Shelley McLeod

Bio: Shelley McLeod is an academic researcher from University of Toronto. The author has contributed to research in topics: Emergency department & Medicine. The author has an hindex of 20, co-authored 101 publications receiving 1746 citations. Previous affiliations of Shelley McLeod include University of Western Ontario & Mount Sinai Hospital, Toronto.

Drug treatments for covid-19: living systematic review and network meta-analysis.

Abstract: Objective To compare the effects of treatments for coronavirus disease 2019 (covid-19). Design Living systematic review and network meta-analysis. Data sources WHO covid-19 database, a comprehensive multilingual source of global covid-19 literature, up to 1 March 2021 and six additional Chinese databases up to 20 February 2021. Studies identified as of 12 February 2021 were included in the analysis. Study selection Randomised clinical trials in which people with suspected, probable, or confirmed covid-19 were randomised to drug treatment or to standard care or placebo. Pairs of reviewers independently screened potentially eligible articles. Methods After duplicate data abstraction, a bayesian network meta-analysis was conducted. Risk of bias of the included studies was assessed using a modification of the Cochrane risk of bias 2.0 tool, and the certainty of the evidence using the grading of recommendations assessment, development, and evaluation (GRADE) approach. For each outcome, interventions were classified in groups from the most to the least beneficial or harmful following GRADE guidance. Results 196 trials enrolling 76 767 patients were included; 111 (56.6%) trials and 35 098 (45.72%) patients are new from the previous iteration; 113 (57.7%) trials evaluating treatments with at least 100 patients or 20 events met the threshold for inclusion in the analyses. Compared with standard care, corticosteroids probably reduce death (risk difference 20 fewer per 1000 patients, 95% credible interval 36 fewer to 3 fewer, moderate certainty), mechanical ventilation (25 fewer per 1000, 44 fewer to 1 fewer, moderate certainty), and increase the number of days free from mechanical ventilation (2.6 more, 0.3 more to 5.0 more, moderate certainty). Interleukin-6 inhibitors probably reduce mechanical ventilation (30 fewer per 1000, 46 fewer to 10 fewer, moderate certainty) and may reduce length of hospital stay (4.3 days fewer, 8.1 fewer to 0.5 fewer, low certainty), but whether or not they reduce mortality is uncertain (15 fewer per 1000, 30 fewer to 6 more, low certainty). Janus kinase inhibitors may reduce mortality (50 fewer per 1000, 84 fewer to no difference, low certainty), mechanical ventilation (46 fewer per 1000, 74 fewer to 5 fewer, low certainty), and duration of mechanical ventilation (3.8 days fewer, 7.5 fewer to 0.1 fewer, moderate certainty). The impact of remdesivir on mortality and most other outcomes is uncertain. The effects of ivermectin were rated as very low certainty for all critical outcomes, including mortality. In patients with non-severe disease, colchicine may reduce mortality (78 fewer per 1000, 110 fewer to 9 fewer, low certainty) and mechanical ventilation (57 fewer per 1000, 90 fewer to 3 more, low certainty). Azithromycin, hydroxychloroquine, lopinavir-ritonavir, and interferon-beta do not appear to reduce risk of death or have an effect on any other patient-important outcome. The certainty in effects for all other interventions was low or very low. Conclusion Corticosteroids and interleukin-6 inhibitors probably confer important benefits in patients with severe covid-19. Janus kinase inhibitors appear to have promising benefits, but certainty is low. Azithromycin, hydroxychloroquine, lopinavir-ritonavir, and interferon-beta do not appear to have any important benefits. Whether or not remdesivir, ivermectin, and other drugs confer any patient-important benefit remains uncertain. Systematic review registration This review was not registered. The protocol is publicly available in the supplementary material. Readers’ note This article is a living systematic review that will be updated to reflect emerging evidence. Updates may occur for up to two years from the date of original publication. This is the fourth version of the original article published on 30 July 2020 (BMJ 2020;370:m2980), and previous versions can be found as data supplements. When citing this paper please consider adding the version number and date of access for clarity.

Federated learning for predicting clinical outcomes in patients with COVID-19.

Abstract: Federated learning (FL) is a method used for training artificial intelligence models with data from multiple sources while maintaining data anonymity, thus removing many barriers to data sharing. Here we used data from 20 institutes across the globe to train a FL model, called EXAM (electronic medical record (EMR) chest X-ray AI model), that predicts the future oxygen requirements of symptomatic patients with COVID-19 using inputs of vital signs, laboratory data and chest X-rays. EXAM achieved an average area under the curve (AUC) >0.92 for predicting outcomes at 24 and 72 h from the time of initial presentation to the emergency room, and it provided 16% improvement in average AUC measured across all participating sites and an average increase in generalizability of 38% when compared with models trained at a single site using that site’s data. For prediction of mechanical ventilation treatment or death at 24 h at the largest independent test site, EXAM achieved a sensitivity of 0.950 and specificity of 0.882. In this study, FL facilitated rapid data science collaboration without data exchange and generated a model that generalized across heterogeneous, unharmonized datasets for prediction of clinical outcomes in patients with COVID-19, setting the stage for the broader use of FL in healthcare. Federated learning, a method for training artificial intelligence algorithms that protects data privacy, was used to predict future oxygen requirements of symptomatic patients with COVID-19 using data from 20 different institutes across the globe.

2020 ESC Guidelines for the diagnosis and management of atrial fibrillation developed in collaboration with the European Association for Cardio-Thoracic Surgery (EACTS).

Abstract: Supplementary Table 9, column 'Edoxaban', row 'eGFR category', '95 mL/min' (page 15). The cell should be coloured green instead of yellow. It should also read "60 mg"instead of "60 mg (use with caution in 'supranormal' renal function)."In the above-indicated cell, a footnote has also been added to state: "Edoxaban should be used in patients with high creatinine clearance only after a careful evaluation of the individual thromboembolic and bleeding risk."Supplementary Table 9, column 'Edoxaban', row 'Dose reduction in selected patients' (page 16). The cell should read "Edoxaban 60 mg reduced to 30 mg once daily if any of the following: creatinine clearance 15-50 mL/min, body weight <60 kg, concomitant use of dronedarone, erythromycin, ciclosporine or ketokonazole"instead of "Edoxaban 60 mg reduced to 30 mg once daily, and edoxaban 30 mg reduced to 15mg once daily, if any of the following: creatinine clearance of 30-50 mL/min, body weight <60 kg, concomitant us of verapamil or quinidine or dronedarone."

Guidelines for the Early Management of Patients With Acute Ischemic Stroke: 2019 Update to the 2018 Guidelines for the Early Management of Acute Ischemic Stroke: A Guideline for Healthcare Professionals From the American Heart Association/American Stroke Association.

Abstract: Background and Purpose- The purpose of these guidelines is to provide an up-to-date comprehensive set of recommendations in a single document for clinicians caring for adult patients with acute arterial ischemic stroke. The intended audiences are prehospital care providers, physicians, allied health professionals, and hospital administrators. These guidelines supersede the 2013 Acute Ischemic Stroke (AIS) Guidelines and are an update of the 2018 AIS Guidelines. Methods- Members of the writing group were appointed by the American Heart Association (AHA) Stroke Council's Scientific Statements Oversight Committee, representing various areas of medical expertise. Members were not allowed to participate in discussions or to vote on topics relevant to their relations with industry. An update of the 2013 AIS Guidelines was originally published in January 2018. This guideline was approved by the AHA Science Advisory and Coordinating Committee and the AHA Executive Committee. In April 2018, a revision to these guidelines, deleting some recommendations, was published online by the AHA. The writing group was asked review the original document and revise if appropriate. In June 2018, the writing group submitted a document with minor changes and with inclusion of important newly published randomized controlled trials with >100 participants and clinical outcomes at least 90 days after AIS. The document was sent to 14 peer reviewers. The writing group evaluated the peer reviewers' comments and revised when appropriate. The current final document was approved by all members of the writing group except when relationships with industry precluded members from voting and by the governing bodies of the AHA. These guidelines use the American College of Cardiology/AHA 2015 Class of Recommendations and Level of Evidence and the new AHA guidelines format. Results- These guidelines detail prehospital care, urgent and emergency evaluation and treatment with intravenous and intra-arterial therapies, and in-hospital management, including secondary prevention measures that are appropriately instituted within the first 2 weeks. The guidelines support the overarching concept of stroke systems of care in both the prehospital and hospital settings. Conclusions- These guidelines provide general recommendations based on the currently available evidence to guide clinicians caring for adult patients with acute arterial ischemic stroke. In many instances, however, only limited data exist demonstrating the urgent need for continued research on treatment of acute ischemic stroke.