The Impact of Concomitant Empiric Cefepime on Patient Outcomes of Methicillin-Resistant Staphylococcus Aureus Bloodstream Infections Treated With Vancomycin

Background: Data suggest that vancomycin + β-lactam combinations improve clearance of methicillin-resistant Staphylococcus aureus(MRSA) bloodstream infections (BSIs). However, it is unclear which specific β-lactams confer benefit. This analysis evaluates the impact of concomitant empiric cefepime on outcomes of MRSA BSIs treated with vancomycin. Methods: Retrospective cohort study of adults with MRSA BSI from 2006 to 2017. Vancomycin + cefepime therapy was defined as ≥24 hours of cefepime during the first 72 hours of vancomycin. The primary outcome was microbiologic failure, defined as BSI duration ≥7 days and/or 60-day recurrence. Multivariable logistic regression was used to evaluate the association between vancomycin + cefepime therapy and binary outcomes. Cause-specific and subdistribution hazard models were used to evaluate the association between vancomycin + cefepime and BSI clearance. Results: Three hundred fifty-eight patients were included, 129 vancomycin and 229 vancomycin + cefepime. Vancomycin + cefepime therapy was independently associated with reduced microbiologic failure (adjusted odds ratio [aOR], 0.488; 95% confidence interval [CI], 0.271-0.741). This was driven by a reduction in the incidence of BSI durations ≥7 days (vancomycin + cefepime aOR, 0.354; 95% CI, 0.202-0.621). Vancomycin + cefepime had no association with 30-day mortality (aOR, 0.952; 95% CI, 0.435-2.425). Vancomycin + cefepime was associated with faster BSI clearance in both cause-specific (HR, 1.408; 95% CI, 1.125-1.762) and subdistribution hazard models (HR, 1.264; 95% CI, 1.040-1.536). Conclusions: Concomitant empiric cefepime improved MRSA BSI clearance and may be useful as the β-lactam component of synergistic vancomycin + β-lactam regimens when empiric or directed gram-negative coverage is desired

Hydrochars as Emerging Biofuels: Recent Advances and Application of Artificial Neural Networks for the Prediction of Heating Values

In this study, the growing scientific field of alternative biofuels was examined, with respect to hydrochars produced from renewable biomasses. Hydrochars are the solid products of hydrothermal carbonization (HTC) and their properties depend on the initial biomass and the temperature and duration of treatment. The basic (Scopus) and advanced (Citespace) analysis of literature showed that this is a dynamic research area, with several sub-fields of intense activity. The focus of researchers on sewage sludge and food waste as hydrochar precursors was highlighted and reviewed. It was established that hydrochars have improved behavior as fuels compared to these feedstocks. Food waste can be particularly useful in co-hydrothermal carbonization with ash-rich materials. In the case of sewage sludge, simultaneous P recovery from the HTC wastewater may add more value to the process. For both feedstocks, results from large-scale HTC are practically non-existent. Following the review, related data from the years 2014–2020 were retrieved and fitted into four different artificial neural networks (ANNs). Based on the elemental content, HTC temperature and time (as inputs), the higher heating values (HHVs) and yields (as outputs) could be successfully predicted, regardless of original biomass used for hydrochar production. ANN3 (based on C, O, H content, and HTC temperature) showed the optimum HHV predicting performance (R2 0.917, root mean square error 1.124), however, hydrochars’ HHVs could also be satisfactorily predicted by the C content alone (ANN1, R2 0.897, root mean square error 1.289)

Evaluation of the INCREMENT-CPE, Pitt Bacteremia and qPitt Scores in Patients with Carbapenem-Resistant Enterobacteriaceae Infections Treated with Ceftazidime–Avibactam

Background The aim of this study was to evaluate the predictive performance of the INCREMENT-CPE (ICS), Pitt bacteremia score (PBS) and qPitt for mortality among patients treated with ceftazidime–avibactam for carbapenem-resistant Enterobacteriaceae (CRE) infections. Methods Retrospective, multicenter, cohort study of patients with CRE infections treated with ceftazidime–avibactam between 2015 and 2019. The primary outcome was 30-day all-cause mortality. Predictive performance was determined by assessing discrimination, calibration and precision. Results In total, 109 patients were included. Thirty-day mortality occurred in 18 (16.5%) patients. There were no significant differences in discrimination of the three scores [area under the curve (AUC) ICS 0.7039, 95% CI 0.5848–0.8230, PBS 0.6893, 95% CI 0.5709–0.8076, and qPitt 0.6847, 95% CI 0.5671–0.8023; P > 0.05 all pairwise comparisons]. All scores showed adequate calibration and precision. When dichotomized at the optimal cut-points of 11, 3, and 2 for the ICS, PBS, and qPitt, respectively, all scores had NPV > 90% at the expense of low PPV. Patients in the high-risk groups had a relative risk for mortality of 3.184 (95% CI 1.35–8.930), 3.068 (95% CI 1.094–8.606), and 2.850 (95% CI 1.016–7.994) for the dichotomized ICS, PBS, and qPitt, scores respectively. Treatment-related variables (early active antibiotic therapy, combination antibiotics and renal ceftazidime–avibactam dose adjustment) were not associated with mortality after controlling for the risk scores. Conclusions In patients treated with ceftazidime–avibactam for CRE infections, mortality risk scores demonstrated variable performance. Modifications to scoring systems to more accurately predict outcomes in the era of novel antibiotics are warranted

Hydrochars as Emerging Biofuels: Recent Advances and Application of Artificial Neural Networks for the Prediction of Heating Values

In this study, the growing scientific field of alternative biofuels was examined, with respect to hydrochars produced from renewable biomasses. Hydrochars are the solid products of hydrothermal carbonization (HTC) and their properties depend on the initial biomass and the temperature and duration of treatment. The basic (Scopus) and advanced (Citespace) analysis of literature showed that this is a dynamic research area, with several sub-fields of intense activity. The focus of researchers on sewage sludge and food waste as hydrochar precursors was highlighted and reviewed. It was established that hydrochars have improved behavior as fuels compared to these feedstocks. Food waste can be particularly useful in co-hydrothermal carbonization with ash-rich materials. In the case of sewage sludge, simultaneous P recovery from the HTC wastewater may add more value to the process. For both feedstocks, results from large-scale HTC are practically non-existent. Following the review, related data from the years 2014–2020 were retrieved and fitted into four different artificial neural networks (ANNs). Based on the elemental content, HTC temperature and time (as inputs), the higher heating values (HHVs) and yields (as outputs) could be successfully predicted, regardless of original biomass used for hydrochar production. ANN3 (based on C, O, H content, and HTC temperature) showed the optimum HHV predicting performance (R2 0.917, root mean square error 1.124), however, hydrochars’ HHVs could also be satisfactorily predicted by the C content alone (ANN1, R2 0.897, root mean square error 1.289)

Multidrug-resistant Pseudomonas aeruginosa lower respiratory tract infections in the intensive care unit: Prevalence and risk factors

Intensive care unit (ICU) admission is a risk for multidrug-resistant (MDR) Pseudomonas aeruginosa, but factors specific to critically ill pneumonia patients are not fully characterized. Objective was to determine risk factors associated with MDR P. aeruginosa pneumonia among ICU patients. This was a retrospective case-control study of P. aeruginosa pneumonia in the ICU; cystic fibrosis and colonizers were excluded. Risk factors included comorbid conditions and prior healthcare exposure (anti-pseudomonal antibiotics, hospitalizations, nursing home, P. aeruginosa colonization/infection, mechanical ventilation). Of 200 patients, 47 (23.5%) had MDR P. aeruginosa pneumonia. Independent predictors for MDR were ≥24h antibiotics in the preceding 90days (carbapenems, fluoroquinolones, and piperacillin-tazobactam) (odds ratio, 3.6 [95% CI, 1.6-8.1]) and nursing home residence (2.3 [1.1-4.9]). MDR P. aeruginosa remains prevalent among ICU patients with pneumonia. Given poor outcomes with delayed therapy, patients should be thoroughly assessed for prior anti-pseudomonal antibiotic exposure and nursing home residency