Objectives: To evaluate the prevalence of hospital-onset bacteremia and fungemia (HOB), identify hospital-level predictors, and to evaluate the feasibility of an HOB metric. Methods: We analyzed 9,202,650 admissions from 267 hospitals during 2015–2020. An HOB event was defined as the first positive blood-culture pathogen on day 3 of admission or later. We used the generalized linear model method via negative binomial regression to identify variables and risk markers for HOB. Standardized infection ratios (SIRs) were calculated based on 2 risk-adjusted models: a simple model using descriptive variables and a complex model using descriptive variables plus additional measures of blood-culture testing practices. Performance of each model was compared against the unadjusted rate of HOB. Results: Overall median rate of HOB per 100 admissions was 0.124 (interquartile range, 0.00–0.22). Facility-level predictors included bed size, sex, ICU admissions, community-onset (CO) blood culture testing intensity, and hospital-onset (HO) testing intensity, and prevalence (all P < .001). In the complex model, CO bacteremia prevalence, HO testing intensity, and HO testing prevalence were the predictors most associated with HOB. The complex model demonstrated better model performance; 55% of hospitals that ranked in the highest quartile based on their raw rate shifted to a lower quartile when the SIR from the complex model was applied. Conclusions: Hospital descriptors, aggregate patient characteristics, community bacteremia and/or fungemia burden, and clinical blood-culture testing practices influence rates of HOB. Benchmarking an HOB metric is feasible and should endeavor to include both facility and clinical variables.

Background Antibacterial therapy is frequently used in patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) without evidence of bacterial infection, prompting concerns about increased antimicrobial resistance (AMR). We evaluated trends in AMR before and during the SARS-CoV-2 pandemic. Methods This multicenter, retrospective cohort analysis included hospitalized adults aged ≥18 years with &gt;1-day inpatient admission and a record of discharge or death from 271 US facilities in the BD Insights Research Database. We evaluated rates of AMR events, defined as positive cultures for select Gram-negative and Gram-positive pathogens from any source with nonsusceptibility reported by commercial panels before (7/1/19-2/29/20) and during (3/1/20-10/30/21) the SARS-CoV-2 pandemic. Results Of 5,518,666 admissions evaluated, AMR rates per 1000 admissions were 35.4 for the pre-pandemic period and 34.7 for the pandemic period (P ≤ 0.0001). In the pandemic period, AMR rates per 1000 admissions were 49.2 for SARS-CoV-2-positive admissions, 41.1 for SARS-CoV-2-negative admissions, and 25.7 for patients untested (P ≤ 0.0001). AMR rates per 1000 admissions among community-onset (CO) infections during the pandemic were lower versus pre-pandemic levels (26.1 vs 27.6; P &lt; 0.0001), while AMR rates for hospital-onset (HO) infections were higher (8.6 vs 7.7; P &lt; 0.0001), driven largely by SARS-Cov-2-positive admissions (21.8). AMR rates were associated with overall antimicrobial use, rates of positive cultures, and higher use of inadequate empiric therapy. Conclusions Although overall AMR rates did not substantially increase from pre-pandemic levels, patients tested for SARS-CoV-2 infection had a significantly higher rate of AMR and HO infections. Antimicrobial and diagnostic stewardship is key to identifying this high-risk AMR population.

Background Bloodstream infections (BSIs) are an important cause of morbidity and mortality in hospitalized patients. We evaluate incidence of community- and hospital-onset BSI rates and outcomes before and during the SARS-CoV-2 pandemic. Methods We conducted a retrospective cohort study evaluating patients who were hospitalized for ≥ 1 day with discharge or death between June 1, 2019, and September 4, 2021, across 271 US health care facilities. Community- and hospital-onset BSI and related outcomes before and during the SARS-CoV-2 pandemic, including intensive care admission rates, and overall and ICU-specific length of stay (LOS) was evaluated. Bivariate correlations were calculated between the pre-pandemic and pandemic periods overall and by SARS-CoV-2 testing status. Results Of 5,239,692 patient admissions, there were 20,113 community-onset BSIs before the pandemic (11.2/1000 admissions) and 39,740 (11.5/1000 admissions) during the pandemic (P ≤ 0.0062). Corresponding rates of hospital-onset BSI were 2,771 (1.6/1000 admissions) and 6,864 (2.0/1000 admissions; P < 0.0062). Compared to the pre-pandemic period, rates of community-onset BSI were higher in patients who tested negative for SARS-CoV-2 (15.8/1000 admissions), compared with 9.6/1000 BSI admissions among SARS-CoV-2-positive patients. Compared with patients in the pre-pandemic period, SARS-CoV-2-positive patients with community-onset BSI experienced greater ICU admission rates (36.6% vs 32.8%; P < 0.01), greater ventilator use (10.7% vs 4.7%; P < 0.001), and longer LOS (12.2 d vs 9.1 d; P < 0.001). Rates of hospital-onset BSI were higher in the pandemic vs the pre-pandemic period (2.0 vs 1.5/1000; P < 0.001), with rates as high a 7.3/1000 admissions among SARS-CoV-2-positive patients. Compared to the pre-pandemic period, SARS-CoV-2-positive patients with hospital-onset BSI had higher rates of ICU admission (72.9% vs 55.4%; P < 0.001), LOS (34.8 d vs 25.5 d; P < 0.001), and ventilator use (52.9% vs 21.5%; P < 0.001). Enterococcus species, Staphylococcus aureus, Klebsiella pneumoniae, and Candida albicans were more frequently detected in the pandemic period. Conclusions and relevance This nationally representative study found an increased risk of both community-onset and hospital-onset BSI during the SARS-CoV-2 pandemic period, with the largest increased risk in hospital-onset BSI among SARS-CoV-2-positive patients. SARS-CoV-2 positivity was associated with worse outcomes.

Objectives: To compare characteristics and outcomes associated with central-line–associated bloodstream infections (CLABSIs) and electronic health record–determined hospital-onset bacteremia and fungemia (HOB) cases in hospitalized US adults. Methods: We conducted a retrospective observational study of patients in 41 acute-care hospitals. CLABSI cases were defined as those reported to the National Healthcare Safety Network (NHSN). HOB was defined as a positive blood culture with an eligible bloodstream organism collected during the hospital-onset period (ie, on or after day 4). We evaluated patient characteristics, other positive cultures (urine, respiratory, or skin and soft-tissue), and microorganisms in a cross-sectional analysis cohort. We explored adjusted patient outcomes [length of stay (LOS), hospital cost, and mortality] in a 1:5 case-matched cohort. Results: The cross-sectional analysis included 403 patients with NHSN-reportable CLABSIs and 1,574 with non-CLABSI HOB. A positive non-bloodstream culture with the same microorganism as in the bloodstream was reported in 9.2% of CLABSI patients and 32.0% of non-CLABSI HOB patients, most commonly urine or respiratory cultures. Coagulase-negative staphylococci and Enterobacteriaceae were the most common microorganisms in CLABSI and non-CLABSI HOB cases, respectively. In case-matched analyses, CLABSIs and non-CLABSI HOB, separately or combined, were associated with significantly longer LOS [difference, 12.1–17.4 days depending on intensive care unit (ICU) status], higher costs (by $25,207–$55,001 per admission), and a >3.5-fold increased risk of mortality in patients with an ICU encounter. Conclusions: CLABSI and non-CLABSI HOB cases are associated with significant increases in morbidity, mortality, and cost. Our data may help inform prevention and management of bloodstream infections.

Objectives: To evaluate the incidence of a candidate definition of healthcare facility-onset, treated Clostridioides difficile (CD) infection (cHT-CDI) and to identify variables and best model fit of a risk-adjusted cHT-CDI metric using extractable electronic heath data. Methods: We analyzed 9,134,276 admissions from 265 hospitals during 2015–2020. The cHT-CDI events were defined based on the first positive laboratory final identification of CD after day 3 of hospitalization, accompanied by use of a CD drug. The generalized linear model method via negative binomial regression was used to identify predictors. Standardized infection ratios (SIRs) were calculated based on 2 risk-adjusted models: a simple model using descriptive variables and a complex model using descriptive variables and CD testing practices. The performance of each model was compared against cHT-CDI unadjusted rates. Results: The median rate of cHT-CDI events per 100 admissions was 0.134 (interquartile range, 0.023–0.243). Hospital variables associated with cHT-CDI included the following: higher community-onset CDI (CO-CDI) prevalence; highest-quartile length of stay; bed size; percentage of male patients; teaching hospitals; increased CD testing intensity; and CD testing prevalence. The complex model demonstrated better model performance and identified the most influential predictors: hospital-onset testing intensity and prevalence, CO-CDI rate, and community-onset testing intensity (negative correlation). Moreover, 78% of the hospitals ranked in the highest quartile based on raw rate shifted to lower percentiles when we applied the SIR from the complex model. Conclusions: Hospital descriptors, aggregate patient characteristics, CO-CDI burden, and clinical testing practices significantly influence incidence of cHT-CDI. Benchmarking a cHT-CDI metric is feasible and should include facility and clinical variables.