COVID-19 and candiduria: an investigation of the risk factors and immunological aspects.

Secondary fungal infections are frequently observed in COVID-19 patients. However, the occurrence of candiduria in these patients and its risk factors are underexplored. We evaluated the risk factors of candiduria in COVID-19 patients, including inflammatory mediators that could be used as prognostic markers. Clinical information, laboratory test results, and outcomes were collected from severely ill COVID-19 patients with and without candiduria. Candida species identification, antifungal susceptibility, and plasma inflammatory mediators' measurements were performed. Regression logistic and Cox regression model were used to evaluate the risk factors. A higher risk of longer hospitalization and mortality were observed in patients with candiduria compared to those with COVID-19 only. Candiduria was caused by Candida albicans, C. glabrata, and C. tropicalis. Isolates with intermediate susceptibility to voriconazole and resistant to caspofungin were identified. Classic factors such as the use of corticosteroids and antibacterials, the worsening of renal function, and hematological parameters (hemoglobin and platelets) were found to predispose to candiduria. The mediators IL-1ß, IL-1ra, IL-2, CXCL-8, IL-17, IFN-γ, basic FGF, and MIP-1ß were significantly increased in patients with COVID-19 and candiduria. Furthermore, IFN-γ, IL-1ra, and CXCL-8 were associated with the occurrence of candiduria in COVID-19 patients, whereas basic FGF, IL-1ß, and CXCL-8 were associated with the risk of death in these patients. Classical and immunological factors were associated with worse prognosis among patients with COVID-19 and candiduria. Some mediators, especially CXCL-8, can be a reliable biomarker of fungal coinfection and may guide the diagnostic and the treatment of these patients.

The impact of COVID-19 on antimicrobial prescription and drug resistance in fungi and bacteria.

Secondary infections are one of the complications in COVID-19 patients. We aimed to analyze the antimicrobial prescriptions and their influence on drug resistance in fungi and bacteria isolated from severely ill COVID-19 patients. Seventy-nine severely ill COVID-19 hospitalized patients with secondary bacterial or fungal infections were included. We analyzed the prescribed antimicrobial regimen for these patients and the resistance profiles of bacterial and fungal isolates. In addition, the association between drug resistance and patients' outcome was analyzed using correlation tests. The most prescribed antibacterial were ceftriaxone (90.7% of patients), vancomycin (86.0%), polymyxin B (74.4%), azithromycin (69.8%), and meropenem (67.4%). Micafungin and fluconazole were used by 22.2 and 11.1% of patients, respectively. Multidrug-resistant (MDR) infections were a common complication in severely ill COVID-19 patients in our cohort since resistant bacteria strains were isolated from 76.7% of the patients. Oxacillin resistance was observed in most Gram-positive bacteria, whereas carbapenem and cephalosporin resistance was detected in most Gram-negative strains. Azole resistance was identified among C. glabrata and C. tropicalis isolates. Patients who used more antimicrobials stayed hospitalized longer than the others. The patient's age and the number of antibacterial agents used were associated with the resistance phenotype. The susceptibility profile of isolates obtained from severely ill COVID-19 patients highlighted the importance of taking microbial resistance into account when managing these patients. The continuous surveillance of resistant/MDR infection and the rational use of antimicrobials are of utmost importance, especially for long-term hospitalized patients with COVID-19.

Method to quickly and accurately calculate absorbed dose from therapeutic and stray photon exposures throughout the entire body in individual patients.

PURPOSE: Photon radiotherapy techniques typically devote considerable attention to limiting the exposure of healthy tissues outside of the target volume. Numerous studies have shown, however, that commercial treatment planning systems (TPSs) significantly underestimate the absorbed dose outside of the treatment field. The purpose of this study was to test the feasibility of quickly and accurately calculating the total absorbed dose to the whole body from photon radiotherapy in individual patients. METHODS: We created an extended TPS by implementing a physics-based analytical model for the absorbed dose from stray photons during photon therapy into a research TPS. We configured and validated the extended TPS using measurements of 6- and 15-MV photon beams in water-box and anthropomorphic phantoms. We characterized the additional computation time required for therapeutic and stray dose calculations in a 44 × 30 × 180 cm3 water-box phantom. RESULTS: The extended TPS achieved superior dosimetric accuracy compared to the research TPS in both water and anthropomorphic phantoms, especially outside of the primary treatment field. In the anthropomorphic phantom, the extended TPS increased the generalized gamma index passing rate by a factor of 10 and decreased the median dosimetric discrepancy in the out-of-field region by a factor of 26. The extended TPS achieved an average discrepancy <1% in and near the treatment field and <1 mGy/Gy far from the treatment field in the anthropomorphic phantom. Characterization of computation time revealed that on average, the extended TPS only required 7% longer than the research TPS to calculate the total absorbed dose. CONCLUSIONS: The results of this work suggest that it is feasible to quickly and accurately calculate whole-body doses inside and outside of the therapeutic treatment field in individual patients on a routine basis using physics-based analytical dose models. This additional capability enables a more personalized approach to minimizing the risk of radiogenic late effects, such as second cancer and cardiac toxicity, as part of the treatment planning process.

Organ doses evaluation for chest computed tomography procedures with TL dosimeters: Comparison with Monte Carlo simulations.

PURPOSE: To evaluate organ doses in routine and low-dose chest computed tomography (CT) protocols using an experimental methodology. To compare experimental results with results obtained by the National Cancer Institute dosimetry system for CT (NCICT) organ dose calculator. To address the differences on organ dose measurements using tube current modulation (TCM) and fixed tube current protocols. METHODS: An experimental approach to evaluate organ doses in pediatric and adult anthropomorphic phantoms using thermoluminescent dosimeters (TLDs) was employed in this study. Several analyses were performed in order to establish the best way to achieve the main results in this investigation. The protocols used in this study were selected after an analysis of patient data collected from the Institute of Radiology of the School of Medicine of the University of São Paulo (InRad). The image quality was evaluated by a radiologist from this institution. Six chest adult protocols and four chest pediatric protocols were evaluated. Lung doses were evaluated for the adult phantom and lung and thyroid doses were evaluated for the pediatric phantom. The irradiations were performed using both a GE and a Philips CT scanner. Finally, organ doses measured with dosimeters were compared with Monte Carlo simulations performed with NCICT. RESULTS: After analyzing the data collected from all CT examinations performed during a period of 3 yr, the authors identified that adult and pediatric chest CT are among the most applied protocol in patients in that clinical institution, demonstrating the relevance on evaluating organ doses due to these examinations. With regards to the scan parameters adopted, the authors identified that using 80 kV instead of 120 kV for a pediatric chest routine CT, with TCM in both situations, can lead up to a 28.7% decrease on the absorbed dose. Moreover, in comparison to the standard adult protocol, which is performed with fixed mAs, TCM, and ultra low-dose protocols resulted in dose reductions of up to 35.0% and 90.0%, respectively. Finally, the percent differences found between experimental and Monte Carlo simulated organ doses were within a 20% interval. CONCLUSIONS: The results obtained in this study measured the impact on the absorbed dose in routine chest CT by changing several scan parameters while the image quality could be potentially preserved.