Hospital-onset Infections Research Articles

Measuring the Direct Medical Costs of Hospital-Onset Infections Using an Analogy Costing Framework.

The majority of recent estimates on the direct medical cost attributable to hospital-onset infections (HOIs) has focused on device- or procedure-associated HOIs. The attributable costs of HOIs that are not associated with device use or procedures have not been extensively studied. We developed simulation models of attributable cost for 16 HOIs and estimated the total direct medical cost, including nondevice-related HOIs in the USA for 2011 and 2015. We used total discharge costs associated with HOI-related hospitalization from the National Inpatient Sample and applied an analogy costing methodology to develop simulation models of the costs attributable to HOIs. The mean attributable cost estimate from the simulation analysis was then multiplied by previously published estimates of the number of HOIs for 2011 and 2015 to generate national estimates of direct medical costs. After adjusting all estimates to 2017 US dollars, attributable cost estimates for select nondevice-related infections attributable cost estimates ranged from $7661 for ear, eye, nose, throat, and mouth (EENTM) infections to $27,709 for cardiovascular system infections in 2011; and from $8394 for EENTM to $26,445 for central nervous system infections in 2016 (based on 2015 incidence data). The national direct medical costs for all HOIs were $14.6 billion in 2011 and $12.1 billion in 2016. Nondevice- and nonprocedure-associated HOIs comprise approximately 26-28% of total HOI costs. Results suggest that nondevice- and nonprocedure-related HOIs result in considerable costs to the healthcare system.

Predictive biomarker of mortality in children with infectious diseases: a nationwide data analysis.

Biomarkers play a crucial role in the early identification of high-risk children with infectious diseases. Despite their importance, few studies evaluated biomarkers' capabilities in predicting mortality. The aim of this study was to evaluate the biomarkers' predictive capabilities for mortality in children with infectious diseases. From an inpatient database covering ≥200 acute-care hospitals in Japan, we included children who underwent blood culture, and received antimicrobial treatment between 2012 and 2021. Biomarkers' results from the day of the initial blood culture were used. Biomarker discriminative capabilities were assessed using the area under receiver operating characteristic curves (AUCs). Of 11,365 eligible children with presumed infection, 1,378 (12.1%) required mechanical ventilation or vasoactive agents within 2 days of blood culture, and 100 (0.9%) died during admission. Of all children, 10,348 (91.1%) had community-onset infections and 1,017 (8.9%) had hospital-onset infections. C-reactive protein and white blood cell demonstrated limited discriminatory capabilities with AUCs of 0.44 [95% confidence interval (CI): 0.38-0.51] and 0.45 (95% CI: 0.39-0.52). In contrast, pH, prothrombin time-international normalized ratio, and procalcitonin exhibited strong discriminatory capabilities with AUCs of 0.77 (95% CI: 0.65-0.90), 0.77 (95% CI: 0.70-0.84) and 0.76 (95% CI: 0.29-1.00). In conclusions, our real-world data analysis suggested that C-reactive protein and white blood cell may not be reliable indicators for predicting mortality in children with presumed infection. These findings could warrant future studies exploring promising biomarkers, including those from blood gas analyses, coagulation studies and procalcitonin.

Hospital-Onset Clostridioides difficile infection in chronic kidney disease patients

Introduction: Hospital-onset Clostridioides difficile infection (HO-CDI), reported as laboratory-identified (LabID) event, is common in patients with chronic kidney disease (CKD), especially those with end-stage renal disease (ESRD), and is associated with prolonged length of hospitalization and more severe disease. CKD patients are at increased of developing CDI due to frequent antimicrobial and healthcare exposures. The objective of this study was to assess recent trends of HO-CDI in patients on a nephrology unit at our academic, tertiary care institution. Methods: Retrospective cross-sectional study of patients with HO-CDI who were hospitalized on a nephrology unit between January 2021 to December 2023. Collected variables included: demographic data, characterization of HO-CDI risk factors, infection and diagnosis (including prior history of CDI, toxin versus nucleic acid amplification test [NAAT] positivity, number of loose stools), CDI rate (defined as CDI count/patient days x1000), standardized antimicrobial administration ratio (SAAR) for high-risk for CDI antimicrobials (defined by the National Healthcare Safety Network), and infection prevention and control (IPC) practices, including hand hygiene audit rates. Results: A total of 30 HO-CDI infections were reported on the nephrology unit [Table], with 8 occurring in 2021, 5 in 2022, and 17 in 2023. The median age of patients was 70.8 (range: 37-96) years, and most patients (57%) were female. The majority of patients were admitted from home (73%), and two patients (7%) had a history of CDI in the last 6 months. Among the CDI cases, 60% were NAAT positive and toxin negative, and only 50% had >3 bowel movements (BM) within 24 hours prior to the positive test. Ten percent received promotility agents prior to testing. Most cases (77%) occurred when other CDI patients were on the unit. Hand hygiene compliance rates averaged 81% over the three-year period [Figure 1A]. Eight-four per cent of patients received antibiotics within 30 days of CDI diagnosis; SAAR was >1 for quarters 2 and 4 in 2022, and quarter 1 in 2023 [Figure 1B]. Conclusion: On our nephrology unit, patients often had < 3 BM within 24 hours of CDI diagnosis, and 60% of cases were toxin-negative, NAAT-positive, suggesting possible C. difficile colonization, rather than true infection. In addition, an elevated SAAR correlated with high CDI rates. Multicomponent interventions may be required to reduce the rates of HO-CDI in CKD patients. Opportunities include emphasis on diagnostic and antimicrobial stewardship, environmental cleaning and adherence to IPC practices, including hand hygiene.

Understanding the Impact of Narrow Spectrum Beta-Lactam Use on Overall and Broad-Spectrum Antimicrobial Utilization in South Carolina

Background: The standardized antimicrobial administration ratio (SAAR) is a metric utilized to measure antimicrobial use within and between hospitals by comparing observed to predicted antimicrobial days of therapy. However, it remains unknown whether narrow-spectrum beta-lactam (NSBL) use adds to overall antimicrobial utilization or substitutes broad-spectrum agents. This muti-hospital cohort study examined the impact of NSBL use on overall antimicrobial utilization and the correlation between the use of NSBL and various broad-spectrum antimicrobial categories in South Carolina (SC) hospitals. Methods: SAARs were collected from all hospitals in SC that reported antimicrobial use (AU) data to the National Healthcare Safety Network (NHSN) between 2017 and 2021. SAARs collected included: overall SAAR, broad-spectrum agents predominantly used for hospital-onset infections (BSHO), broad-spectrum agents predominantly used for community-acquired infections (BSCA), NSBL, and antibacterial agents posing the highest risk for Clostridioides difficile infection (CDI). Category SAARs were combined to include data in both the adult intensive care unit (ICU) and adult wards using the formula: [(total observed antimicrobial days ICU + total observed antimicrobial days ward) / (total predicted antimicrobial days ICU + total predicted antimicrobial days wards)]. Pearson correlation coefficient (r) was used to examine the correlation between various SAARs categories. Results: A total of 38 hospitals in South Carolina reported AU to NHSN at least during one calendar year during the study period. The use of NSBL agents was negatively correlated with the use of BSHO (r = -0.596, p < 0.001), BSCA (r = -0.543, p < 0.001), and high-risk CDI antibiotics (r = -0.601, p < 0.001). Moreover, the use of NSBL agents did not correlate with the overall SAAR (r = 0.008, p = 0.93), whereas the use of BSHO (r = 0.587, p < 0.001), BSCA (r = 0.494, p < 0.001), and high-risk CDI agents (r = 0.464; p < 0.001) positively correlated with the overall SAAR. Conclusion: In South Carolina hospitals, the use of NSBLs does not contribute to additional antibiotic use overall as it seems to replace broad-spectrum antimicrobials in various categories. By de-escalating from broad-spectrum agents to NSBL agents, one can improve antimicrobial use without negatively impacting the overall SAAR. This observation encourages implementation of antimicrobial stewardship interventions that increase utilization of NSBLs, when appropriate, such as de-escalation of antimicrobial therapy among others without concerns for increasing the SAAR for overall antibiotic use.

ISR 87 - Timing of Catheter-Associated Urinary Tract Infections (CAUTIs) and Non-CAUTI Hospital-Onset Urinary Tract Infections – Implications for Mitigating Infection Risk

ISR 87 - Timing of Catheter-Associated Urinary Tract Infections (CAUTIs) and Non-CAUTI Hospital-Onset Urinary Tract Infections – Implications for Mitigating Infection Risk

CDC’s Hospital-Onset Clostridioides difficile Prevention Framework in a Regional Hospital Network

Despite modest reductions in the incidence of hospital-onset Clostridioides difficile infection (HO-CDI), CDI remains a leading cause of health care-associated infection. As no single intervention has proven highly effective on its own, a multifaceted approach to controlling HO-CDI is needed. To assess the effectiveness of the Centers for Disease Control and Prevention's Strategies to Prevent Clostridioides difficile Infection in Acute Care Facilities Framework (hereafter, the Framework) in reducing HO-CDI incidence. This quality improvement study was performed within the Duke Infection Control Outreach Network from July 1, 2019, through March 31, 2022. In all, 20 hospitals in the network participated in an implementation study of the Framework recommendations, and 26 hospitals did not participate and served as controls. The Framework has 39 discrete intervention categories organized into 5 focal areas for CDI prevention: (1) isolation and contact precautions, (2) CDI confirmation, (3) environmental cleaning, (4) infrastructure development, and (5) antimicrobial stewardship engagement. Monthly teleconferences supporting Framework implementation for the participating hospitals. Primary outcomes were HO-CDI incidence trends at participating hospitals compared with controls and postintervention HO-CDI incidence at intervention sites compared with rates during the 24 months before the intervention. The study sample included a total of 2184 HO-CDI cases and 7 269 429 patient-days. In the intervention cohort of 20 participating hospitals, there were 1403 HO-CDI cases and 3 513 755 patient-days, with a median (IQR) HO-CDI incidence of 2.8 (2.0-4.3) cases per 10 000 patient-days. The first analysis included an additional 3 755 674 patient-days and 781 HO-CDI cases among the 26 controls, with a median (IQR) HO-CDI incidence of 1.1 (0.7-2.7) case per 10 000 patient-days. The second analysis included an additional 2 538 874 patient-days and 1751 HO-CDI cases, with a median (IQR) HO-CDI incidence of 5.9 (2.7-8.9) cases per 10 000 patient-days, from participating hospitals 24 months before the intervention. In the first analysis, intervention sites had a steeper decline in HO-CDI incidence over time relative to controls (yearly incidence rate ratio [IRR], 0.79 [95% CI, 0.67-0.94]; P = .01), but the decline was not temporally associated with study participation. In the second analysis, HO-CDI incidence was declining in participating hospitals before the intervention, and the rate of decline did not change during the intervention. The degree to which hospitals implemented the Framework was associated with steeper declines in HO-CDI incidence (yearly IRR, 0.95 [95% CI, 0.90-0.99]; P = .03). In this quality improvement study of a regional hospital network, implementation of the Framework was not temporally associated with declining HO-CDI incidence. Further study of the effectiveness of multimodal prevention measures for controlling HO-CDI is warranted.

Comparative epidemiology of hospital-onset bloodstream infections (HOBSIs) and central line-associated bloodstream infections (CLABSIs) across a three-hospital health system.

To evaluate the comparative epidemiology of hospital-onset bloodstream infection (HOBSI) and central line-associated bloodstream infection (CLABSI). Retrospective observational study of HOBSI and CLABSI across a three-hospital healthcare system from 01/01/2017 to 12/31/2021. HOBSIs were identified as any non-commensal positive blood culture event on or after hospital day 3. CLABSIs were identified based on National Healthcare Safety Network (NHSN) criteria. We performed a time-series analysis to assess comparative temporal trends among HOBSI and CLABSI incidence. Using univariable and multivariable regression analyses, we compared demographics, risk factors, and outcomes between non-CLABSI HOBSI and CLABSI, as HOBSI and CLABSI are not exclusive entities. HOBSI incidence increased over the study period (IRR 1.006 HOBSI/1,000 patient days; 95% CI 1.001-1.012; P=.03), while no change in CLABSI incidence was observed (IRR .997 CLABSIs/1,000 central line days, 95% CI .992-1.002, P=.22). Differing demographic, microbiologic, and risk factor profiles were observed between CLABSIs and non-CLABSI HOBSIs. Multivariable analysis found lower odds of mortality among patients with CLABSIs when adjusted for covariates that approximate severity of illness (OR .27; 95% CI .11-.64; P<.01). HOBSI incidence increased over the study period without a concurrent increase in CLABSI in our study population. Furthermore, risk factor and outcome profiles varied between CLABSI and non-CLABSI HOBSI, which suggest that these metrics differ in important ways worth considering if HOBSI is adopted as a quality metric.

Catheter-associated urinary tract infections (CAUTIs) and non-CAUTI hospital-onset urinary tract infections: Relative burden, cost, outcomes and related hospital-onset bacteremia and fungemia infections.

To describe the relative burden of catheter-associated urinary tract infections (CAUTIs) and non-CAUTI hospital-onset urinary tract infections (HOUTIs). A retrospective observational study of patients from 43 acute-care hospitals was conducted. CAUTI cases were defined as those reported to the National Healthcare Safety Network. Non-CAUTI HOUTI was defined as a positive, non-contaminated, non-commensal culture collected on day 3 or later. All HOUTIs were required to have a new antimicrobial prescribed within 2 days of the first positive urine culture. Outcomes included secondary hospital-onset bacteremia and fungemia (HOB), total hospital costs, length of stay (LOS), readmission risk, and mortality. Of 549,433 admissions, 434 CAUTIs and 3,177 non-CAUTI HOUTIs were observed. The overall rate of HOB likely secondary to HOUTI was 3.7%. Total numbers of secondary HOB were higher in non-CAUTI HOUTIs compared to CAUTI (101 vs 34). HOB secondary to non-CAUTI HOUTI was more likely to originate outside the ICU compared to CAUTI (69.3% vs 44.1%). CAUTI was associated with adjusted incremental total hospital cost and LOS of $9,807 (P < .0001) and 3.01 days (P < .0001) while non-CAUTI HOUTI was associated with adjusted incremental total hospital cost and LOS of $6,874 (P < .0001) and 2.97 days (P < .0001). CAUTI and non-CAUTI HOUTI were associated with deleterious outcomes. Non-CAUTI HOUTI occurred more often and was associated with a higher facility aggregate volume of HOB than CAUTI. Patients at risk for UTIs in the hospital represent a vulnerable population who may benefit from surveillance and prevention efforts, particularly in the non-ICU setting.

Quantifying racial disparities in risk of invasive Staphylococcus aureus infection in Metropolitan Atlanta, Georgia, during the 2020-2021 coronavirus disease 2019 (COVID-19) pandemic.

We estimated the racial disparity in rates of invasive S. aureus infections based on community coronavirus disease 2019 (COVID-19) rates at the county level. Our data suggest that COVID-19 infection burden (1) affects not only hospital-onset MRSA invasive infection risk but also community-onset S. aureus invasive infection risk and (2) affects Black residents ∼60% more than White residents.

2466. The Evolution of Candidemia during the COVID-19 Pandemic in Connecticut

Abstract Background Candidemia is a life-threatening bloodstream infection. The changing epidemiology of candidemia during the COVID-19 pandemic has not been well described. The goal of this study is to describe trends in candidemia epidemiology throughout various phases of the COVID-19 pandemic in Connecticut. Methods Using statewide surveillance we identified all adult Connecticut residents with candidemia between January 2020 and October 2022. Cases were aggregated by four-month intervals. Three surges of COVID-19 (Initial, Delta, and Omicron variant surges) were identified based on statewide COVID-19 case numbers. Incidence rate ratios (IRR) were calculated to compare the incidence rate (IR) of candidemia during surge periods to the IR of candidemia in non-surge periods (four-month intervals before and after surges). Patient demographics and clinical characteristics were compared using chi-square analysis. Results 721 candidemia cases were included in the analysis (255 in 2020, 290 in 2021, and 176 in 2022). The IR of candidemia during the Initial surge was 1.49 times higher than the 4 months after the Initial surge (95% CI: 1.09-2.03). The IR of candidemia during the Delta surge was 1.46 times higher than the preceding 4 months (95% CI: 1.07-1.99) and 1.13 times higher than the 4 months after the Delta surge (95% CI: 0.84-1.51). The IR candidemia during the Omicron surge was 1.05 times higher than the preceding 4 months (95% CI: 0.78-1.41) but 1.56 times higher than 4 months after the surge (95% CI: 1.12-2.17). During surge periods candidemia was more frequently associated with persons of non-white race/ethnicity, hospital-onset infection, mechanical ventilation and mortality (all p &amp;lt; 0.05). Conclusion We identified an association between COVID-19 surges and increased rates of candidemia. Candidemia cases during surge periods occurred more frequently among non-white persons, were more likely to have hospital-onset and were more severe suggesting that COVID-19 treatments or interventions may have impacted candidemia rates. Further study is needed to understand factors that resulted in different IRs of candidemia during various phases of the COVID-19 pandemic to inform strategies to prevent candidemia during future public health crises. Disclosures All Authors: No reported disclosures

1428. The proportion of excess hospital-onset antibiotic-resistant infections attributable to patients diagnosed with COVID-19 in U.S. hospitals, 2019-2021

Abstract Background Hospital-onset (HO) antibiotic-resistant (AR) infections increased in 2020. We examined what proportion of HO AR infection increases could be attributed to patients with COVID-19. Methods HO cases were identified using PINC-AI microbiology data from a cohort of 240 hospitals in 2019-2021. The data were divided into a pre-pandemic period (Jan 2019-Jan 2020) and a pandemic period (Apr 2020-Dec 2021). We built a predictive model for HO AR infections using multivariable logistic regression including patient and facility demographics. The predictive model was built using pre-pandemic period data and applied to pandemic period patients not diagnosed with COVID-19 and pandemic period patients with COVID-19 (COVID cohort). The excess number of HO AR infections (observed – expected) was determined for each cohort and the proportion of excess attributable to the COVID cohort was calculated. We then repeated the predictive model process adding patient clinical characteristics in the model. Recycled predictions were used to estimate confidence intervals. Results Before adjusting for clinical characteristics, MRSA had the highest proportion of excess HO AR cases attributable to the COVID cohort (100%; 95% CI 100-100%). ESBL (49%; 95% CI 45-53%), CRAsp (48%; 95% CI 44-54%), MDR Pseudomonas (48%; 95% CI 43-54%) and CRE (52%; 95% CI 45-61%) all had similar proportions of excess (Table). VRE had the lowest proportion of excess (24%; 95% CI 20-29%). After adjusting for clinical characteristics, the proportion of excess attributable to the COVID cohort decreased to 0% for MRSA, CRE, and VRE. CRAsp had the highest proportion of excess after adjusting (40%; 95% CI 35-45%); ESBL (15%; 95% CI 10-21%) and MDR Pseudomonas (8%; 95% CI 0-15%) had lower but non-zero proportions of excess. Rates of excess cases attributable to the COVID cohort can be seen in the Figure.Table.Model results with and without adjusting for patient clinical characteristics of the observed and excess hospital-onset (HO) antibiotic-resistant (AR) cases stratified by patients with and without COVID-19 as well as the proportion of excess HO AR cases attributable to patients diagnosed with COVID-19 (with 95% confidence intervals), by pathogen.Figure.Comparison of the rates of excess hospital-onset (HO) antibiotic-resistant (AR) cases diagnosed with COVID-19 per 10,000 COVID-19 discharges to the proportion of excess HO AR cases attributable to patients diagnosed with COVID-19 (with 95% confidence intervals) for 6 pathogens, methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant Enterococcus spp. (VRE), carbapenem-resistant Enterobacteriaceae (CRE), extended-spectrum β-lactamase (ESBL)-producing Enterobacteriaceae, carbapenem-resistant Acinetobacter spp. (CRAsp), and multidrug-resistant Pseudomonas aeruginosa (MDR Pseudomonas) without adjusting for clinical characteristics. Conclusion Patients with COVID-19 accounted for 20-100% of excess HO AR infections, varying by pathogen. In COVID-19 patients, increases in HO AR infections were largely due to patients’ clinical characteristics such as length of stay and comorbidities. In non-COVID-19 patients, increases in HO AR infections were not entirely explained by clinical characteristics, and might be due to factors such as lapses in infection prevention practices. Disclosures All Authors: No reported disclosures

2455. National Trends in the Rates of Drug-resistant Bacteria Commonly Associated with Healthcare in U.S. Acute Care Hospitals, 2019-2021

Abstract Background The 2022 Special Report: COVID-19 U.S. Impact on Antimicrobial Resistance identified significant increases in the rate of hospital-onset (HO) infections during the year 2020 for bacteria commonly associated with healthcare. Using the same data sources and methodology, we provide updated estimates for the year 2021. Methods We identified a cohort of patients from the PINC AI PHD and BD Research Insights databases with a clinical culture yielding an isolate of an organism of interest with accompanying susceptibility testing. Isolates from patients with no culture yielding the same resistance phenotype of interest in the previous 14 days were counted as an incident case. Community-onset (CO) cultures were obtained ≤ day 3 of hospitalization; HO cultures were obtained ≥ day 4. We used a raking-procedure to determine weights for extrapolating the number of discharges included in our sample to match the distribution of discharges, stratified by bed size, U.S. census division, urban/rural designation, and teaching status, for U.S. hospitals included in the American Hospital Association survey. We examined temporal trends using a multivariable logistic model incorporating a survey design with the corresponding weights and hospital designation as the specific cluster controlling for hospital characteristics, month of discharge, proportion of patients in specific age group, proportion of male patients, and database. Results were stratified by HO and CO. Results From 2019-2021, the overall number of hospitals contributing data was 640. HO rates were significantly higher in 2020 and 2021 compared with 2019. The HO rates of VRE, MDRPseu, and CRE were significantly higher in 2021 when compared to 2020 (Table 1). For CO infections, we found that MRSA rates decreased significantly during the study period, while VRE and CRAB were significantly higher in 2021 compared to 2019 (Table 1). Conclusion Hospital onset antibiotic resistant infection rates in 2021 remain higher than pre-pandemic rates with increasing rates for several pathogens in 2021 compared to 2020, while CO MRSA declined. As infections caused by resistant pathogens represent a serious threat to patient safety, further study of factors contributing to the continued increases and decreases may inform prevention strategies. Disclosures All Authors: No reported disclosures

2473. Rates of Antibiotic Resistant Infections in Hospitalized Patients with Hematologic and Non-Hematologic Cancers, 2019

Abstract Background Patients with cancer have risk factors for developing both hospital-onset (HO) and antibiotic resistant (AR) infections such as high antibiotic use, long lengths of stay, and device utilization. Understanding the epidemiology of AR infections in this population can inform clinical management and prevention strategies. We aimed to describe the rates and proportions of AR infections in hospitalized patients with cancer. Methods Using the PINC AI Healthcare Database, we included adult discharges from 2019 among facilities reporting microbiology data. We identified patients with at least one cancer diagnosis from the Healthcare Cost and Utilization Project’s Clinical Classifications Software Refined categories and Elixhauser Comorbidity Software Refined for ICD-10-CM. We calculated age-standardized rates of AR infections among cancer patients per 10,000 discharges, stratified by community-onset (CO: ≤ day 3 of hospitalization) and HO (≥ day 4 of hospitalization), and hematologic and non-hematologic cancer types. Hematologic cancers included lymphoma, leukemia, myeloma and myelodysplastic syndrome. We also examined the proportion of AR infections in patients with cancer among all AR infections in the cohort. Results Of &amp;gt;2 million discharges from 277 facilities, 11.4% were patients with cancer. Compared to all patients, cancer patients had higher rates of infection with CO and HO vancomycin resistant Enterococcus (VRE) and carbapenem resistant Enterobacterales (CRE), and HO Enterobacterales with AR phenotypes suggestive of extended-spectrum β-lactamase (ESBL) production (Table 1). Compared to patients with non-hematologic cancer, patients with hematologic cancer had higher rates of all AR infections, except for CO carbapenem resistant Acinetobacter spp. (CRAsp) infections (Table 1). For most AR infections, cancer patients made up a greater proportion of all HO AR infections compared to CO AR infections (Table 2). Conclusion Patients with cancer had higher rates of several AR infections compared to all patients. To decrease the burden of AR infections in this population, infection prevention strategies may focus on VRE, ESBL, and CRE pathogens, as well as HO infections, in all cancer patients, particularly those with hematologic cancer. Disclosures All Authors: No reported disclosures

The role of the plasmid-mediated fluoroquinolone resistance genes as resistance mechanisms in pediatric infections due to Enterobacterales.

Fluoroquinolones (FQs) are not commonly prescribed in children, yet the increasing incidence of multidrug-resistant (MDR) Enterobacterales (Ent) infections in this population often reveals FQ resistance. We sought to define the role of FQ resistance in the epidemiology of MDR Ent in children, with an overall goal to devise treatment and prevention strategies. A case-control study of children (0-18 years) at three Chicago hospitals was performed. Cases had infections by FQ-susceptible, β-lactamase-producing (bla) Ent harboring a non- or low-level expression of PMFQR genes (PMFQS Ent). Controls had FQR infections due to bla Ent with expressed PMFQR genes (PMFQR Ent). We sought bla genes by PCR or DNA (BD Max Check-Points assay®) and PMFQR genes by PCR. We performed rep-PCR, MLST, and E. coli phylogenetic grouping. Whole genome sequencing was additionally performed on PMFQS Ent positive isolates. Demographics, comorbidities, and device, antibiotic, and healthcare exposures were evaluated. Predictors of infection were assessed. Of 170 β-lactamase-producing Ent isolates, 85 (50%) were FQS; 23 (27%) had PMFQR genes (PMFQS cases). Eighty-five (50%) were FQR; 53 (62%) had PMFQR genes (PMFQR controls). The median age for children with PMFQS Ent and PMFQR Ent was 4.3 and 6.2 years, respectively (p = NS). Of 23 PMFQS Ent, 56% were Klebsiella spp., and of 53 PMFQR Ent, 76% were E. coli. The most common bla and PMFQR genes detected in PMFQS Ent were bla SHV ESBL (44%) and oqxAB (57%), and the corresponding genes detected in PMFQR Ent were bla CTX-M-1-group ESBL (79%) and aac(6')-Ib-cr (83%). Whole genome sequencing of PMFQS Ent revealed the additional presence of mcr-9, a transferable polymyxin resistance gene, in 47% of isolates, along with multiple plasmids and mobile genetic elements propagating drug resistance. Multivariable regression analysis showed that children with PMFQS Ent infections were more likely to have hospital onset infection (OR 5.7, 95% CI 1.6-22) and isolates containing multiple bla genes (OR 3.8, 95% CI 1.1-14.5). The presence of invasive devices mediated the effects of healthcare setting in the final model. Differences in demographics, comorbidities, or antibiotic use were not found. Paradoxically, PMFQS Ent infections were often hospital onset and PMFQR Ent infections were community onset. PMFQS Ent commonly co-harbored multiple bla and PMFQR genes, and additional silent, yet transferrable antibiotic resistance genes such as mcr-9, affecting therapeutic options and suggesting the need to address infection prevention strategies to control spread. Control of PMFQS Ent infections will require validating community and healthcare-based sources and risk factors associated with acquisition.

Assessment of Hospital-Onset SARS-CoV-2 Infection Rates and Testing Practices in the US, 2020-2022.

Characterizing the scale and factors associated with hospital-onset SARS-CoV-2 infections could help inform hospital and public health policies regarding prevention and surveillance needs for these infections. To evaluate associations of hospital-onset SARS-CoV-2 infection rates with different periods of the COVID-19 pandemic, hospital characteristics, and testing practices. This cohort study of US hospitals reporting SARS-CoV-2 testing data in the PINC AI Healthcare Database COVID-19 special release files was conducted from July 2020 through June 2022. Data were collected from hospitals that reported at least 1 SARS-CoV-2 reverse transcription-polymerase chain reaction or antigen test during hospitalizations discharged that month. For each hospital-month where the hospital reported sufficient data, all hospitalizations discharged in that month were included in the cohort. SARS-CoV-2 viral tests and results reported in the microbiology files for all hospitalizations in the study period by discharge month were identified. Data analysis was conducted from September 2022 to March 2023. Hospitalizations discharged in an included hospital-month. Multivariable generalized estimating equation negative-binomial regression models were used to assess associations of monthly rates of hospital-onset SARS-CoV-2 infections per 1000 patient-days (defined as a first positive SARS-CoV-2 test during after hospitalization day 7) with the phase of the pandemic (defined as the predominant SARS-CoV-2 variant in circulation), admission testing rates, and hospital characteristics (hospital bed size, teaching status, urban vs rural designation, Census region, and patient distribution variables). A total of 5687 hospital-months from 288 distinct hospitals were included, which contributed 4 421 268 hospitalization records. Among 171 564 hospitalizations with a positive SARS-CoV-2 test, 7591 (4.4%) were found to be hospital onset and 6455 (3.8%) were indeterminate onset. The mean monthly hospital-onset infection rate per 1000 patient-days was 0.27 (95 CI, 0.26-0.29). Hospital-onset infections occurred in 2217 of 5687 hospital-months (39.0%). The monthly percentage of discharged patients tested for SARS-CoV-2 at admission varied; 1673 hospital-months (29.4%) had less than 25% of hospitalizations tested at admission; 2199 hospital-months (38.7%) had 25% to 50% of all hospitalizations tested, and 1815 hospital months (31.9%) had more than 50% of all hospitalizations tested at admission. Postadmission testing rates and community-onset infection rates increased with admission testing rates. In multivariable models restricted to hospital-months testing at least 25% of hospitalizations at admission, a 10% increase in community-onset SARS-CoV-2 infection rate was associated with a 178% increase in the hospital-onset infection rate (rate ratio, 2.78; 95% CI, 2.52-3.07). Additionally, the phase of the COVID-19 pandemic, the admission testing rate, Census region, and bed size were all significantly associated with hospital-onset SARS-CoV-2 infection rates. In this cohort study of hospitals reporting SARS-CoV-2 infections, there was an increase of hospital-onset SARS-CoV-2 infections when community-onset infections were higher, indicating a need for ongoing and enhanced surveillance and prevention efforts to reduce in-hospital transmission of SARS-CoV-2 infections, particularly when community-incidence of SARS-CoV-2 infections is high.

A 7-year analysis of attributable costs of healthcare-associated infections in a network of community hospitals in the southeastern United States.

We calculated the attributable cost of several healthcare-associated infections in a community hospital network: central-line-associated bloodstream infections (CLABSIs), catheter-associated urinary tract infections (CAUTIs), hospital-onset Clostridioides difficile infections (CDI-HOs) (43 hospitals); surgical site infections (SSIs) (40 hospitals). From 2016 to 2022, the total cost of CLABSIs, CAUTIs, CDI-HOs, and SSIs was $420,012,025.

Increased Incidence and Risk of Septicemia and Urinary Tract Infection After Clostridioides difficile Infection.

Although increased occurrence of septicemia in persons with Clostridioides difficile infection (CDI) has been reported, incidence rates and risk of septicemia and urinary tract infection (UTI) after CDI are unclear. The first episode of CDI was identified using 2011-2017 MarketScan and CMS Medicare data and CDI cases categorized by standard surveillance definitions. Uninfected persons were frequency matched 4:1 to cases by the CDI case surveillance definition. Multivariable Cox proportional hazards models were used to identify risk factors for septicemia and UTI within 90 days of CDI onset, accounting for the competing risk of death in the Medicare population. The incidence of septicemia was highest after hospital-onset CDI in the Medicare, younger commercial, and younger Medicaid populations (25.5%, 15.7%, and 19.5%, respectively) and lowest in those with community-associated CDI (3.8%, 4.3%, and 8.3%, respectively). In contrast, the incidence of UTI was highest in those with other healthcare facility onset CDI in all 3 populations (32.1%, 24.2%, and 18.1%, respectively). Hospital-onset CDI was associated with highest risk of septicemia compared with uninfected controls in all 3 populations. In the younger populations, risk of septicemia was more uniform across the CDI surveillance definitions. The risk of UTI was significantly higher in all CDI surveillance categories compared to uninfected controls, and among CDI cases it was lowest in those with community-associated CDI. The incidence of septicemia is high after CDI, particularly after hospital-onset infection. Additional preventive measures are needed to reduce infectious complications of CDI.

Is neighborhood deprivation index a risk factor for Staphylococcus aureus infections?

We assessed the association between neighborhood area deprivation index (ADI) and community-onset (co) and hospital-onset (ho) Staphylococcus aureus infection. Demographic and clinical characteristics of patients admitted to 5 adult hospitals in the mid-Atlantic between 2016 and 2018 were obtained. The association of ADI with methicillin-resistant (MRSA) and methicillin-sensitive (MSSA) S aureus infections was assessed using logistic regression models adjusting for severity of illness and days of admission. Overall, increasing ADI was associated with higher odds of co- and ho-MRSA and MSSA infection. In univariate analysis, Black race was associated with 44% greater odds of ho-MRSA infection (odds ratio [OR] 1.44; 95% CI 1.18-1.76) and Asian race (co-MRSA OR 0.355; Confidence Interval (CI) 0.240-0.525; co-MSSA OR 0.718; CI 0.557-0.928) and unknown race (co-MRSA OR 0.470; CI 0.365-0.606; co-MSSA OR 0.699; CI 0.577-0.848) was associated with lower odds of co-MSSA and co-MRSA infections. When both race and ADI were included in the model, Black race was no longer associated with ho-MRSA infections whereas Asian and unknown race remained associated with lower odds of co-MRSA and co-MSSA infection. In the multivariable logistic regression, ADI was consistently associated with increased odds of S aureus infection (co-MRSA OR 1.132; CI 1.064-1.205; co-MSSA OR 1.089; CI 1.030-1.15; ho-MRSA OR 1.29; CI 1.16-1.43: ho-MSSA OR 1.215; CI 1.096-1.346). The area deprivation index is associated with community and hospital-onset MRSA and MSSA infections.

Impact of mandatory nucleic acid amplification test (NAAT) testing approval on hospital-onset Clostridioides difficile infection (HO-CDI) rates: A diagnostic stewardship intervention.

Misclassification of Clostridioides difficile colonization as hospital-onset C. difficile infection (HO-CDI) can lead to unnecessary treatment of patients and substantial financial penalties for hospitals. We successfully implemented mandatory C. difficile PCR testing approval as a strategy to optimize testing, which was associated with a significant decline in the monthly incidence of HO-CDI rates and lowering of our standardized infection ratio to 0.77 (from 1.03) 18 months after this intervention. Approval request served as an educational opportunity to promote mindful testing and accurate diagnosis of HO-CDI.

A comparison of National Healthcare Safety Network surveillance definitions to physician review for central-line-associated bloodstream infections.

For 147 hospital-onset bloodstream infections, we assessed the sensitivity, specificity, positive predictive value, and negative predictive value of the National Healthcare Safety Network surveillance definitions of central-line-associated bloodstream infections against the gold standard of physician review, examining the drivers of discrepancies and related implications for reporting and infection prevention.