The Impact of C Reactive Protein in Prediction of the Outcome in Infective Endocarditis
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Cited by 3 publications
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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.
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.
Background Human angiotensin-converting enzyme 2 (ACE2), a type I transmembrane receptor physiologically acting as a carboxypeptidase enzyme within the renin-angiotensin system (RAS), is a critical mediator of infection by several severe acute respiratory syndrome (SARS) corona viruses. For instance, it has been demonstrated that ACE2 is the primary receptor for the SARS-CoV-2 entry to many human cells through binding to the viral spike S protein. Consequently, genetic variability in ACE2 gene has been suggested to contribute to the variable clinical manifestations in COVID-19. Many of those genetic variations result in missense variants within the amino acid sequence of ACE2. The potential effects of those variations on binding to the spike protein have been speculated and, in some cases, demonstrated experimentally. However, their effects on ACE2 protein folding, trafficking and subcellular targeting have not been established. Results In this study we aimed to examine the potential effects of 28 missense variants (V801G, D785N, R768W, I753T, L731F, L731I, I727V, N720D, R710H, R708W, S692P, E668K, V658I, N638S, A627V, F592L, G575V, A501T, I468V, M383I, G173S, N159S, N149S, D38E, N33D, K26R, I21T, and S19P) distributed across the ACE2 receptor domains on its subcellular trafficking and targeting through combinatorial approach involving in silico analysis and experimental subcellular localization analysis. Our data show that none of the studied missense variants (including 3 variants predicted to be deleterious R768W, G575V, and G173S) has a significant effect on ACE2 intracellular trafficking and subcellular targeting to the plasma membrane. Conclusion Although the selected missense variants display no significant change in ACE2 trafficking and subcellular localization, this does not rule out their effect on viral susceptibility and severity. Further studies are required to investigate the effect of ACE2 variants on its expression, binding, and internalization which might explain the variable clinical manifestations associated with the infection.
Although tigecycline is widely used in clinical practice, its efficiency and optimal dosage regimens remain controversial. The purpose of this article was to help guide tigecycline dosing in different patient subpopulations through comparing the published population pharmacokinetic models of tigecycline, as well as summarizing and determining the potential covariates that markedly influence tigecycline pharmacokinetics. In this review, literature was systematically searched from the PubMed database from inception to March 2022. The articles focusing on population pharmacokinetics for tigecycline in healthy volunteers or patients were included; finally, a total of eight studies were included in this review. NONMEM methods were used in five studies to generate the population pharmacokinetic models. Tigecycline pharmacokinetics were mostly described by a two-compartment model in these included studies. Estimated clearance and volumes of distribution of tigecycline at steady state ( Vss ) varied widely in different target patient populations, with a range of 7.5–23.1 L/h and 212.7–1087.7 L, respectively. Body-weight and creatinine clearance were the most important predictors of clearance in these studies, while other predictors include age, gender, bilirubin and aspartate aminotransferase. In conclusion, this review showed the large variability of tigecycline population pharmacokinetics, which can provide guide dosing in different target populations. For clinicians, the individual dosing adjustment should be based not only on the indication and pathogen susceptibility but also on the potential important predictors. However, more studies were needed to confirm the necessity of modified dosage regimens in different patient subpopulations.
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