RESUMEN
Antibiotic combination therapy is a promising approach to address the urgent need for novel treatment options for infections caused by carbapenem-polymyxin-resistant Klebsiella pneumoniae (CPR-Kp). The present study aimed to investigate the synergistic potential of four cephalosporins in combination with polymyxin B (PMB). A checkerboard assay was performed to evaluate the synergistic effects of cephalexin (CLX), cefixime, cefotaxime (CTX), and cefmenoxime (CMX) in combination with PMB. Subsequently, experiments evaluating the use of CTX or CMX in combination with PMB (CTX-PMB or CMX-PMB, respectively), including growth curve and SynergyFinder analysis, antibiofilm activity assays, cell membrane integrity assays, and scanning electron microscopy, were performed. Safety assessments were also conducted, including hemolysis and toxicity evaluations, using Caenorhabditis elegans. Furthermore, an in vivo model in C. elegans was adopted to assess the treatment efficacy against CPR-Kp infections. CTX-PMB and CMX-PMB exhibited low fractional inhibitory concentration indexes ranging from 0.19 to 0.50 and from 0.25 to 1.5, respectively, and zero interaction potency scores of 37.484 and 15.076, respectively. The two combinations significantly reduced growth and biofilm formation in CPR-Kp. Neither CTX-PMB nor CMX-PMB compromised bacterial cell integrity. Safety assessments revealed a low hemolysis percentage and high survival rates in the C. elegans toxicity evaluations. The in vivo model revealed that the CTX-PMB and CMX-PMB treatments improved the survival rates of C. elegans. The synergistic effects of the CTX-PMB and CMX-PMB combinations, both in vitro and in vivo, indicate that these antibiotic pairings could represent effective therapeutic options for infections caused by CPR-Kp.
Asunto(s)
Antibacterianos , Biopelículas , Caenorhabditis elegans , Cefalosporinas , Sinergismo Farmacológico , Klebsiella pneumoniae , Pruebas de Sensibilidad Microbiana , Polimixina B , Polimixina B/farmacología , Polimixina B/uso terapéutico , Klebsiella pneumoniae/efectos de los fármacos , Antibacterianos/farmacología , Antibacterianos/uso terapéutico , Animales , Caenorhabditis elegans/efectos de los fármacos , Biopelículas/efectos de los fármacos , Cefalosporinas/farmacología , Cefalosporinas/uso terapéutico , Carbapenémicos/farmacología , Carbapenémicos/uso terapéutico , Infecciones por Klebsiella/tratamiento farmacológico , Infecciones por Klebsiella/microbiología , Farmacorresistencia Bacteriana Múltiple/efectos de los fármacos , Quimioterapia CombinadaRESUMEN
BACKGROUND AND OBJECTIVES: The acute respiratory infection caused by severe acute respiratory syndrome coronavirus disease (COVID-19) has resulted in increased mortality among pregnant, puerperal, and neonates. Brazil has the highest number of maternal deaths and a distressing fatality rate of 7.2%, more than double the country's current mortality rate of 2.8%. This study investigates the impact of the COVID-19 pandemic on the Brazilian Maternal Mortality Ratio (BMMR) and forecasts the BMMR up to 2025. METHODS: To assess the impact of the COVID-19 pandemic on the BMMR, we employed Holt-Winters, Autoregressive Integrated Moving Average (ARIMA), and Neural Networks Autoregression (NNA). We utilized a retrospective time series spanning twenty-five years (1996-2021) to forecast the BMMR under both a COVID-19 pandemic scenario and a controlled COVID-19 scenario. RESULTS: Brazil consistently exhibited high maternal mortality values (mean BMMR [1996-2019] = 57.99 ±6.34/100,000 live births) according to World Health Organization criteria. The country experienced its highest mortality peak in the historical BMMR series in the second quarter of 2021 (197.75/100,000 live births), representing a more than 200% increase compared to the previous period. Holt-Winter and ARIMA models demonstrated better agreement with prediction results beyond the sample data, although NNA provided a better fit to previous data. CONCLUSIONS: Our study revealed an increase in BMMR and its temporal correlation with COVID-19 incidence. Additionally, it showed that Holt-Winter and ARIMA models can be employed for BMMR forecasting with lower errors. This information can assist governments and public health agencies in making timely and informed decisions.