Intravenous Ceftazidime-Avibactam in Extremely Premature Neonates With Carbapenem-Resistant Enterobacteriaceae: Two Case Reports.

The increasing use of carbapenems has contributed to a notable distribution of carbapenem-resistant Enterobacteriaceae (CRE). Recently, the incidence of CRE-associated infections is increasing significantly in NICUs, which pose a grave challenge to clinical treatment. We report 2 cases of IV ceftazidimeavibactam use to treat CRE infections in extremely premature neonates. The first case was diagnosed with bacteraemia and meningitis and the second one was diagnosed with bacteraemia only. Due to the lack of neonatal-specific information for IV ceftazidime-avibactam, the usual pediatric dose (62.5 mg/kg/dose every 8 hours) was used in these patients. Clinical cure occurred in these 2 patients. Although blood cultures became sterile after starting ceftazidime-avibactam in the second case, the patient died, presumably owing to sepsis or various causes, such as prematurity and chronic lung disease. Large and randomized studies are necessary to ensure the safety and efficacy of IV ceftazidime-avibactam for the treatment of neonates with sepsis caused by multidrug resistant organisms.

Use of Early-Onset Sepsis Risk Calculator for Neonates ≥ 34 Weeks in a Large Tertiary Neonatal Centre, Saudi Arabia.

Early-onset sepsis (EOS) refers to sepsis with onset before 72 hours of life. Kaiser Permanente Calculator (KPC) or EOS risk calculator is an advanced multivariate risk model for predicting EOS in infants. Objective To examine the EOS risk calculator effect for predicting neonatal EOS, the necessity for laboratory tests, antibiotic usage, and length of hospital stay among the term and late-preterm newborns. Method In this cross-sectional study, we evaluated 44 cases of neonates ≥34 weeks of gestation started on empiric antibiotics within 72 hours after birth due to suspected EOS at the neonatal intensive care unit (NICU). The study site is a 1,500-bed teaching hospital, with around 4,500 annual deliveries, 70 beds in the level II and level III tertiary care NICU. We calculated the risk of the incidence of EOS as one per 1000 live births. Then we retrospectively calculated the probability of neonatal early-onset infection at birth based on the EOS risk calculator and assigned each neonate to one of the recommended categories of the calculator. The primary outcome was to evaluate the infection risk calculator's effect for predicting neonatal EOS and antibiotic usage among the term and late-preterm newborns ≥34 weeks of gestation. Results In our data, EOS calculator showed unnecessary antibiotic usage for 12 (27.3%) neonates [relative risk reduction (RRR) 27.2%; 95% confidence interval (CI) 20.3% - 35.7%)]. EOS risk calculator implementation may decrease in the number of NICU admission (RRR 20.4%; 95% CI 14.3% - 28%), laboratory tests (RRR 20.4%; 95% CI 14.3% - 28%), and length of stay (RRR 25%; 95% CI 38% - 95%). Conclusion EOS calculator could be considered a strategic and objective implementation for managing EOS that can limit unnecessary laboratory tests, reduce antibiotic usage, and length of stay related to EOS. Our findings ensure a multicenter, randomized study evaluating the safety and general use of the calculator for EOS sepsis in Saudi Arabia's clinical practice.

Clinical characteristics and in-hospital outcome of medical staff infected with COVID-19 in Saudi Arabia. A retrospective single-center study.

OBJECTIVES: To analyze the clinical characteristics and in-hospital outcomes among coronavirus disease 2019 (COVID-19) positive medical staff compared with those of public. Methods: A total of 108 COVID-19-positive medical staff patients were included in the study from March 23, 2020 to June 15, 2020. Patients were analyzed for demographic data, clinical presentations, and in-hospital outcomes and compared against 661 COVID-19-infected patients of non-medical personel. Results: Mean age of medical staff patients was 44.05±13.9 years, most of whom were women (63.9%). The infected medical staff members consisted of 63 nurses (58.3%), 37 physicians (34.3%), 5 technicians (4.6%), and 3 pharmacists (2.8%). Smoking (60.2%) was the most frequent, followed by diabetes mellitus (37%). Of 108 COVID-19 infected medical staff, 18 (16.6%) were isolated in the intensive care unit (ICU), of which 14 (77.8%) were male, 16 (88.9%) were smokers, and 16 (88.9%) presented with pneumonia. Fatality ratio among medical staff patients was 4.6%. Male gender with odds ratios (OR) of 7.771 and 95% confidence intervals (CI) of 0.837-72.195 and a history of chronic kidney disease of (OR=10.778, 95% CI: 1.503-77.287) were predictors of death among the medical staff group. Conclusion: The incidence of COVID-19 infection among medical staff is quite high, but the occurrence of extreme illness and death is significantly low compared with the general community. Training should be implemented for all hospital staff on infection prevention techniques. Reliable and quick access for testing medical personnel is essential to maintain health, safety, and availability of health care workers during this pandemic.