SCD risk threshold of 6% was cheaper than current practice and has marginally better total quality adjusted life years (QALYs). This is the most cost-effective of the options considered, with an incremental cost-effectiveness ratio of £834 per QALY. Sensitivity analyses highlighted that this decision is largely driven by what health-related quality of life (HRQL) is attributed to ICD patients and time horizon. CONCLUSION:We present a timely new perspective on HCM-ICD cost-effectiveness, using methods reflecting real-world practice. While we have shown that a 6% 5-year SCD risk cut-off provides the best cohort stratification to aid ICD decision-making, this will also be influenced by the particular values of costs and HRQL for subgroups or at a local level. The process of explicitly demonstrating the main factors, which drive conclusions from such an analysis will help to inform shared decision-making in this complex area for all stakeholders concerned.

Introduction Acute heart failure (HF) is a major cause of unplanned hospitalisation characterised by excess body water. A restriction in oral fluid intake is commonly imposed on patients as an adjunct to pharmacological therapy with loop diuretics, but there is a lack of evidence from traditional randomised controlled trials (RCTs) to support the safety and effectiveness of this intervention in the acute setting.This study aims to explore the feasibility of using computer alerts within the electronic health record (EHR) system to invite clinical care teams to enrol patients into a pragmatic RCT at the time of clinical decision-making. It will additionally assess the effectiveness of using an alert to help address the clinical research question of whether oral fluid restriction is a safe and effective adjunct to pharmacological therapy for patients admitted with fluid overload.Methods and analysis THIRST (Randomised Controlled Trial within the electronic Health record of an Interruptive alert displaying a fluid Restriction Suggestion in patients with the treatable Trait of congestion) Alert is a single-centre, parallel-group, open-label pragmatic RCT embedded in the EHR system that will be conducted as a feasibility study at an National Health Service (NHS) hospital in London. The clinical care team will be invited to enrol suitable patients in the study using a point-of-care alert with a target sample size of 50 patients. Enrolled patients will then be randomised to either restricted or unrestricted oral fluid intake. Two primary outcomes will be explored (1) the proportion of eligible patients enrolled in the study and (2) the mean difference in oral fluid intake between randomised groups. A series of secondary outcomes are specified to evaluate the effectiveness of the alert, adherence to the randomised treatment allocation and the quality of data generated from routine care, relevant to the outcomes of interest.Ethics and dissemination This study was approved by Riverside Research Ethics Committee (Ref: 22/LO/0889) and will be published on completion.Trial registration number NCT05869656.

Background and aimOpportunities to participate in leadership and management with protected time can be limited for clinical trainees. The aim of this fellowship was to gain experience of gold standard healthcare management by becoming part of multidisciplinary teams working to deliver transformational change in the National Health Service (NHS). MethodsA 6-month pilot fellowship, structured as an Out of Programme Experience was created for two registrars to be seconded to the healthcare division of Deloitte, a leading professional services firm. Competitive selection was jointly administered by the Director of Medical Education at St Bartholomew's Hospital and Deloitte. ResultsThe successful candidates worked on service-led and digital transformation projects, interfacing with senior NHS executives and directors. Trainees gained direct experience and understanding of high-level decision making in the NHS, tackling complex service delivery problems and the practical realities of delivering change within a constrained budget. One impact of this pilot has been completion of a business case to scale up the fellowship into an established programme that can allow other trainees to apply. ConclusionThis innovative fellowship has allowed interested trainees an opportunity to broaden the relevant skills and experience in leadership and management required in specialty training curriculum with real-life application in the NHS.

Background Patient and public involvement (PPI) has growing impact on the design of clinical care and research studies. There remains underreporting of formal PPI events including views related to using digital tools. This study aimed to assess the feasibility of hosting a hybrid PPI event to gather views on the use of digital tools in clinical care and research. Methods A PPI focus day was held following local procedures and published recommendations related to advertisement, communication and delivery. Two exemplar projects were used as the basis for discussions and qualitative and quantitative data was collected. Results 32 individuals expressed interest in the PPI day and 9 were selected to attend. 3 participated in person and 6 via an online video-calling platform. Selected written and verbal feedback was collected on two digitally themed projects and on the event itself. The overall quality and interactivity for the event was rated as 4/5 for those who attended in person and 4.5/5 and 4.8/5 respectively, for those who attended remotely. Conclusions A hybrid PPI event is feasible and offers a flexible format to capture the views of patients. The overall enthusiasm for digital tools amongst patients in routine care and clinical research is high, though further work and standardised, systematic reporting of PPI events is required.

The increasing volume and richness of healthcare data collected during routine clinical practice have not yet translated into significant numbers of actionable insights that have systematically improved patient outcomes. An evidence-practice gap continues to exist in healthcare. We contest that this gap can be reduced by assessing the use of nudge theory as part of clinical decision support systems (CDSS). Deploying nudges to modify clinician behaviour and improve adherence to guideline-directed therapy represents an underused tool in bridging the evidence-practice gap. In conjunction with electronic health records (EHRs) and newer devices including artificial intelligence algorithms that are increasingly integrated within learning health systems, nudges such as CDSS alerts should be iteratively tested for all stakeholders involved in health decision-making: clinicians, researchers, and patients alike. Not only could they improve the implementation of known evidence, but the true value of nudging could lie in areas where traditional randomized controlled trials are lacking, and where clinical equipoise and variation dominate. The opportunity to test CDSS nudge alerts and their ability to standardize behaviour in the face of uncertainty may generate novel insights and improve patient outcomes in areas of clinical practice currently without a robust evidence base.

BACKGROUND:Clinical decision-making is influenced by many factors, including clinicians' perceptions of the certainty around what is the best course of action to pursue.OBJECTIVE:To characterise the documentation of working diagnoses and the associated level of real-time certainty expressed by clinicians and to gauge patient opinion about the importance of research into clinician decision certainty.METHOD:This was a single-centre retrospective cohort study of non-consultant grade clinicians and their assessments of patients admitted from the emergency department between 01 March 2019 and 31 March 2019. De-identified electronic health record proformas were extracted that included the type of diagnosis documented and the certainty adjective used. Patient opinion was canvassed from a focus group.RESULTS:During the study period, 850 clerking proformas were analysed; 420 presented a single diagnosis, while 430 presented multiple diagnoses. Of the 420 single diagnoses, 67 (16%) were documented as either a symptom or physical sign and 16 (4%) were laboratory-result-defined diagnoses. No uncertainty was expressed in 309 (74%) of the diagnoses. Of 430 multiple diagnoses, uncertainty was expressed in 346 (80%) compared to 84 (20%) in which no uncertainty was expressed. The patient focus group were unanimous in their support of this research.CONCLUSION:The documentation of working diagnoses is highly variable among non-consultant grade clinicians. In nearly three quarters of assessments with single diagnoses, no element of uncertainty was implied or quantified. More uncertainty was expressed in multiple diagnoses than single diagnoses.IMPLICATIONS:Increased standardisation of documentation will help future studies to better analyse and quantify diagnostic certainty in both single and multiple working diagnoses. This could lead to subsequent examination of their association with important process or clinical outcome measures.

Randomised controlled trials (RCTs) are the gold standard study design used to evaluate the safety and effectiveness of healthcare interventions. The reporting quality of RCTs is of fundamental importance for readers to appropriately analyse and understand the design and results of studies which are often labelled as practice changing papers. The aim of this article is to assess the reporting standards of a representative sample of randomised controlled trials (RCTs) published between 2019 and 2020 in four of the highest impact factor general medical journals. A systematic review of the electronic database Medline was conducted. Eligible RCTs included those published in the New England Journal of Medicine, Lancet, Journal of the American Medical Association, and British Medical Journal between January 1, 2019, and June 9, 2020. The study protocol was registered on medRxiv ( https://doi.org/10.1101/2020.07.06.20147074 ). Of a total eligible sample of 497 studies, 50 full-text RCTs were reviewed against the CONSORT 2010 statement and relevant extensions where necessary. The mean adherence to the CONSORT checklist was 90% (SD 9%). There were specific items on the CONSORT checklist which had recurring suboptimal adherence, including in title (item 1a, 70% adherence), randomisation (items 9 and 10, 56% and 30% adherence) and outcomes and estimation (item 17b, 62% adherence). Amongst a sample of RCTs published in four of the highest impact factor general medical journals, there was good overall adherence to the CONSORT 2010 statement. However there remains significant room for improvement in areas such as description of allocation concealment and implementation of randomisation.

Background: The international healthcare response to COVID-19 has been driven by epidemiological data related to case numbers and case fatality rate. Second order effects have been less well studied. This study aimed to characterise the changes in emergency activity of a high-volume cardiac catheterisation centre and to cautiously model any excess indirect morbidity and mortality. Method: Retrospective cohort study of patients admitted with acute coronary syndrome fulfilling criteria for the heart attack centre (HAC) pathway at St. Bartholomew's hospital, UK. Electronic data were collected for the study period March 16th - May 16th 2020 inclusive and stored on a dedicated research server. Standard governance procedures were observed in line with the British Cardiovascular Intervention Society audit. Results: There was a 28% fall in the number of primary percutaneous coronary interventions (PCIs) for ST elevation myocardial infarction (STEMI) during the study period (111 vs. 154) and 36% fewer activations of the HAC pathway (312 vs. 485), compared to the same time period averaged across three preceding years. In the context of 'missing STEMIs', the excess harm attributable to COVID-19 could result in an absolute increase of 1.3% in mortality, 1.9% in nonfatal MI and 4.5% in recurrent ischemia. Conclusions: The emergency activity of a high-volume PCI centre was significantly reduced for STEMI during the peak of the first wave of COVID-19. Our data can be used as an exemplar to help future modelling within cardiovascular workstreams to refine aggregate estimates of the impact of COVID-19 and inform targeted policy action. (C) 2021 Published by Elsevier B.V.

OBJECTIVES:The clinical environment has been forced to adapt to meet the unprecedented challenges posed by the COVID-19 pandemic. Intensive care facilities were expanded in anticipation of the pandemic where the consequences include severe delays in elective procedures. Emergent procedures such as Percutaneous Coronary Intervention (PCI) in acute myocardial infarction (AMI) in which delays in timely delivery have well established adverse prognostic effects must also be explored in the context of changes in procedure and public behaviour associated with the COVID-19 pandemic. The aim for this single centre retrospective cohort study is to determine if door-to-balloon (D2B) times in PCI for ST Elevation Myocardial Infarction (STEMI) during the United Kingdom's first wave of the COVID-19 pandemic differed from pre-COVID-19 populations.METHODS:Data was extracted from our single centre PCI database for all patients that underwent pPCI for STEMI. The reference (Pre-COVID-19) cohort was collected over the period 01-03-2019 to 31-05-2019 and the exposure group (COVID-19) over the period 01-03-2020 to 31-05-2020. Baseline patient characteristics for both populations were extracted. The primary outcome measurement was D2B times. Secondary outcome measurements included: time of symptom onset to call for help, transfer time to first hospital, transfer time from non-PCI to PCI centre, time from call-to-help to PCI centre, time to table and onset of symptoms to balloon time. Categorical and continuous variables were assessed with Chi squared and Mann-Whitney U analysis respectively. Procedural times were calculated and compared in the context of heterogeneity findings.RESULTS:4 baseline patient characteristics were unbalanced between populations with statistical significance (P<0.05). The pre-covid-19 cohort was more likely to have suffered out of hospital cardiac arrest (OHCA) and had left circumflex disease, whereas the 1st wave cohort were more likely to have been investigated with left ventriculography and be of Afro-Caribbean origin. No statistically significant difference in in-hospital procedural times was found with D2B, C2B, O2B times comparable between groups. Pre-hospital delays were the greatest contributors in missed target times: the 1st wave group had significantly longer delayed time of symptom onset to call for help (Control: 31 mins; IQR [82.5] vs 1st wave: 60 mins; IQR [90.0], P=0.001) and time taken from call for help to arrival at the PCI hospital (control: 72 mins; IQR [23] vs 1st wave: 80 mins; IQR [66.5], P=0.042).CONCLUSION:Enhanced infection prevention and control procedures considering the COVID-19 pandemic did not impede the delivery of pPCI in our single centre cohort. The public health impact of the pandemic has been demonstrated with times being significantly impacted by patient related delays. The recovery of public engagement in emergency medical services must become the focus for public health initiatives as we emerge from the height of COVID-19 disease burden in the UK.

The aim of this systematic review was to evaluate randomized clinical trials (RCTs) of cardiac catheter ablation (CCA) and to assess the prevalence, characteristics and reporting standards of clinically relevant patient-reported outcome measures (PROMs). Electronic database searches of Medline, Embase, CENTRAL, and the WHO Trial Registry were conducted in March 2019. The study protocol was registered on PROSPERO (CRD42019133086). Of 7125 records identified, 237 RCTs were included for analysis, representing 35 427 patients with a mean age of 59 years. Only 43 RCTs (18%) reported PROMs of which 27 included a generic PROM that measured health-related quality of life (HRQL) necessary to conduct comparative effectiveness research. There was notable under-representation of certain patient groups-only 31% were women and only 8% were of non-Caucasian ethnicity, in trials which reported such data. The reporting standard of PROMs was highly variable with 8-62% adherence against CONSORT PRO-specific items. In summary, PROMs play a crucial role in determining the clinical and cost-effectiveness of treatments which primarily offer symptomatic improvement, such as CCA. Their underuse significantly limits evaluation of the comparative effectiveness of treatments. Using CCA as an exemplar, there are additional issues of infrequent assessment, poor reporting and under-representation of many population groups. Greater use of PROMs, and specifically validated HRQL questionnaires, is paramount in giving patients a voice in studies, generating more meaningful comparisons between treatments and driving better patient-centred clinical and policy-level decision-making.

Hypertrophic cardiomyopathy (HCM) came to prominence in 1958 when Donald Teare described in the British Heart Journal its typical pathological features in 8 patients who died suddenly. The excessive risk of sudden cardiac death (SCD) dominated the early literature and contemporary 21st century studies suggest that the SCD rate is approximately 1% per year [ [1] Elliott P.M. Anastasakis A. Borger M.A. Borggrefe M. Cecchi F. Charron P. et al. 2014 ESC Guidelines on diagnosis and management of hypertrophic cardiomyopathy: The Task Force for the Diagnosis and Management of Hypertrophic Cardiomyopathy of the European Society of Cardiology (ESC). Eur. Heart J. 2014; 35: 2733-2779 Crossref PubMed Scopus (37) Google Scholar ]. Ventricular arrhythmias are the primary cause of SCD and the development of the implantable cardioverter defibrillator (ICD) in 1980 was a significant milestone. Since ICDs were approved for human use in 1985, the technology has improved, thoracotomy and abdominal implants have been abandoned and devices are now inserted under conscious sedation as a day case procedure. Subcutaneous ICDs represent the latest iteration of this technology and are particularly attractive as they avoid intracardiac complications [ [2] Lambiase P.D. Gold M.R. Hood M. Boersma L. Theuns D.A. Burke M.C. et al. Evaluation of subcutaneous ICD early performance in hypertrophic cardiomyopathy from the pooled EFFORTLESS and IDE cohorts. Heart Rhythm. 2016; 13: 1066-1074 Abstract Full Text Full Text PDF PubMed Scopus (74) Google Scholar ]. Health economic evaluation of implantable cardioverter defibrillators in hypertrophic cardiomyopathy in adultsInternational Journal of CardiologyVol. 311PreviewHypertrophic cardiomyopathy is a heterogeneous disease in which an implantable cardioverter defibrillator (ICD) effectively prevents sudden cardiac death in at-risk individuals. Nevertheless, the cost-effectiveness of ICDs in this specific patient group has not been evaluated. Full-Text PDF

Abstract As well as its profound effects on healthcare and wider society, the COVID-19 pandemic will have far-reaching implications for the future training and professional development of healthcare workers and, in particular, doctors. While initial educational priorities focused on creating a more agile workforce with better cross-specialty skill-mix, attention must now shift to how our system can prepare a proportionate response that not only addresses the needs of the pandemic but also the underlying challenges of healthcare: multimorbidity, bridging the evidence–practice gap and delivering integrated, personalised medicine for all. It is our contention that meeting such challenges will require a rapid upskilling of the digital capabilities of the healthcare workforce. In short, optimising the health of the nation will depend, in part, on improving the digital health of the workforce. In this review, we examine how digital technology played its part in the COVID-19 response, and how fundamental changes to medical training are urgently needed in the context of a ‘healthcare reset’. Familiarity with health informatics, data science and digital technology have to move to centre stage in order to future-proof our profession in the years to come. The people that deliver care are our systems’ greatest asset, and at a time when change is accelerating, we cannot knowingly allow current and future colleagues to be ill-equipped to survive and thrive in the practice of medicine.

Background In July 2020, the National Health Service (NHS) People Plan was refreshed, giving further impetus to staff development and leadership training. Through a series of interwoven tales, I discuss my own journey of leadership development and offer an analysis of the value of dedicated courses and the importance of providing this to the wider workforce. Story of self I am a doctor in training and was among the first three cohorts placed onto the new Rosalind Franklin programme, organised by the NHS Leadership Academy. I share my key reflections of the impact of this course on my personal and professional development. Story of us My cohort contained professionals from a diverse range of backgrounds-their challenges, views and insights contrasted greatly with my own. Having the protected time to build trust, form teams and discuss issues that crossed organisational boundaries provided novel insights that helped all of us. Story of now As the COVID-19 pandemic has taken hold, we are in a state of extreme flux. As a result, I have become aware of how important it is to marry expertise with generalist skills and knowledge of the wider healthcare system. Enduring the initial surge of COVID-19 was about staff working together and blending specialism with generalist pragmatism. The ability to harness and sustain this type of working will represent a legacy from COVID-19 that is positive and one which galvanises our greatest asset-the talents and experiences of our diverse workforce-in order to meet future healthcare challenges.

Objective:Catheter ablation is an important treatment for ventricular tachycardia (VT) that reduces the frequency of episodes of VT. We sought to evaluate the cost-effectiveness of catheter ablation versus antiarrhythmic drug (AAD) therapy.Methods:A decision-analytic Markov model was used to calculate the costs and health outcomes of catheter ablation or AAD treatment of VT for a hypothetical cohort of patients with ischaemic cardiomyopathy and an implantable cardioverter-defibrillator. The health states and input parameters of the model were informed by patient-reported health-related quality of life (HRQL) data using randomised clinical trial (RCT)-level evidence wherever possible. Costs were calculated from a 2018 UK perspective.Results:Catheter ablation versus AAD therapy had an incremental cost-effectiveness ratio (ICER) of £144 150 (€161 448) per quality-adjusted life-year gained, over a 5-year time horizon. This ICER was driven by small differences in patient-reported HRQL between AAD therapy and catheter ablation. However, only three of six RCTs had measured patient-reported HRQL, and when this was done, it was assessed infrequently. Using probabilistic sensitivity analyses, the likelihood of catheter ablation being cost-effective was only 11%, assuming a willingness-to-pay threshold of £30 000 used by the UK's National Institute for Health and Care Excellence.Conclusion:Catheter ablation of VT is unlikely to be cost-effective compared with AAD therapy based on the current randomised trial evidence. However, better designed studies incorporating detailed and more frequent quality of life assessments are needed to provide more robust and informed cost-effectiveness analyses.

Postgraduate medical education will need to adapt in light of the healthcare and educational reset that the COVID-19 response has necessitated. The ongoing uncertainty of the pandemic, and the proliferation of data from many sources, used by many actors with different frames, has meant that the importance of unbiased decision-making is now central in pulling together a unified response. As two aspiring academic clinicians in the UK with protected time to develop and explore ideas alongside our clinical training1, we became curious about clinical decision-making. We initially examined decision-making from the lens of our research experiences of evaluating the rise of artificial intelligence (AI) algorithms in healthcare.2 Our thesis was that their increasing use would profoundly affect how clinicians made decisions. As we began to unpack the existing literature of clinical decision-making, we focused on the current educational provision for clinicians in understanding what makes for good decisions—and the biases that may warp them. We were surprised to uncover such a paucity of assessment and formal training in these areas—for instance, the terms ‘clinical decision-making’ and ‘bias’ appear only twice each in the UK’s general internal medicine curriculum.3 As a result, we designed an educational intervention in the form of a series of Grand Rounds with a TED-style presentation.4 Our aim was to increase the awareness of biases that can affect decision-making among our peers, consultant colleagues and other allied health professionals. Using our experiences of delivering the presentation ‘Biases in clinical reasoning: I’ll think to that! ’, we reflect on the wider implications for clinicians, not only in terms of the need for future educational interventions but also in terms of the format that they will need …

OBJECTIVE:Fractional flow reserve (FFR) is regarded as the gold standard for the physiological assessment of intermediate coronary artery stenoses. However, FFR does not allow assessment of plaque morphology and lesion geometry. Intracoronary imaging techniques such as intravascular ultrasound (IVUS) and optical coherence tomography (OCT) can help treatment planning by optimising stent implantation, which can improve patient outcomes. The aim of this meta-analysis is to compare the efficacy of IVUS and OCT-derived metrics in detecting flow limiting stenoses in non-left main stem lesions.METHODS:A systematic review of PubMed, Medline, and Cochrane databases was performed and identified studies examining the diagnostic accuracy of IVUS and OCT in detecting significant stenoses when compared to FFR.RESULTS:A total of 33 (7537 lesions) studies (24 IVUS, 7 OCT and 2 IVUS & OCT studies) were included in the meta-analysis. Pooled analysis showed that IVUS- and OCT-derived minimum lumen area (MLA) had a similar sensitivity in predicting haemodynamically significant lesions (IVUS-MLA: 0.747 vs OCT-MLA 0.732, p = 0.519). However, OCT-MLA had a higher specificity (0.763 vs 0.665, p < 0.001) and diagnostic accuracy in detecting flow-limiting stenoses than IVUS-MLA (AUC 0.810 vs 0.754, p = 0.045). Sub-analysis of the studies with the clinically significant FFR cut-off value of 0.80 yielded similar results demonstrating that OCT-MLA has a better accuracy than IVUS-MLA in detecting haemodynamically significant stenoses (AUC 0.809 vs 0.750, p = 0.034).CONCLUSIONS:OCT with its superior image resolution appears to be the preferable intravascular imaging modality for the detection of haemodynamically significant stenoses in non-left main stem lesions.

OBJECTIVE To systematically examine the design, reporting standards, risk of bias, and claims of studies comparing the performance of diagnostic deep learning algorithms for medical imaging with that of expert clinicians. DESIGN Systematic review. DATA SOURCES Medline, Embase, Cochrane Central Register of Controlled Trials, and the World Health Organization trial registry from 2010 to June 2019. ELIGIBILITY CRITERIA FOR SELECTING STUDIES Randomised trial registrations and non-randomised studies comparing the performance of a deep learning algorithm in medical imaging with a contemporary group of one or more expert clinicians. Medical imaging has seen a growing interest in deep learning research. The main distinguishing feature of convolutional neural networks (CNNs) in deep learning is that when CNNs are fed with raw data, they develop their own representations needed for pattern recognition. The algorithm learns for itself the features of an image that are important for classification rather than being told by humans which features to use. The selected studies aimed to use medical imaging for predicting absolute risk of existing disease or classification into diagnostic groups (eg, disease or non-disease). For example, raw chest radiographs tagged with a label such as pneumothorax or no pneumothorax and the CNN learning which pixel patterns suggest pneumothorax. REVIEW METHODS Adherence to reporting standards was assessed by using CONSORT (consolidated standards of reporting trials) for randomised studies and TRIPOD (transparent reporting of a multivariable prediction model for individual prognosis or diagnosis) for non-randomised studies. Risk of bias was assessed by using the Cochrane risk of bias tool for randomised studies and PROBAST (prediction model risk of bias assessment tool) for non-randomised studies. RESULTS Only 10 records were found for deep learning randomised clinical trials, two of which have been published (with low risk of bias, except for lack of blinding, and high adherence to reporting standards) and eight are ongoing. Of 81 non-randomised clinical trials identified, only nine were prospective and just six were tested in a real world clinical setting. The median number of experts in the comparator group was only four (interquartile range 2-9). Full access to all datasets and code was severely limited (unavailable in 95% and 93% of studies, respectively). The overall risk of bias was high in 58 of 81 studies and adherence to reporting standards was suboptimal (<50% adherence for 12 of 29 TRIPOD items). 61 of 81 studies stated in their abstract that performance of artificial intelligence was at least comparable to (or better than) that of clinicians. Only 31 of 81 studies (38%) stated that further prospective studies or trials were required. CONCLUSIONS Few prospective deep learning studies and randomised trials exist in medical imaging. Most nonrandomised trials are not prospective, are at high risk of bias, and deviate from existing reporting standards. Data and code availability are lacking in most studies, and human comparator groups are often small. Future studies should diminish risk of bias, enhance real world clinical relevance, improve reporting and transparency, and appropriately temper conclusions. STUDY REGISTRATION PROSPERO CRD42019123605.

BackgroundThe combination pharmacotherapy of antiplatelet agents, lipid-modifiers, ACE inhibitors/ARBs and beta-blockers are recommended by international guidelines. However, data on effectiveness of the evidence-based combination pharmacotherapy (EBCP) is limited.ObjectivesTo determine the effect of EBCP on mortality and Cardiovascular events in patients with Coronary Heart Disease (CHD) or cerebrovascular disease.MethodsPublications in EMBASE and Medline up to October 2018 were searched for cohort and case-control studies on EBCP for the secondary prevention of cardiovascular disease. The main outcomes were all-cause mortality and major cardiovascular events. Meta-analyses were performed based on random effects models.Results21 studies were included. Comparing EBCP to either monotherapy or no therapy, the pooled risk ratios were 0.60 (95% confidence interval 0.55 to 0.66) for all-cause mortality, 0.70 (0.62 to 0.79) for vascular mortality, 0.73 (0.64 to 0.83) for myocardial infarction and 0.79 (0.68 to 0.91) for cerebrovascular events. Optimal EBCP (all 4 classes of drug prescribed) had a risk ratio for all-cause mortality of 0.50 (0.40 to 0.64). This benefit became more dilute as the number of different classes of drug comprising EBCP was decreased-for 3 classes of drug prescribed the risk ratio was 0.58 (0.49 to 0.69) and for 2 classes, the risk ratio was 0.67 (0.60 to 0.76).ConclusionsEBCP reduces the risk of all-cause mortality and cardiovascular events in patients with CHD or cerebrovascular disease. The different classes of drugs comprising EBCP work in an additive manner, with optimal EBCP conferring the greatest benefit.