Impact of the COVID-19 Pandemic on Inpatient Antibiotic Use in the United States, January 2019 Through July 2022.

Antimicrobial use data reported to the National Healthcare Safety Network's Antimicrobial Use and Resistance Module between January 2019 and July 2022 were analyzed to assess the impact of the COVID-19 pandemic on inpatient antimicrobial use.

Vital Signs: Health Disparities in Hemodialysis-Associated Staphylococcus aureus Bloodstream Infections - United States, 2017-2020.

INTRODUCTION: Racial and ethnic minorities are disproportionately affected by end-stage kidney disease (ESKD). ESKD patients on dialysis are at increased risk for Staphylococcus aureus bloodstream infections, but racial, ethnic, and socioeconomic disparities associated with this outcome are not well described. METHODS: Surveillance data from the 2020 National Healthcare Safety Network (NHSN) and the 2017-2020 Emerging Infections Program (EIP) were used to describe bloodstream infections among patients on hemodialysis (hemodialysis patients) and were linked to population-based data sources (CDC/Agency for Toxic Substances and Disease Registry [ATSDR] Social Vulnerability Index [SVI], United States Renal Data System [USRDS], and U.S. Census Bureau) to examine associations with race, ethnicity, and social determinants of health. RESULTS: In 2020, 4,840 dialysis facilities reported 14,822 bloodstream infections to NHSN; 34.2% were attributable to S. aureus . Among seven EIP sites, the S. aureus bloodstream infection rate during 2017-2020 was 100 times higher among hemodialysis patients (4,248 of 100,000 person-years) than among adults not on hemodialysis (42 of 100,000 person-years). Unadjusted S. aureus bloodstream infection rates were highest among non-Hispanic Black or African American (Black) and Hispanic or Latino (Hispanic) hemodialysis patients. Vascular access via central venous catheter was strongly associated with S. aureus bloodstream infections (NHSN: adjusted rate ratio [aRR] = 6.2; 95% CI = 5.7-6.7 versus fistula; EIP: aRR = 4.3; 95% CI = 3.9-4.8 versus fistula or graft). Adjusting for EIP site of residence, sex, and vascular access type, S. aureus bloodstream infection risk in EIP was highest in Hispanic patients (aRR = 1.4; 95% CI = 1.2-1.7 versus non-Hispanic White [White] patients), and patients aged 18-49 years (aRR = 1.7; 95% CI = 1.5-1.9 versus patients aged ≥65 years). Areas with higher poverty levels, crowding, and lower education levels accounted for disproportionately higher proportions of hemodialysis-associated S. aureus bloodstream infections. CONCLUSIONS AND IMPLICATIONS FOR PUBLIC HEALTH PRACTICE: Disparities exist in hemodialysis-associated S. aureus infections. Health care providers and public health professionals should prioritize prevention and optimized treatment of ESKD, identify and address barriers to lower-risk vascular access placement, and implement established best practices to prevent bloodstream infections.

Vital Signs: Health Disparities in Hemodialysis-Associated Staphylococcus aureus Bloodstream Infections - United States, 2017-2020.

Introduction: Racial and ethnic minorities are disproportionately affected by end-stage kidney disease (ESKD). ESKD patients on dialysis are at increased risk for Staphylococcus aureus bloodstream infections, but racial, ethnic, and socioeconomic disparities associated with this outcome are not well described. Methods: Surveillance data from the 2020 National Healthcare Safety Network (NHSN) and the 2017-2020 Emerging Infections Program (EIP) were used to describe bloodstream infections among patients on hemodialysis (hemodialysis patients) and were linked to population-based data sources (CDC/Agency for Toxic Substances and Disease Registry [ATSDR] Social Vulnerability Index [SVI], United States Renal Data System [USRDS], and U.S. Census Bureau) to examine associations with race, ethnicity, and social determinants of health. Results: In 2020, 4,840 dialysis facilities reported 14,822 bloodstream infections to NHSN; 34.2% were attributable to S. aureus. Among seven EIP sites, the S. aureus bloodstream infection rate during 2017-2020 was 100 times higher among hemodialysis patients (4,248 of 100,000 person-years) than among adults not on hemodialysis (42 of 100,000 person-years). Unadjusted S. aureus bloodstream infection rates were highest among non-Hispanic Black or African American (Black) and Hispanic or Latino (Hispanic) hemodialysis patients. Vascular access via central venous catheter was strongly associated with S. aureus bloodstream infections (NHSN: adjusted rate ratio [aRR] = 6.2; 95% CI = 5.7-6.7 versus fistula; EIP: aRR = 4.3; 95% CI = 3.9-4.8 versus fistula or graft). Adjusting for EIP site of residence, sex, and vascular access type, S. aureus bloodstream infection risk in EIP was highest in Hispanic patients (aRR = 1.4; 95% CI = 1.2-1.7 versus non-Hispanic White [White] patients), and patients aged 18-49 years (aRR = 1.7; 95% CI = 1.5-1.9 versus patients aged ≥65 years). Areas with higher poverty levels, crowding, and lower education levels accounted for disproportionately higher proportions of hemodialysis-associated S. aureus bloodstream infections. Conclusions and implications for public health practice: Disparities exist in hemodialysis-associated S. aureus infections. Health care providers and public health professionals should prioritize prevention and optimized treatment of ESKD, identify and address barriers to lower-risk vascular access placement, and implement established best practices to prevent bloodstream infections.

A comparison of methods to harmonize cortical thickness measurements across scanners and sites.

Results of neuroimaging datasets aggregated from multiple sites may be biased by site-specific profiles in participants' demographic and clinical characteristics, as well as MRI acquisition protocols and scanning platforms. We compared the impact of four different harmonization methods on results obtained from analyses of cortical thickness data: (1) linear mixed-effects model (LME) that models site-specific random intercepts (LMEINT), (2) LME that models both site-specific random intercepts and age-related random slopes (LMEINT+SLP), (3) ComBat, and (4) ComBat with a generalized additive model (ComBat-GAM). Our test case for comparing harmonization methods was cortical thickness data aggregated from 29 sites, which included 1,340 cases with posttraumatic stress disorder (PTSD) (6.2-81.8 years old) and 2,057 trauma-exposed controls without PTSD (6.3-85.2 years old). We found that, compared to the other data harmonization methods, data processed with ComBat-GAM was more sensitive to the detection of significant case-control differences (Χ2(3) = 63.704, p < 0.001) as well as case-control differences in age-related cortical thinning (Χ2(3) = 12.082, p = 0.007). Both ComBat and ComBat-GAM outperformed LME methods in detecting sex differences (Χ2(3) = 9.114, p = 0.028) in regional cortical thickness. ComBat-GAM also led to stronger estimates of age-related declines in cortical thickness (corrected p-values < 0.001), stronger estimates of case-related cortical thickness reduction (corrected p-values < 0.001), weaker estimates of age-related declines in cortical thickness in cases than controls (corrected p-values < 0.001), stronger estimates of cortical thickness reduction in females than males (corrected p-values < 0.001), and stronger estimates of cortical thickness reduction in females relative to males in cases than controls (corrected p-values < 0.001). Our results support the use of ComBat-GAM to minimize confounds and increase statistical power when harmonizing data with non-linear effects, and the use of either ComBat or ComBat-GAM for harmonizing data with linear effects.

National Healthcare Safety Network Standardized Antimicrobial Administration Ratios (SAARs): A Progress Report and Risk Modeling Update Using 2017 Data.

BACKGROUND: The Standardized Antimicrobial Administration Ratio (SAAR) is a risk-adjusted metric of antimicrobial use (AU) developed by the Centers for Disease Control and Prevention (CDC) in 2015 as a tool for hospital antimicrobial stewardship programs (ASPs) to track and compare AU with a national benchmark. In 2018, CDC updated the SAAR by expanding the locations and antimicrobial categories for which SAARs can be calculated and by modeling adult and pediatric locations separately. METHODS: We identified eligible patient-care locations and defined SAAR antimicrobial categories. Predictive models were developed for eligible adult and pediatric patient-care locations using negative binomial regression applied to nationally aggregated AU data from locations reporting ≥9 months of 2017 data to the National Healthcare Safety Network (NHSN). RESULTS: 2017 Baseline SAAR models were developed for 7 adult and 8 pediatric SAAR antimicrobial categories using data reported from 2156 adult and 170 pediatric locations across 457 hospitals. The inclusion of step-down units and general hematology-oncology units in adult 2017 baseline SAAR models and the addition of SAARs for narrow-spectrum B-lactam agents, antifungals predominantly used for invasive candidiasis, antibacterial agents posing the highest risk for Clostridioides difficile infection, and azithromycin (pediatrics only) expand the role SAARs can play in ASP efforts. Final risk-adjusted models are used to calculate predicted antimicrobial days, the denominator of the SAAR, for 40 SAAR types displayed in NHSN. CONCLUSIONS: SAARs can be used as a metric to prompt investigation into potential overuse or underuse of antimicrobials and to evaluate the effectiveness of ASP interventions.

Uptake of Antibiotic Stewardship Programs in US Acute Care Hospitals: Findings From the 2015 National Healthcare Safety Network Annual Hospital Survey.

To assess uptake of the Centers for Disease Control and Prevention's Core Elements of Hospital Antibiotic Stewardship Programs, we analyzed stewardship practices as reported in the 2015 National Healthcare Safety Network's Annual Hospital Survey. Hospital uptake of all 7 core elements increased from 40.9% in 2014 to 48.1% in 2015.

An Update From the National Healthcare Safety Network on Hospital Antibiotic Stewardship Programs in the United States, 2014-2021.

Background: In 2014, the Centers for Disease Control and Prevention (CDC) released the Core Elements of Hospital Antibiotic Stewardship Programs (ASPs) and began monitoring uptake through the National Healthcare Safety Network (NHSN) Annual Hospital Survey. In 2019, CDC updated the Core Elements and in 2022 released the Priorities for Hospital Core Element Implementation. We describe Core Element uptake from 2014 to 2021, provide a snapshot of specific ASP practices in acute care hospitals in 2021, and describe how we plan to monitor stewardship moving forward. Methods: We used the NHSN Annual Hospital Survey to summarize facility demographics and ASP practices and to monitor uptake of Core Elements. Questions have been updated over time, so not all data could be compared across years. Results: Uptake of all 7 Core Elements increased from 41% in 2014 to 95% in 2021. Uptake of all 6 Priority Elements was 10% in 2021, though 46% of hospitals met 4 or 5 of the possible 6 elements. Antibiotic stewardship was specifically listed in a contract or job description for about 60% of program leaders. The percentage of physician-pharmacist co-led programs rose from 23% to 64%. Seventy-six percent of hospitals reported implementing audit with feedback interventions. Conclusions: With nearly all acute care hospitals reporting uptake of the 7 Core Elements in 2021, and with more evidence for which ASP practices are most effective, the Priorities for Hospital Core Element Implementation were released in 2022 to help enhance the quality and impact of existing ASPs.

Intrusive Traumatic Re-Experiencing Domain: Functional Connectivity Feature Classification by the ENIGMA PTSD Consortium.

Background: Intrusive traumatic re-experiencing domain (ITRED) was recently introduced as a novel perspective on posttraumatic psychopathology, proposing to focus research of posttraumatic stress disorder (PTSD) on the unique symptoms of intrusive and involuntary re-experiencing of the trauma, namely, intrusive memories, nightmares, and flashbacks. The aim of the present study was to explore ITRED from a neural network connectivity perspective. Methods: Data were collected from 9 sites taking part in the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) PTSD Consortium (n= 584) and included itemized PTSD symptom scores and resting-state functional connectivity (rsFC) data. We assessed the utility of rsFC in classifying PTSD, ITRED-only (no PTSD diagnosis), and trauma-exposed (TE)-only (no PTSD or ITRED) groups using a machine learning approach, examining well-known networks implicated in PTSD. A random forest classification model was built on a training set using cross-validation, and the averaged cross-validation model performance for classification was evaluated using the area under the curve. The model was tested using a fully independent portion of the data (test dataset), and the test area under the curve was evaluated. Results: rsFC signatures differentiated TE-only participants from PTSD and ITRED-only participants at about 60% accuracy. Conversely, rsFC signatures did not differentiate PTSD from ITRED-only individuals (45% accuracy). Common features differentiating TE-only participants from PTSD and ITRED-only participants mainly involved default mode network-related pathways. Some unique features, such as connectivity within the frontoparietal network, differentiated TE-only participants from one group (PTSD or ITRED-only) but to a lesser extent from the other group. Conclusions: Neural network connectivity supports ITRED as a novel neurobiologically based approach to classifying posttrauma psychopathology.

Association between prevalence of laboratory-identified Clostridioides difficile infection (CDI) and antibiotic treatment for CDI in US acute-care hospitals, 2019.

OBJECTIVE: To evaluate hospital-level variation in using first-line antibiotics for Clostridioides difficile infection (CDI) based on the burden of laboratory-identified (LabID) CDI. METHODS: Using data on hospital-level LabID CDI events and antimicrobial use (AU) for CDI (oral/rectal vancomycin or fidaxomicin) submitted to the National Healthcare Safety Network in 2019, we assessed the association between hospital-level CDI prevalence (per 100 patient admissions) and rate of CDI AU (days of therapy per 1,000 days present) to generate a predicted value of AU based on CDI prevalence and CDI test type using negative binomial regression. The ratio of the observed to predicted AU was then used to identify hospitals with extreme discordance between CDI prevalence and CDI AU, defined as hospitals with a ratio outside of the intervigintile range. RESULTS: Among 963 acute-care hospitals, rate of CDI prevalence demonstrated a positive dose-response relationship with rate of CDI AU. Compared with hospitals without extreme discordance (n = 902), hospitals with lower-than-expected CDI AU (n = 31) had, on average, fewer beds (median, 106 vs 208), shorter length of stay (median, 3.8 vs 4.2 days), and higher proportion of undergraduate or nonteaching medical school affiliation (48% vs 39%). Hospitals with higher-than-expected CDI AU (n = 30) were similar overall to hospitals without extreme discordance. CONCLUSIONS: The prevalence rate of LabID CDI had a significant dose-response association with first-line antibiotics for treating CDI. We identified hospitals with extreme discordance between CDI prevalence and CDI AU, highlighting potential opportunities for data validation and improvements in diagnostic and treatment practices for CDI.

Impact of coronavirus disease 2019 (COVID-19) on US Hospitals and Patients, April-July 2020.

OBJECTIVE: The rapid spread of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) throughout key regions of the United States in early 2020 placed a premium on timely, national surveillance of hospital patient censuses. To meet that need, the Centers for Disease Control and Prevention's National Healthcare Safety Network (NHSN), the nation's largest hospital surveillance system, launched a module for collecting hospital coronavirus disease 2019 (COVID-19) data. We present time-series estimates of the critical hospital capacity indicators from April 1 to July 14, 2020. DESIGN: From March 27 to July 14, 2020, the NHSN collected daily data on hospital bed occupancy, number of hospitalized patients with COVID-19, and the availability and/or use of mechanical ventilators. Time series were constructed using multiple imputation and survey weighting to allow near-real-time daily national and state estimates to be computed. RESULTS: During the pandemic's April peak in the United States, among an estimated 431,000 total inpatients, 84,000 (19%) had COVID-19. Although the number of inpatients with COVID-19 decreased from April to July, the proportion of occupied inpatient beds increased steadily. COVID-19 hospitalizations increased from mid-June in the South and Southwest regions after stay-at-home restrictions were eased. The proportion of inpatients with COVID-19 on ventilators decreased from April to July. CONCLUSIONS: The NHSN hospital capacity estimates served as important, near-real-time indicators of the pandemic's magnitude, spread, and impact, providing quantitative guidance for the public health response. Use of the estimates detected the rise of hospitalizations in specific geographic regions in June after they declined from a peak in April. Patient outcomes appeared to improve from early April to mid-July.

National Healthcare Safety Network 2018 Baseline Neonatal Standardized Antimicrobial Administration Ratios.

BACKGROUND: The microbiologic etiologies, clinical manifestations, and antimicrobial treatment of neonatal infections differ substantially from infections in adult and pediatric patient populations. In 2019, the Centers for Disease Control and Prevention developed neonatal-specific (Standardized Antimicrobial Administration Ratios SAARs), a set of risk-adjusted antimicrobial use metrics that hospitals participating in the National Healthcare Safety Network's (NHSN's) antimicrobial use surveillance can use in their antibiotic stewardship programs (ASPs). METHODS: The Centers for Disease Control and Prevention, in collaboration with the Vermont Oxford Network, identified eligible patient care locations, defined SAAR agent categories, and implemented neonatal-specific NHSN Annual Hospital Survey questions to gather hospital-level data necessary for risk adjustment. SAAR predictive models were developed using 2018 data reported to NHSN from eligible neonatal units. RESULTS: The 2018 baseline neonatal SAAR models were developed for 7 SAAR antimicrobial agent categories using data reported from 324 neonatal units in 304 unique hospitals. Final models were used to calculate predicted antimicrobial days, the SAAR denominator, for level II neonatal special care nurseries and level II/III, III, and IV NICUs. CONCLUSIONS: NHSN's initial set of neonatal SAARs provides a way for hospital ASPs to assess whether antimicrobial agents in their facility are used at significantly higher or lower rates compared with a national baseline or whether an individual SAAR value is above or below a specific percentile on a given SAAR distribution, which can prompt investigations into prescribing practices and inform ASP interventions.

Remodeling of the Cortical Structural Connectome in Posttraumatic Stress Disorder: Results From the ENIGMA-PGC Posttraumatic Stress Disorder Consortium.

BACKGROUND: Posttraumatic stress disorder (PTSD) is accompanied by disrupted cortical neuroanatomy. We investigated alteration in covariance of structural networks associated with PTSD in regions that demonstrate the case-control differences in cortical thickness (CT) and surface area (SA). METHODS: Neuroimaging and clinical data were aggregated from 29 research sites in >1300 PTSD cases and >2000 trauma-exposed control subjects (ages 6.2-85.2 years) by the ENIGMA-PGC (Enhancing Neuro Imaging Genetics through Meta Analysis-Psychiatric Genomics Consortium) PTSD working group. Cortical regions in the network were rank ordered by the effect size of PTSD-related cortical differences in CT and SA. The top-n (n = 2-148) regions with the largest effect size for PTSD > non-PTSD formed hypertrophic networks, the largest effect size for PTSD < non-PTSD formed atrophic networks, and the smallest effect size of between-group differences formed stable networks. The mean structural covariance (SC) of a given n-region network was the average of all positive pairwise correlations and was compared with the mean SC of 5000 randomly generated n-region networks. RESULTS: Patients with PTSD, relative to non-PTSD control subjects, exhibited lower mean SC in CT-based and SA-based atrophic networks. Comorbid depression, sex, and age modulated covariance differences of PTSD-related structural networks. CONCLUSIONS: Covariance of structural networks based on CT and cortical SA are affected by PTSD and further modulated by comorbid depression, sex, and age. The SC networks that are perturbed in PTSD comport with converging evidence from resting-state functional connectivity networks and networks affected by inflammatory processes and stress hormones in PTSD.

Using NHSN's Antimicrobial Use Option to Monitor and Improve Antibiotic Stewardship in Neonates.

BACKGROUND: The Antimicrobial Use (AU) Option of the Centers for Disease Control and Prevention's National Healthcare Safety Network (NHSN) is a surveillance resource that can provide actionable data for antibiotic stewardship programs. Such data are used to enable measurements of AU across hospitals and before, during, and after stewardship interventions. METHODS: We used monthly AU data and annual facility survey data submitted to the NHSN to describe hospitals and neonatal patient care locations reporting to the AU Option in 2017, examine frequencies of most commonly reported agents, and analyze variability in AU rates across hospitals and levels of care. We used results from these analyses in a collaborative project with Vermont Oxford Network to develop neonatal-specific Standardized Antimicrobial Administration Ratio (SAAR) agent categories and neonatal-specific NHSN Annual Hospital Survey questions. RESULTS: As of April 1, 2018, 351 US hospitals had submitted data to the AU Option from at least 1 neonatal unit. In 2017, ampicillin and gentamicin were the most frequently reported antimicrobial agents. On average, total rates of AU were highest in level III NICUs, followed by special care nurseries, level II-III NICUs, and well newborn nurseries. Seven antimicrobial categories for neonatal SAARs were created, and 6 annual hospital survey questions were developed. CONCLUSIONS: A small but growing percentage of US hospitals have submitted AU data from neonatal patient care locations to NHSN, enabling the use of AU data aggregated by NHSN as benchmarks for neonatal antimicrobial stewardship programs and further development of the SAAR summary measure for neonatal AU.