Background Pneumonia from SARS-CoV-2 is difficult to distinguish from other viral and bacterial etiologies. Broad-spectrum antimicrobials are frequently prescribed to patients hospitalized with COVID-19 which potentially acts as a catalyst for the development of antimicrobial resistance (AMR). Objectives We conducted a systematic review and meta-analysis during the first 18 months of the pandemic to quantify the prevalence and types of resistant co-infecting organisms in patients with COVID-19 and explore differences across hospital and geographic settings. Methods We searched MEDLINE, Embase, Web of Science (BioSIS), and Scopus from November 1, 2019 to May 28, 2021 to identify relevant articles pertaining to resistant co-infections in patients with laboratory confirmed SARS-CoV-2. Patient- and study-level analyses were conducted. We calculated pooled prevalence estimates of co-infection with resistant bacterial or fungal organisms using random effects models. Stratified meta-analysis by hospital and geographic setting was also performed to elucidate any differences. Results Of 1331 articles identified, 38 met inclusion criteria. A total of 1959 unique isolates were identified with 29% (569) resistant organisms identified. Co-infection with resistant bacterial or fungal organisms ranged from 0.2 to 100% among included studies. Pooled prevalence of co-infection with resistant bacterial and fungal organisms was 24% (95% CI 8–40%; n = 25 studies: I2 = 99%) and 0.3% (95% CI 0.1–0.6%; n = 8 studies: I2 = 78%), respectively. Among multi-drug resistant organisms, methicillin-resistant Staphylococcus aureus, carbapenem-resistant Acinetobacter baumannii, Klebsiella pneumoniae, Pseudomonas aeruginosa and multi-drug resistant Candida auris were most commonly reported. Stratified analyses found higher proportions of AMR outside of Europe and in ICU settings, though these results were not statistically significant. Patient-level analysis demonstrated > 50% (n = 58) mortality, whereby all but 6 patients were infected with a resistant organism. Conclusions During the first 18 months of the pandemic, AMR prevalence was high in COVID-19 patients and varied by hospital and geography although there was substantial heterogeneity. Given the variation in patient populations within these studies, clinical settings, practice patterns, and definitions of AMR, further research is warranted to quantify AMR in COVID-19 patients to improve surveillance programs, infection prevention and control practices and antimicrobial stewardship programs globally.
BackgroundThe aim of our systematic review was to investigate the association between cytomegalovirus (CMV) reactivation and outcomes in immunocompetent critically ill patients.MethodsWe searched electronic databases and gray literature for original studies and abstracts published between 1990 and October 2016. The review was limited to studies including critically ill immunocompetent patients. Cytomegalovirus reactivation was defined as positive polymerase chain reaction, pp65 antigenemia, or viral culture from blood or bronchoalveolar lavage. Selected patient-centered outcomes included mortality, duration of mechanical ventilation, need for renal replacement therapy (RRT), and nosocomial infections. Health resource utilization outcomes included intensive care unit and hospital lengths of stay.ResultsTwenty-two studies were included. In our primary analysis, CMV reactivation was associated with increased ICU mortality (odds ratio [OR], 2.55; 95% confidence interval [CI], 1.87–3.47), overall mortality (OR, 2.02; 95% CI, 1.60–2.56), duration of mechanical ventilation (mean difference 6.60 days; 95% CI, 3.09–10.12), nosocomial infections (OR, 3.20; 95% CI, 2.05–4.98), need for RRT (OR, 2.37; 95% CI, 1.31–4.31), and ICU length of stay (mean difference 8.18 days; 95% CI, 6.14–10.22). In addition, numerous sensitivity analyses were performed.ConclusionsIn this meta-analysis, CMV reactivation was associated with worse clinical outcomes and greater health resource utilization in critically ill patients. However, it remains unclear whether CMV reactivation plays a causal role or if it is a surrogate for more severe illness.
Background: Home hemodialysis is associated with lower costs to the health care system compared with conventional facility-based hemodialysis because of lower staffing and overhead costs, and by transferring the treatment cost of utilities (water and power) to the patient. The purpose of this study was to determine the utility costs of home hemodialysis and create a formula such that patients and renal programs can estimate the annual patient-borne costs involved with this type of treatment.Methods: Seven common combinations of treatment duration and dialysate flows were replicated 5 times using various combinations of home hemodialysis and reverse osmosis machines. Real-time utility (electricity and water) consumption was monitored during these simulations. A generic formula was developed to allow patients and programs to calculate a more precise estimate of utility costs based on individual combinations of dialysis intensity, frequency and utility costs unique to any patient.Results: Using typical 2014 utility costs for Edmonton, the most expensive prescription was for nocturnal home hemodialysis (8 h at 300 mL/min, 6 d/wk), which resulted in a utility cost of $1269 per year; the least expensive prescription was for conventional home hemodialysis (4 h at 500 mL/min, 3 d/wk), which cost $420 per year. Water consumption makes up most of this expense, with electricity accounting for only 12% of the cost. Interpretation:We show that a substantial cost burden is transferred to the patient on home hemodialysis, which would otherwise be borne by the renal program. Abstract ResearchResearch CMAJ OPEN E62CMAJ OPEN, 5(1)
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.