Bacterial infections in patients hospitalized with COVID-19

Bacterial infections may complicate the course of COVID-19 patients. The rate and predictors of bacterial infections were examined in patients consecutively admitted with COVID-19 at one tertiary hospital in Madrid between March 1st and April 30th, 2020. Among 1594 hospitalized patients with COVID-19, 135 (8.5%) experienced bacterial infectious events, distributed as follows: urinary tract infections (32.6%), bacteremia (31.9%), pneumonia (31.8%), intra-abdominal infections (6.7%) and skin and soft tissue infections (6.7%). Independent predictors of bacterial infections were older age, neurological disease, prior immunosuppression and ICU admission (p < 0.05). Patients with bacterial infections who more frequently received steroids and tocilizumab, progressed to lower Sap02/FiO2 ratios, and experienced more severe ARDS (p < 0.001). The mortality rate was significantly higher in patients with bacterial infections as compared to the rest (25% vs 6.7%, respectively; p < 0.001). In multivariate analyses, older age, prior neurological or kidney disease, immunosuppression and ARDS severity were associated with an increased mortality (p < 0.05) while bacterial infections were not. Conversely, the use of steroids or steroids plus tocilizumab did not confer a higher risk of bacterial infections and improved survival rates. Bacterial infections occurred in 8.5% of patients hospitalized with COVID-19 during the first wave of the pandemic. They were not independently associated with increased mortality rates. Baseline COVID-19 severity rather than the incidence of bacterial infections seems to contribute to mortality. When indicated, the use of steroids or steroids plus tocilizumab might improve survival in this population.

Severe Lymphopenia as a Predictor of COVID-19 Mortality in Immunosuppressed Patients

Background. Coronavirus disease 2019 (COVID-19) has a high mortality in certain group of patients. We analysed the impact of baseline immunosuppression in COVID-19 mortality and the role of severe lymphopenia in immunocompromised subjects. Methods. We analysed all patients admitted with COVID-19 in a tertiary hospital in Madrid between March 1st and April 30th 2020. Epidemiological and clinical data, including severe lymphopenia (<500 lymphocytes/mm³) during admission, were analysed and compared based on their baseline immunosuppression condition. Results. A total of 1594 patients with COVID-19 pneumonia were hospitalised during the study period. 166 (10.4%) were immunosuppressed. Immunocompromised patients were younger (64 vs. 67 years, p = 0.02) but presented higher rates of hypertension, diabetes, heart, neurological, lung, kidney and liver disease (p < 0.05). They showed more severe lymphopenia (53% vs 24.1%, p < 0.001), lower SapO₂/FiO₂ ratios (251 vs 276, p = 0.02) during admission and higher mortality rates (27.1% vs 13.5%, p < 0.001). After adjustment, immunosuppression remained as an independent factor related to mortality (Odds Ratio (OR): 2.24, p < 0.001). In the immunosuppressed group, age (OR = 1.06, p = 0.01), acute respiratory distress syndrome (ARDS) (OR = 12.27, p = 0.017) and severe lymphopenia (OR = 3.48, p = 0.04) were the factors related to high mortality rate. Conclusion. Immunosuppression is an independent mortality risk factor in COVID-19. Severe lymphopenia should be promptly identified in these patients.

Viscoelastic model characterization of human cervical tissue by torsional waves

The understanding of changes in the viscoelastic properties of cervical tissue during the gestation process is a challenging problem. In this work, we explore the importance of considering the multilayer nature (epithelial and connective layers) of human cervical tissue for characterizing the viscoelastic parameters from torsional waves. For this purpose, torsional wave propagations are simulated in three multilayer cervical tissue models (pure elastic, Kelvin-Voigt (KV) and Maxwell) using the finite difference time domain method. High-speed camera measurements have been carried out in tissue-mimicking phantoms in order to obtain the boundary conditions of the numerical simulations. Finally, a parametric modeling study through a probabilistic inverse procedure was performed to rank the most plausible rheological model and to reconstruct the viscoelastic parameters. The procedure consist in comparing the experimental signals obtained in human cervical tissues using the Torsional Wave Elastography (TWE) technique with the synthetic signals from the numerical models. It is shown that the rheological model that best describes the nature of cervical tissue is the Kelvin-Voigt model. Once the most plausible model has been selected, the stiffness and viscosity parameters have been reconstructed of the epithelial and connective layers for the measurements of the 18 pregnant women, along with the thickness of the epithelial layer.

Characterization of non-linear mechanical behavior of the cornea

The objective of this study was to evaluate which hyperelastic model could best describe the non-linear mechanical behavior of the cornea, in order to characterize the capability of the non-linear model parameters to discriminate structural changes in a damaged cornea. Porcine corneas were used, establishing two different groups: control (non-treated) and NaOH-treated (damaged) corneas (n = 8). NaOH causes a chemical burn to the corneal tissue, simulating a disease associated to structural damage of the stromal layer. Quasi-static uniaxial tensile tests were performed in nasal-temporal direction immediately after preparing corneal strips from the two groups. Three non-linear hyperelastic models (i.e. Hamilton-Zabolotskaya model, Ogden model and Mooney-Rivlin model) were fitted to the stress–strain curves obtained in the tensile tests and statistically compared. The corneas from the two groups showed a non-linear mechanical behavior that was best described by the Hamilton-Zabolotskaya model, obtaining the highest coefficient of determination (R² > 0.95). Moreover, Hamilton-Zabolotskaya model showed the highest discriminative capability of the non-linear model parameter (Parameter A) for the tissue structural changes between the two sample groups (p = 0.0005). The present work determines the best hyperelastic model with the highest discriminative capability in description of the non-linear mechanical behavior of the cornea.

First isolation of Cryptococcus neoformans var. gattii, serotype C, from the environment in Colombia

The natural habitat of Cryptococcus neoformans var. gattii, serotype B in the environment was established by Australian investigators who demonstrated its association with species of Eucalyptus. The aim of the present study was to search for the habitat of this variety in a city of Colombia, where clinical cases due to this variety occur with great frequency. For a period of 5 months detritus, vegetable material and air samples in and around 68 almond trees (Terminalia catappa) located in the city were studied. C. neoformans var. gattii serotype C was the only variety isolated from two of the 68 trees sampled. These trees were positive for 4 of the 5 months during which they were studied. From the first positive sample kept under refrigeration, it was possible to isolate the fungus up to 3 months later. This is the first report of the isolation of serotype C from the environment. More studies are required in order to establish the ecological significance of this finding.