Background: Given the mortality risk in COVID-19 patients, it is necessary to estimate the impact of glycemic control on mortality rates among inpatients by designing and implementing evidence-based blood glucose (BG) control methods. There is evidence to suggest that COVID-19 patients with hyperglycemia are at risk of mortality, and glycemic control may improve outcomes. However, the optimal target range of blood glucose levels in critically ill COVID-19 patients remains unclear, and further research is needed to establish the most effective glycemic control strategies in this population. Methods: The investigation was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Data sources were drawn from Google Scholar, ResearchGate, PubMed (MEDLINE), Cochrane Library, and Embase databases. Randomized controlled trials, non-randomized controlled trials, retrospective cohort studies, and observational studies with comparison groups specific to tight glycemic control in COVID-19 patients with and without diabetes. Results: Eleven observational studies (26,953 patients hospitalized for COVID-19) were included. The incidence of death was significantly higher among COVID-19 patients diagnosed with diabetes than those without diabetes (OR = 2.70 [2.11, 3.45] at a 95% confidence interval). Incidences of death (OR of 3.76 (3.00, 4.72) at a 95% confidence interval) and complications (OR of 0.88 [0.76, 1.02] at a 95% confidence interval) were also significantly higher for COVID-19 patients with poor glycemic control. Conclusion: These findings suggest that poor glycemic control in critically ill patients leads to an increased mortality rate, infection rate, mechanical ventilation, and prolonged hospitalization.
To explore the racial and ethnic differences in the occurrence of healthcare-associated infections (HAIs) captured using the most recent available National Inpatient Survey (NIS) data for 2016-2017. METHODS: Using merged NIS data from 2016-2017, for adult patients (18 and above), 9 HAI measures-surgical site infection (SSI), central line-associated bloodstream infections (CLABSI), catheter-associated urinary tract infection (CAUTI), ventilatorassociated pneumonia (VAP), hospital-acquired pneumonia (HAP), methicillin-resistant staphylococcus aureus (MRSA) pneumonia, postoperative pneumonia (POP), MRSA sepsis and clostridium difficile infection (c. diff) were explored using ICD-10 codes. All 9 HAI measures were combined into a composite measure, hospital-associated infection (HAI), and the percent incidence was calculated. Using a binomial regression model and controlling for potentially confounding comorbidities, the odds of HAI were estimated among racial/ethnic groups.
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