Examining the Effect of Virtual Learning on Canadian Pre-Clerkship Medical Student Well-Being During the COVID-19 Pandemic.

Introduction: The restrictions of the COVID-19 pandemic resulted in the broad and abrupt incorporation of virtual/online learning into medical school curricula. While current literature explores the effectiveness and economic advantages of virtual curricula, robust literature surrounding the effect of virtual learning on medical student well-being is needed. This study aims to explore the effects of a predominantly virtual curriculum on pre-clerkship medical student well-being. Methods: This study followed a constructivist grounded theory approach. During the 2020-2021 and 2021-2022 academic years, students in pre-clerkship medical studies at Western University in Canada were interviewed by medical student researchers over Zoom. Data was analyzed iteratively using constant comparison. Results: We found that students experiencing virtual learning faced two key challenges: 1) virtual learning may be associated with an increased sense of social isolation, negatively affecting wellbeing, 2) virtual learning may impede or delay the development of trainees' professional identity. With time, however, we found that many students were able to adapt by using protective coping strategies that enabled them to appreciate positive elements of online learning, such as its flexibility. Discussion: When incorporating virtual learning into medical education, curriculum developers should prioritize optimizing existing and creating new ways for students to interact with both peers and faculty to strengthen medical student identity and combat feelings of social isolation.

Medical Students as Educators: Addressing Teaching Skills Through a Pre-clerkship Development Group.

In medicine, effective teaching is requisite for both successful patient care and trainee development. However, opportunities for medical students to gain exposure to pedagogical principles and hone teaching skills are currently limited. Our initiative provides avenues for medical students to intentionally develop their teaching skill set from an early stage.

Effect of inhaled anaesthetics on cognitive and psychiatric outcomes in critically ill adults: a systematic review and meta-analysis.

BACKGROUND: Sedation of critically ill patients with inhaled anaesthetics may reduce lung inflammation, time to extubation, and ICU length of stay compared with intravenous (i.v.) sedatives. However, the impact of inhaled anaesthetics on cognitive and psychiatric outcomes in this population is unclear. In this systematic review, we aimed to summarise the effect of inhaled anaesthetics on cognitive and psychiatric outcomes in critically ill adults. METHODS: We searched MEDLINE, EMBASE, and PsycINFO for case series, retrospective, and prospective studies in critically ill adults sedated with inhaled anaesthetics. Outcomes included delirium, psychomotor and neurological recovery, long-term cognitive dysfunction, ICU memories, anxiety, depression, post-traumatic stress disorder (PTSD), and instruments used for assessment. RESULTS: Thirteen studies were included in distinct populations of post-cardiac arrest survivors (n=4), postoperative noncardiac patients (n=3), postoperative cardiac patients (n=2), and mixed medical-surgical patients (n=4). Eight studies reported delirium incidence, two neurological recovery, and two ICU memories. One study reported on psychomotor recovery, long-term cognitive dysfunction, anxiety, depression, and PTSD. A meta-analysis of five trials found no difference in delirium incidence between inhaled and i.v. sedatives (relative risk 0.95 [95% confidence interval: 0.59-1.54]). Compared with i.v. sedatives, inhaled anaesthetics were associated with fewer hallucinations and faster psychomotor recovery but no differences in other outcomes. There was heterogeneity in the instruments used and timing of these assessments. CONCLUSIONS: Based on the limited evidence available, there is no difference in cognitive and psychiatric outcomes between adults exposed to volatile sedation or intravenous sedation in the ICU. Future studies should incorporate outcome assessment with validated tools during and after hospital stay. SYSTEMATIC REVIEW PROTOCOL: PROSPERO CRD42021236455.

Protocol for a systematic review on effective patient positioning for rapid sequence intubation.

INTRODUCTION: Rapid sequence intubation (RSI) is an advanced airway technique to perform endotracheal intubation in patients at high risk of aspiration. Although RSI is recognised as a life-saving technique and performed by many physicians in various settings (emergency departments, intensive care units), there is still a lack of consensus on various features of the procedure, most notably patient positioning. Previously, experts have commented on the unique drawbacks and benefits of various positions and studies have been published comparing patient positions and how it can affect endotracheal intubation in the context of RSI. The purpose of this systematic review is to compile the existing evidence to understand and compare how different patient positions can potentially affect the success of RSI. METHODS AND ANALYSIS: We will use MEDLINE, EMBASE and the Cochrane Library to source studies from 1946 to 2021 that evaluate the impact of patient positioning on endotracheal intubation in the context of RSI. We will include randomised control trials, case-control studies, prospective/retrospective cohort studies and mannequin simulation studies for consideration in this systematic review. Subsequently, we will generate a Preferred Reporting Items for Systematic Reviews and Meta-Analyses flow diagram to display how we selected our final studies for inclusion in the review. Two independent reviewers will complete the study screening, selection and extraction, with a third reviewer available to address any conflicts. The reviewers will extract this data in accordance with our outcomes of interest and display it in a table format to highlight patient-relevant outcomes and difficulty airway management outcomes. We will use the Risk of Bias tool and the Newcastle-Ottawa Scale to assess included studies for bias. ETHICS AND DISSEMINATION: This systematic review does not require ethics approval, as all patient-centred data will be reported from published studies. PROSPERO REGISTRATION NUMBER: CRD42022289773.

Deep Ensemble Learning for Retinal Image Classification.

Purpose: Vision impairment affects 2.2 billion people worldwide, half of which is preventable with early detection and treatment. Currently, automatic screening of ocular pathologies using convolutional neural networks (CNNs) on retinal fundus photographs is limited to a few pathologies. Simultaneous detection of multiple ophthalmic pathologies would increase clinical usability and uptake. Methods: Two thousand five hundred sixty images were used from the Retinal Fundus Multi-Disease Image Dataset (RFMiD). Models were trained (n = 1920) and validated (n = 640). Five selected CNN architectures were trained to predict the presence of any pathology and categorize the 28 pathologies. All models were trained to minimize asymmetric loss, a modified form of binary cross-entropy. Individual model predictions were averaged to obtain a final ensembled model and assessed for mean area under the receiver-operator characteristic curve (AUROC) for disease screening (healthy versus pathologic image) and classification (AUROC for each class). Results: The ensemble network achieved a disease screening (healthy versus pathologic) AUROC score of 0.9613. The highest single network score was 0.9586 using the SE-ResNeXt architecture. For individual disease classification, the average AUROC score for each class was 0.9295. Conclusions: Retinal fundus images analyzed by an ensemble of CNNs trained to minimize asymmetric loss were effective in detection and classification of ocular pathologies than individual models. External validation is needed to translate machine learning models to diverse clinical contexts. Translational Relevance: This study demonstrates the potential benefit of ensemble-based deep learning methods on improving automatic screening and diagnosis of multiple ocular pathologies from fundoscopy imaging.

Evidence-Based Considerations for the Design of an Open-Source Ventilator: A Systematic Review.

To inform the design of open-source ventilators, we performed a systematic review of clinical practice guidelines (CPGs) to consolidate the evidence on mechanical ventilation strategies that result in improved patient-important outcomes for acute hypoxic respiratory failure. DATA SOURCES: We developed a search strategy to identify relevant CPGs from Ovid Medline, Ovid Medline In-Process & Other Non-Indexed Citations, Embase, the Cochrane Library, Mendeley, and Google scholar from 2010 to February 17, 2022. STUDY SELECTION: Using a two-step screening process with two independent reviewers, we included CPGs that made recommendations on mechanical ventilation strategies of interest. Guidelines that reported at least one recommendation about mechanical ventilation in ICU patients with acute hypoxic respiratory failure were included. DATA EXTRACTION: From the 13 eligible guidelines, we collected data on country, aim, patient population, impact on morbidity and mortality (effect size and CIs), recommendations, strength of Recommendation (as per Grading of Recommendations, Assessment, Development and Evaluations), and details of supporting evidence base. DATA SYNTHESIS: We identified three ventilation strategies that confer a mortality and morbidity benefit for ventilated patients with acute hypoxic respiratory failure: low-tidal volume ventilation, plateau pressures of less than 30 cm H2O, and higher positive end-expiratory pressure (PEEP). These moderate-to-strong recommendations were based on moderate-to-high certainty in evidence. We identified several other recommendations with no or minimal certainty in evidence. CONCLUSIONS: Our systematic review of international CPGs identified no recommendations favoring specific mode of ventilation and three ventilation strategies that confer mortality and morbidity benefits, backed by moderate-to-strong evidence. Ventilator design teams must include the ability to consistently provide and measure low-tidal volume ventilation, plateau pressures of less than 30 cm H2O, and higher PEEP into their designs. Based on our findings, we provide the first public framework for open-source ventilator design.