Nutritional management in critically ill patients with COVID-19: a retrospective multicentre study.

INTRODUCTION: Although nutritional treatment is an established pillar of multidisciplinary care provided in critical illness, there are many concerns regarding this issue in severe COVID-19. This observational, retrospective, multicentre study aimed to analyse the approach to nutritional treatment among selected intensive care units (ICUs) in Poland. MATERIAL AND METHODS: The medical records of 129 patients hospitalized in five units due to respiratory failure following COVID-19 were analysed in terms of nutritional management on the eighth day of the ICU stay. The Harris-Benedict equation (HB), Mifflin St. Jeor equation (MsJ) and ESPEN formula (20 kcal kg -1 body weight) were used to estimate the energy target for each patient, and two ESPEN formulas determined the protein target (1 g kg -1 body weight and 1.3 g kg -1 body weight). RESULTS: Evaluation of nutritional therapy was performed in 129 subjects. The fulfilment of caloric requirement considering the HB, MsJ and ESPEN formula was 66%, 66.7% and 62.5%, respectively. Two clinical centres managed to provide 70% or more of daily caloric requirements. According to the ESPEN formula, the implementation of the protein target was 70%; however, one of the investigated units provided a median of 157% of the protein demand. The nutritional management varied in the preferred route of nutrition administration. Neither method nor grade of nutrition supply influenced biochemical parameters on the 8th day of ICU stay. CONCLUSIONS: Significant differences in nutritional treatment of critically ill COVID-19 patients in Polish ICUs were noted, which underlines the importance of setting up clear guidelines regarding this issue.

A Multi-Centre, Randomised, Double-Blind, Placebo-Controlled Phase III Clinical Trial Evaluating the Impact of BCG Re-Vaccination on the Incidence and Severity of SARS-CoV-2 Infections among Symptomatic Healthcare Professionals during the COVID-19 Pandemic in Poland-Evaluation of Antibody Concentrations.

Tuberculosis (TB) was the predominant cause of death from a single infectious agent worldwide before the severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) pandemic. Although TB vaccines have been successfully used for about 100 years, their full effect is still unknown. In previous studies, a reduced incidence and mortality from a coronavirus disease in TB-vaccinated populations were reported. In this article, we present the secondary analysis of a randomised controlled trial, reporting the results of a serological assessment evaluating the effect of the Bacillus Calmette-Guérin (BCG) vaccine on SARS-CoV-2. Participants-healthcare workers-were assessed 1-2 and 8 months after the second dose of the coronavirus disease 2019 (COVID-19) vaccine. We found no associations between antibody concentration, BCG revaccination, and additional characteristics, such as age, gender, or Body Mass Index. The effect of BCG vaccination on the immunological response against SARS-CoV-2 requires further research.

Use of Bayesian statistical approach in diagnosing secondary hypertension.

Bayes's theorem is predominantly used in diagnosing based on the results of various diagnostic tests. This statistical approach is intuitive in differential diagnosis as it explicitly takes into consideration data from medical history, physical examination, laboratory findings and imaging. Bayes's theorem states that the probability of disease occurrence (or occurrence of other outcome) after new information is obtained, called a posteriori probability, depends directly on an a priori probability and the value of likelihood ratio associated with a given test result. This paper describes basic Bayesian analysis in relation to the diagnosis of two types of secondary hypertension; primary aldosteronism and pheochromocytoma. This choice is based on two facts; primary aldosteronism is believed to be the most common and the most commonly detected cause of symptomatic hypertension and pheochromocytoma is thought to have rapid progress and stormy clinical course. This article aims to draw physicians' attention to and increase the knowledge of Bayesian analysis, and to describe its use in everyday clinical decision making. On the basis of this theorem's foundations, the discussion in relation to the issue of differential diagnosis between physicians, their patients, and medical students should also improve. When used in practice, one should be aware, however, of Bayesian analysis limitations concerning the diagnostic test application and limited knowledge of diagnostic test accuracy, and insecure or faulty a priori probability estimates.