Effect Of The Cardio First Angel™ Device On CPR Indices: A Randomized Controlled Clinical Trial

Background: A number of cardiopulmonary resuscitation (CPR) adjunct devices have been developed to improve the consistency and quality of manual chest compressions. We investigated whether a CPR feedback device would improve CPR quality and consistency, as well as patient survival. Methods: We conducted a randomized controlled study of patients undergoing CPR for cardiac arrest in the mixed medical-surgical intensive care units of four academic teaching hospitals. Patients were randomized to receive either standard manual CPR or CPR using the Cardio First Angel™ CPR feedback device. Recorded variables included guideline adherence, CPR quality, return of spontaneous circulation (ROSC) rates, and CPR-associated morbidity. Results: A total of 229 subjects were randomized; 149 were excluded; and 80 were included. Patient demographics were similar. Adherence to published CPR guidelines and CPR quality was significantly improved in the intervention group (p \u3c 0.0001), as were ROSC rates (72 % vs. 35 %; p = 0.001). A significant decrease was observed in rib fractures (57 % vs. 85 %; p = 0.02), but not sternum fractures (5 % vs. 17 %; p = 0.15). Conclusions: Use of the Cardio First Angel™ CPR feedback device improved adherence to published CPR guidelines and CPR quality, and it was associated with increased rates of ROSC. A decrease in rib but not sternum fractures was observed with device use. Further independent prospective validation is warranted to determine if these results are reproducible in other acute care settings

Cardiac Rehabilitation Using The Family-Centered Empowerment Model Versus Home-Based Cardiac Rehabilitation In Patients With Myocardial Infarction: A Randomised Controlled Trial

Objective To determine if a hybrid cardiac rehabilitation (CR) programme using the Family-Centered Empowerment Model (FCEM) as compared with standard CR will improve patient quality of life, perceived stress and state anxiety of patients with myocardial infarction (MI). Methods We conducted a randomised controlled trial in which patients received either standard home CR or CR using the FCEM strategy. Patient empowerment was measured with FCEM questionnaires preintervention and postintervention for a total of 9 assessments. Quality of life, perceived stress, and state and trait anxiety were assessed using the 36-Item Short Form Health Survey (SF-36), the 14-item Perceived Stress, and the 20-item State and 20-item Trait Anxiety questionnaires, respectively. Results 70 patients were randomised. Baseline characteristics were similar. Ejection fraction was significantly higher in the intervention group at measurements 2 (p=0.01) and 3 (p=0.001). Exercise tolerance measured as walking distance was significantly improved in the intervention group throughout the study. The quality of life results in the FCEM group showed significant improvement both within the group over time (p\u3c0.0001) and when compared with control (p\u3c0.0001). Similarly, the perceived stress and state anxiety results showed significant improvement both within the FCEM group over time (p\u3c0.0001) and when compared with control (p\u3c0.0001). No significant difference was found either within or between groups for trait anxiety. Conclusions The family-centred empowerment model may be an effective hybrid cardiac rehabilitation method for improving the physical and mental health of patients post-MI; however, further study is needed to validate these findings. Clinical Trials.gov identifier NCT02402582. Trial registration number NCT02402582

Multiscale interactome analysis coupled with off-target drug predictions reveals drug repurposing candidates for human coronavirus disease

The COVID-19 pandemic has highlighted the urgent need for the identification of new antiviral drug therapies for a variety of diseases. COVID-19 is caused by infection with the human coronavirus SARS-CoV-2, while other related human coronaviruses cause diseases ranging from severe respiratory infections to the common cold. We developed a computational approach to identify new antiviral drug targets and repurpose clinically-relevant drug compounds for the treatment of a range of human coronavirus diseases. Our approach is based on graph convolutional networks (GCN) and involves multiscale host-virus interactome analysis coupled to off-target drug predictions. Cell-based experimental assessment reveals several clinically-relevant drug repurposing candidates predicted by the in silico analyses to have antiviral activity against human coronavirus infection. In particular, we identify the MET inhibitor capmatinib as having potent and broad antiviral activity against several coronaviruses in a MET-independent manner, as well as novel roles for host cell proteins such as IRAK1/4 in supporting human coronavirus infection, which can inform further drug discovery studies.We gratefully acknowledge funding that supported this research support from the Ryerson University Faculty of Science (CNA), as well as funding support in the form of a CIFAR Catalyst Grant (JPJ and CNA), an NSERC Alliance Grant (CNA) and the Ryerson COVID-19 SRC Response Fund award (CNA). BW is partly supported by CIFAR AI Chairs Program. This work was also supported by a Mitacs award (BW), the European Union’s Horizon 2020 research and innovation program under a Marie Sklodowska-Curie grant (ER), by the CIFAR Azrieli Global Scholar program (JPJ), by the Ontario Early Researcher Awards program (JPJ and CNA), and by the Canada Research Chairs program (JPJ). We also thank Dr. James Rini (University of Toronto) for the kind gift of the 9.8E12 antibody used to detect the 229E Spike protein, and Dr. Scott Gray-Owen (University of Toronto) for the kind gift of the NL63 human coronavirus.Peer reviewe

Biological and therapeutic implications of a unique subtype of NPM1 mutated AML

In acute myeloid leukemia (AML), molecular heterogeneity across patients constitutes a major challenge for prognosis and therapy. AML with NPM1 mutation is a distinct genetic entity in the revised World Health Organization classification. However, differing patterns of co-mutation and response to therapy within this group necessitate further stratification. Here we report two distinct subtypes within NPM1 mutated AML patients, which we label as primitive and committed based on the respective presence or absence of a stem cell signature. Using gene expression (RNA-seq), epigenomic (ATAC-seq) and immunophenotyping (CyToF) analysis, we associate each subtype with specific molecular characteristics, disease differentiation state and patient survival. Using ex vivo drug sensitivity profiling, we show a differential drug response of the subtypes to specific kinase inhibitors, irrespective of the FLT3-ITD status. Differential drug responses of the primitive and committed subtype are validated in an independent AML cohort. Our results highlight heterogeneity among NPM1 mutated AML patient samples based on stemness and suggest that the addition of kinase inhibitors to the treatment of cases with the primitive signature, lacking FLT3-ITD, could have therapeutic benefit. Molecular heterogeneity of acute myeloid leukaemia (AML) across patients is a major challenge for prognosis and therapy. Here, the authors show that NPM1 mutated AML is a heterogeneous class, consisting of two subtypes which exhibit distinct molecular characteristics, differentiation state, patient survival and drug response

Multiscale interactome analysis coupled with off-target drug predictions reveals drug repurposing candidates for human coronavirus disease

The COVID-19 pandemic has led to an urgent need for the identification of new antiviral drug therapies that can be rapidly deployed to treat patients with this disease. COVID-19 is caused by infection with the human coronavirus SARS-CoV-2. We developed a computational approach to identify new antiviral drug targets and repurpose clinically-relevant drug compounds for the treatment of COVID-19. Our approach is based on graph convolutional networks (GCN) and involves multiscale host-virus interactome analysis coupled to off-target drug predictions. Cellbased experimental assessment reveals several clinically-relevant repurposing drug candidates predicted by the in silico analyses to have antiviral activity against human coronavirus infection. In particular, we identify the MET inhibitor capmatinib as having potent and broad antiviral activity against several coronaviruses in a MET-independent manner, as well as novel roles for host cell proteins such as IRAK1/4 in supporting human coronavirus infection, which can inform further drug discovery studies.We gratefully acknowledge funding that supported this research support from the Ryerson University Faculty of Science (CNA), as well as funding support in the form of a CIFAR Catalyst Grant (JPJ and CNA), an NSERC Alliance Grant (CNA) and the Ryerson COVID-19 SRC Response Fund award (CNA). BW is partly supported by CIFAR AI Chairs Program. This work was also supported by a Mitacs award (BW), the European Union’s Horizon 2020 research and innovation program under a Marie Sklodowska-Curie grant (ER), by the CIFAR Azrieli Global Scholar program (JPJ), by the Ontario Early Researcher Awards program (JPJ and CNA), and by the Canada Research Chairs program (JPJ).N