Can anxiety in undergraduate students in a high-fidelity clinical simulation be predicted? A randomized, sham-controlled, blinded trial

INTRODUCTION

High-fidelity clinical simulation has implied a revolution in health science training. Despite its benefits, some drawbacks could hinder the learning process, especially the anxiety produced during such scenarios.

OBJECTIVES

The aim of the present work is to develop a predictive model capable of determining which students will present high levels of anxiety.

DESIGN

We performed a randomized, sham-controlled, blinded trial in which students were randomly assigned to four scenarios and played one of two possible roles.

METHODS

Before and after the simulation we assessed the anxiety level along with physiological and analytical parameters. The main analyzed outcome was an increase of ≥25% in anxiety compared with baseline.

RESULTS

The type of scenario or the role played had no effect on anxiety. The predictive model presented an Area Under the Receiver Operating Characteristics of 0.798 (95% CI: 0.69-0.90; p < 0.001), with age and systolic blood pressure being protective factors against anxiety.

CONCLUSIONS

Our results showed that the anxiety level developed during simulation could be predicted. The application of this predictive model when associated to appropriate techniques to deal with increased anxiety levels could improve the learning process of medical students during simulations.

Blood Biomarkers for Assessing Headaches in Healthcare Workers after Wearing Biological Personal Protective Equipment in a COVID-19 Field Hospital

The coronavirus disease 2019 (COVID-19) has led to a pandemic, which among other things, has highlighted biosafety as a key cornerstone in the management of disease transmission. The aim of this work was to analyze the role played by different blood biomarkers in predicting the appearance of headaches in healthcare workers wearing personal protective equipment (PPE) in a COVID-19 treatment unit. A prospective cohort study of 38 healthcare workers was performed during April 2020. Blood analysis, performed just before the start of a 4 hour shift, was carried out on all volunteers equipped with PPE. At the end of their shifts and after decontamination, they were asked if they had suffered from headache in order to obtain a binary outcome. The baseline creatinine value reflected a specific odds ratio of 241.36 (95% CI: 2.50-23,295.43; p = 0.019) and an area under the curve (AUC) value of 0.737 (95%CI: 0.57-0.90; p < 0.01). Blood creatinine is a good candidate for predicting the appearance of a de novo headache in healthcare workers after wearing PPE for four hours in a COVID-19 unit.

Blood Biomarkers for Assessing Headaches in Healthcare Workers after Wearing Biological Personal Protective Equipment in a COVID-19 Field Hospital

The coronavirus disease 2019 (COVID-19) has led to a pandemic, which among other things, has highlighted biosafety as a key cornerstone in the management of disease transmission. The aim of this work was to analyze the role played by different blood biomarkers in predicting the appearance of headaches in healthcare workers wearing personal protective equipment (PPE) in a COVID-19 treatment unit. A prospective cohort study of 38 healthcare workers was performed during April 2020. Blood analysis, performed just before the start of a 4 hour shift, was carried out on all volunteers equipped with PPE. At the end of their shifts and after decontamination, they were asked if they had suffered from headache in order to obtain a binary outcome. The baseline creatinine value reflected a specific odds ratio of 241.36 (95% CI: 2.50–23,295.43; p = 0.019) and an area under the curve (AUC) value of 0.737 (95%CI: 0.57–0.90; p < 0.01). Blood creatinine is a good candidate for predicting the appearance of a de novo headache in healthcare workers after wearing PPE for four hours in a COVID-19 unit.