Cardiac arrhythmias amongst hospitalised Coronavirus 2019 (COVID-19) patients: Prevalence, characterisation, and clinical algorithm to classify arrhythmic risk.

OBJECTIVES: A significant proportion of COVID-19 patients may have cardiac involvement including arrhythmias. Although arrhythmia characterisation and possible predictors were previously reported, there are conflicting data regarding the exact prevalence of arrhythmias. Clinically applicable algorithms to classify COVID patients' arrhythmic risk are still lacking, and are the aim of our study. METHODS: We describe a single-centre cohort of hospitalised patients with a positive nasopharyngeal swab for COVID-19 during the initial Israeli outbreak between 1/2/2020 and 30/5/2020. The study's outcome was any documented arrhythmia during hospitalisation, based on daily physical examination, routine ECG's, periodic 24-hour Holter, and continuous monitoring. Multivariate analysis was used to find predictors for new arrhythmias and create classification trees for discriminating patients with high and low arrhythmic risk. RESULTS: Out of 390 COVID-19 patients included, 28 (7.2%) had documented arrhythmias during hospitalisation, including 23 atrial tachyarrhythmias, combined atrial fibrillation (AF), and ventricular fibrillation, ventricular tachycardia storm, and 3 bradyarrhythmias. Only 7/28 patients had previous arrhythmias. Our study showed a significant correlation between disease severity and arrhythmia prevalence (P < .001) with a low arrhythmic prevalence amongst mild disease patients (2%). Multivariate analysis revealed background heart failure (CHF) and disease severity are independently associated with overall arrhythmia while age, CHF, disease severity, and arrhythmic symptoms are associated with tachyarrhythmias. A novel decision tree using age, disease severity, CHF, and troponin levels was created to stratify patients into high and low risk for developing arrhythmia. CONCLUSIONS: Dominant arrhythmia amongst COVID-19 patients is AF. Arrhythmia prevalence is associated with age, disease severity, CHF, and troponin levels. A novel simple Classification tree, based on these parameters, can discriminate between high and low arrhythmic risk patients.

What can we learn from simulation-based training to improve skills for end-of-life care? Insights from a national project in Israel.

BACKGROUND: Simulation-based training improves residents' skills for end-of-life (EOL) care. In the field, staff providers play a significant role in handling those situations and in shaping practice by role modeling. We initiated an educational intervention to train healthcare providers for improved communication skills at EOL using simulation of sensitive encounters with patients and families. METHODS: Hospital physicians and nurses (n = 1324) attended simulation-based workshops (n = 100) in a national project to improve EOL care. We analyzed perceptions emerging from group discussions following simulations, from questionnaires before and after each workshop, and from video-recorded simulations using a validated coding system. We used the simulation setting as a novel tool for action research. We used a participatory inquiry paradigm, with repetitive cycles of exploring barriers and challenges with participants in an iterative pattern of observation, discussion and reflection - including a description of our own responses and evolution of thought as well as system effects. RESULTS: The themes transpiring included lack of training, knowledge and time, technology overuse, uncertainty in decision-making, poor skills for communication and teamwork. Specific scenarios demonstrated lack of experience at eliciting preferences for EOL care and at handling conflicts or dilemmas. Content analysis of simulations showed predominance of cognitive utterances - by an order of magnitude more prevalent than emotional expressions. Providers talked more than actors did and episodes of silence were rare. Workshop participants acknowledged needs to improve listening skills, attention to affect and teamwork. They felt that the simulation-based workshop is likely to ameliorate future handling of EOL situations. We observed unanticipated consequences from our project manifested as a field study of preparedness to EOL in nursing homes, followed by a national survey on quality of care, leading to expansion of palliative care services and demand for EOL care education in various frameworks and professional areas. CONCLUSIONS: Reflective simulation exercises show barriers and paths to improvement among staff providers. When facing EOL situations, physicians and nurses use cognitive language far more often than emotions related expressions, active listening, or presence in silence. Training a critical mass of staff providers may be valuable to induce a cultural shift in EOL care.