Changes in hospitalized coronavirus disease 2019 (COVID-19) patient characteristics and resource use in a system of community hospitals in the United States.

Coronavirus disease 2019 (COVID-19) has migrated to regions that were initially spared, and it is likely that different populations are currently at risk for illness. Herein, we present our observations of the change in characteristics and resource use of COVID-19 patients over time in a national system of community hospitals to help inform those managing surge planning, operational management, and future policy decisions.

The Impact of Coronavirus Disease 2019 (COVID-19) on Healthcare-Associated Infections.

BACKGROUND: The profound changes wrought by coronavirus disease 2019 (COVID-19) on routine hospital operations may have influenced performance on hospital measures, including healthcare-associated infections (HAIs). We aimed to evaluate the association between COVID-19 surges and HAI and cluster rates. METHODS: In 148 HCA Healthcare-affiliated hospitals, from 1 March 2020 to 30 September 2020, and a subset of hospitals with microbiology and cluster data through 31 December 2020, we evaluated the association between COVID-19 surges and HAIs, hospital-onset pathogens, and cluster rates using negative binomial mixed models. To account for local variation in COVID-19 pandemic surge timing, we included the number of discharges with a laboratory-confirmed COVID-19 diagnosis per staffed bed per month. RESULTS: Central line-associated blood stream infections (CLABSI), catheter-associated urinary tract infections (CAUTI), and methicillin-resistant Staphylococcus aureus (MRSA) bacteremia increased as COVID-19 burden increased. There were 60% (95% confidence interval [CI]: 23-108%) more CLABSI, 43% (95% CI: 8-90%) more CAUTI, and 44% (95% CI: 10-88%) more cases of MRSA bacteremia than expected over 7 months based on predicted HAIs had there not been COVID-19 cases. Clostridioides difficile infection was not significantly associated with COVID-19 burden. Microbiology data from 81 of the hospitals corroborated the findings. Notably, rates of hospital-onset bloodstream infections and multidrug resistant organisms, including MRSA, vancomycin-resistant enterococcus, and Gram-negative organisms, were each significantly associated with COVID-19 surges. Finally, clusters of hospital-onset pathogens increased as the COVID-19 burden increased. CONCLUSIONS: COVID-19 surges adversely impact HAI rates and clusters of infections within hospitals, emphasizing the need for balancing COVID-related demands with routine hospital infection prevention.

Hyperglycaemia increases mortality risk in non-diabetic patients with COVID-19 even more than in diabetic patients.

AIM: Diabetes has been identified as a risk factor for poor outcomes in patients with COVID-19. We examined the association of hyperglycaemia, both in the presence and absence of pre-existing diabetes, with severity and outcomes in COVID-19 patients. METHODS: Data from 74,148 COVID-19-positive inpatients with at least one recorded glucose measurement during their inpatient episode were analysed for presence of pre-existing diabetes diagnosis and any glucose values in the hyperglycaemic range (>180 mg/dl). RESULTS: Among patients with and without a pre-existing diabetes diagnosis on admission, mortality was substantially higher in the presence of high glucose measurements versus all measurements in the normal range (70-180 mg/dl) in both groups (non-diabetics: 21.7% vs. 3.3%; diabetics 14.4% vs. 4.3%). When adjusting for patient age, BMI, severity on admission and oxygen saturation on admission, this increased risk of mortality persisted and varied by diabetes diagnosis. Among patients with a pre-existing diabetes diagnosis, any hyperglycaemic value during the episode was associated with a substantial increase in the odds of mortality (OR: 1.77, 95% CI: 1.52-2.07); among patients without a pre-existing diabetes diagnosis, this risk nearly doubled (OR: 3.07, 95% CI: 2.79-3.37). CONCLUSION: This retrospective analysis identified hyperglycaemia in COVID-19 patients as an independent risk factor for mortality after adjusting for the presence of diabetes and other known risk factors. This indicates that the extent of glucose control could serve as a mechanism for modifying the risk of COVID-19 morality in the inpatient environment.

Patient characteristics and admitting vital signs associated with coronavirus disease 2019 (COVID-19)-related mortality among patients admitted with noncritical illness.

OBJECTIVE: To determine risk factors for mortality among COVID-19 patients admitted to a system of community hospitals in the United States. DESIGN: Retrospective analysis of patient data collected from the routine care of COVID-19 patients. SETTING: System of >180 acute-care facilities in the United States. PARTICIPANTS: All admitted patients with positive identification of COVID-19 and a documented discharge as of May 12, 2020. METHODS: Determination of demographic characteristics, vital signs at admission, patient comorbidities and recorded discharge disposition in this population to construct a logistic regression estimating the odds of mortality, particular for those patients characterized as not being critically ill at admission. RESULTS: In total, 6,180 COVID-19+ patients were identified as of May 12, 2020. Most COVID-19+ patients (4,808, 77.8%) were admitted directly to a medical-surgical unit with no documented critical care or mechanical ventilation within 8 hours of admission. After adjusting for demographic characteristics, comorbidities, and vital signs at admission in this subgroup, the largest driver of the odds of mortality was patient age (OR, 1.07; 95% CI, 1.06-1.08; P < .001). Decreased oxygen saturation at admission was associated with increased odds of mortality (OR, 1.09; 95% CI, 1.06-1.12; P < .001) as was diabetes (OR, 1.57; 95% CI, 1.21-2.03; P < .001). CONCLUSIONS: The identification of factors observable at admission that are associated with mortality in COVID-19 patients who are initially admitted to non-critical care units may help care providers, hospital epidemiologists, and hospital safety experts better plan for the care of these patients.