The purpose of the study is to analyze bloodstream infection (BSI) data reported by outpatient hemodialysis facilities to understand temporal trends, the potential impact of infection prevention practices and the COVID-19 pandemic on BSI rates.

Outpatient hemodialysis facilities report BSI data to the National Healthcare Safety Network. We used interrupted time series with mixed effects negative binomial modeling to estimate the annual change of BSI rates from 2012 to 2021, using March 2020 as the COVID-19 inflection point. The model controlled for seasonal factors, vascular access types, and facility characteristics.

The number of facilities used for analysis increased from 5,581 in 2012 to 7,313 in 2021. Most facilities were freestanding (range: 90%–93%) and belonged to for-profit organizations (range: 85%–88%). The annual adjusted BSI rates decreased by an average of 8.90% (95% CI: −9.10 %, −8.71%) January 2012-February 2020. The annual decrease in BSI rate was not significant during March 2020-December 2021 (P = 0.15). There was a level drop of 32.03% (95%CI: −33.84%, −30.17%) in BSI rates in the period of March 2020-December 2021 compared with the period of January 2012-February 2020.

BSI rates decreased steadily from January 2012 to February 2020 likely due to the identification and adoption of evidence-based prevention practices. BSI rates plateaued at lower levels during March 2020-December 2021. This suggests that infection prevention measures implemented by facilities prior to the emergence of COVID-19 contributed to substantial decreases in BSI rates and may have helped to stabilize BSI rates after March 2020.

An improved understanding of the epidemiology of hospital-onset methicillin-resistant Staphylococcus aureus bloodstream infection (HO-MRSA BSI) could inform future prevention strategies for HO-MRSA BSI.

We performed a retrospective cohort study of HO-MRSA BSI reported to NHSN from 2020–2023 at a system of 9 acute care hospitals located in New York City. The primary outcome was to describe the demographic and clinical characteristics of patients with HO-MRSA BSI. Secondary outcomes included comparisons of tertiary (TH) and community (CH) hospitals, standardized infection ratio (SIR) and rates per 10,000 patient-discharges, presumptive potential infectious sources, and mortality.

Between 2020 and 2023, 222 patients had HO-MRSA BSI. Their median age was 65 years, 139 (63%) were male, 92 (41%) had central lines, 89 (40%) were in ICUs, and 63 (28%) were on a ventilator. These characteristics were similar across the 176 (79%) patients in TH and the 46 (21%) patients in CH. SIRs were similar across each year of the study (with cumulative SIRs of 0.815 overall, 1.412 [CH] and 0.732 [TH]). Overall HO-MRSA BSI rates ranged from 2.58–3.53 per 10,000 patient-discharges. The most common sources of HO-MRSA BSI were pneumonia (41%), SSTIs (17%), CLABSIs (13%), and PIV catheter-related issues (9%). The all-cause mortality rate was 35%.

The unchanged HO-MRSA BSI SIRs in this study support the need for additional interventions that focus on prevention of the primary sources of MRSA infections. Ongoing systematic surveillance of the primary sources of HO-MRSA BSI should be implemented to inform and monitor best practices for prevention.

A semi-automated surveillance system for surgical site infections (SSIs), SPICMI (Surveillance and Prevention Program for Infectious Risk in Surgery and Interventional Medicine), has been implemented in French hospitals, leveraging data from electronic health records (EHRs).

To evaluate the performance of the SPICMI algorithm in detecting SSIs in orthopedic and digestive surgery.

Surveillance data were collected annually from the EHRs. The algorithm identified suspected SSIs based on two criteria: (1) surgical revision during the index stay or readmission, (2) positive microbiological samples from the wound. Suspected SSIs identified were subsequently validated by surgeons.

A stochastic modeling approach was used to estimate probability intervals for performance indicators. Various detection scenarios were constructed based on SPICMI criteria. Logistic regression analysis was performed using surveillance data. Data unavailable in the database were estimated through a literature review and expert opinions.

The probability of surgical revision following an SSI varied significantly between surgical specialties, ranging from 92% in orthopedic surgery to 45.2% in gynecology. In orthopedic and digestive surgery, the SPICMI algorithm demonstrated good reliability for detecting SSIs in minimizing false-negative and false-positive cases (Youden index: 0.96 and 0.79, respectively). Sensitivity (Se) was lower in digestive surgery (0.7–0.9) compared to orthopedic surgery (0.9–1), while specificity (Sp) remained high (0.9–1) in both specialties.

The SPICMI algorithm shows potential to support efficient use of time and resources in SSIs surveillance management. Further evaluation is needed with a broader panel of surgery procedures.

While infection is a leading cause of mortality among patients on hemodialysis, there are limited data on patients’ infection prevention knowledge and attitudes. We aimed to assess hemodialysis patients’ knowledge of their elevated infection risk, their willingness to actively prevent infections, and the acceptability of a long-term intranasal decolonization intervention.

We surveyed patients as part of a stepped wedge cluster randomized trial evaluating intranasal povidone-iodine (PVI) decolonization.

Sixteen outpatient hemodialysis centers affiliated with 5 academic medical centers.

Patients undergoing outpatient hemodialysis.

Patients were asked to complete a pre-intervention survey (9 questions) and two intervention surveys (13 questions; only patients interested in PVI) at 1 month and 6 months after starting PVI. We used the chi-squared test to compare responses over time.

469 (∼25%) participants completed at least one survey. Most (55%) participants underestimated their infection risk compared with an average person in the United States. The percentage of participants willing to expend “a lot of effort” to prevent an infection decreased from 79% (pre-intervention) to 63% (final survey) (p < 0.01). Among the 102 participants using PVI at 6 months, 87% said PVI felt neutral or pleasant and 75% used PVI for the past 3 dialysis sessions. Only 9.4% reported side effects.

Patients on hemodialysis underestimate their infection risk. Most patients found intranasal PVI to be acceptable. Future research should aim to improve patient education on their infection risk and remove barriers to adherence with infection prevention interventions.

Clinical trial information: NCT04210505, https://clinicaltrials.gov/

We evaluated whether patient perceptions of cleanliness are associated with objective measures of Clostridioides difficile infection (CDI), as an early indicator of facility-level CDI rates and prevention.

Cross-sectional analysis of Medicare-certified hospitals across the United States.

Data from the CMS Hospital Compare website and U.S. Census Bureau from 2023 were analyzed using multivariate logistic regression models. The primary outcome was C. difficile standardized infection ratios (SIRs) compared to the national average. The primary exposure was patient-rated cleanliness star ratings from the Hospital Consumer Assessment of Healthcare Providers and Systems survey.

The population studied was 3,616 medicare-certified hospitals with an estimated 17,994,034 unique patient admissions. There was no association between better patient-rated cleanliness and improved CDI performance. Facilities with a 5-star cleanliness rating were not more likely to have an SIR less than or equal to the national average compared to those with a lower star rating. For every 1% increase in patients who reported their room and bathroom as always clean, the odds of CDI observed cases being higher than predicted increases by 4.2% (ie, increasing patient-related cleanliness was weakly associated with worse CDI performance).

Patient-rated cleanliness was not associated with improved CDI performance in U.S. national hospital data. Findings were consistent across multiple operationalizations of cleanliness and CDI suggesting patient perceptions of cleanliness are not a strong indicator of CDI control measure performance.

To identify host and clinical risk factors contributing to the development of Clostridioides difficile infection (CDI) among colonized patients.

Retrospective, matched case-control study.

Duke University Health System, including 3 hospitals and affiliated outpatient clinics.

Adult patients who underwent ≥2 two-step C. difficile tests (nucleic acid amplification test (NAAT) followed by toxin enzyme immunoassay) between 03/15/2020–12/31/2023. Cases were patients with C. difficile colonization (NAAT+/toxin–) who converted to CDI (NAAT+/toxin+) within 90 days; controls were colonized patients who remained toxin-negative. Cases were matched to controls by date of index testing (±1 year).

Data collection encompassed a 90-day “pre-exposure” period preceding index testing and a ≤ 90-day “exposure” period between index and repeat testing. Antibiotic use was stratified by risk for each period. Multivariate conditional logistic regression with forward selection was used to identify predictors of progression.

Among 2,212 colonized patients, 71 cases and 133 matched controls were identified. Several host and clinical characteristics were independently associated with progression to CDI in our multivariate model. Notably, high-risk antibiotic use across the pre-exposure and exposure periods was associated with greater odds of progression to CDI compared to other patterns of antibiotic use (adjusted odds ratio 2.70; P = .03).

Sustained exposure to high-risk antibiotics was a strong predictor of the progression from C. difficile colonization to infection, underscoring the need for further research on longitudinal stewardship strategies for CDI prevention, particularly among patients previously identified as colonized.

Early identification of patients colonized with multidrug-resistant organisms (MDROs) facilitates infection control interventions. We assessed a Public Health Risk Model’s ability to predict carbapenem-resistant Enterobacterales and other MDROs.

We retrospectively analyzed a medical intensive care unit patient cohort screened at time of admission for MDRO carriage (1/2017–1/2018). Encounters were linked to Illinois Hospital Discharge Data and assigned a public health risk model probability score. We compared the model’s performance to traditional screening strategies that use variables locally available to clinicians at time of admission (i.e., transfer from other hospital, tracheostomy, gastrostomy, pressure ulcer). Model discrimination was evaluated by quantifying the area under the curve (AUC). For each approach, we assessed sensitivity, specificity, and number needed to screen (NNS) to detect one MDRO carrier.

Model probability calculation was successful in 1237/1250 (98.9%) admissions. The model identified carbapenem-resistant Enterobacterales colonization well (AUC 0.82) and generalized to predict colonization with other healthcare-associated MDROs, including carbapenem-resistant Pseudomonas aeruginosa (AUC 0.82) and vancomycin-resistant enterococci (AUC 0.76). The model did not predict MDROs with known local community reservoirs, i.e., third-generation cephalosporin-resistant Enterobacterales (AUC 0.61) and methicillin-resistant Staphylococcus aureus (AUC 0.59). At the same NNS, the model had higher sensitivity compared to use of traditional screening strategies (68% versus 41%).

A risk model using patient-level healthcare exposure data from a state public health dataset identified critically ill patients likely to harbor healthcare-associated MDROs at the time of admission.

Estimate bacterial pathogen contamination of healthcare workers’ (HCW) long-sleeved attire.

Prospective observational study.

Tertiary care hospital.

HCWs wearing long-sleeved attire providing direct inpatient care.

Sampling of both sleeves of HCWs wearing long-sleeved attire was performed using a swab and cultured for aerobic bacterial growth classified as potential pathogens or presumptive skin commensals. Potential predictors of sleeve contamination, including participant survey responses related to attire and infection prevention practices, were analyzed using univariate analyses. Whole genome sequencing compared isolates to a genomic surveillance database of patient clinical isolates.

Among 280 samples, 81.1% (n = 227) demonstrated any bacterial growth and 20.7% (n = 58) grew ≥1 potential pathogen. Speciated organisms included alpha-hemolytic streptococci (n = 28), Bacillus sp. (n = 20), and Pantoea/Mixta sp. (n = 8), gram-negative bacilli (n = 6), and Staphylococcus aureus (n = 2). Univariate analysis demonstrated that sleeves sampled on non-intensive care units (P = .038) were significantly associated with any bacterial growth, and attire type (P = .002) and sleeve material (P = .004) were associated with growth of ≥1 potential pathogen. Fleece attire and material were more likely to be contaminated than other attire and material types. Sequenced isolates from sleeve samples were not genetically related to any patient isolates.

HCW long sleeve contamination occurs frequently, including with potential pathogens. Changing trends in attire type may have an impact on bacterial transmissibility. While this study could not infer transmission events associated with clinically diagnosed patient infections, the potential benefit of a “bare below the elbows” attire policy warrants further investigation.

This study investigates the potential aerosol transmission of respiratory syncytial virus (RSV), a major cause of viral pneumonia and bronchiolitis in young children.

Two hundred samples were collected in a long-term environmental surveillance program from January 2022 until January 2023. Samples were collected in a pediatric emergency corridor. The analyses were performed using reverse transcription-quantitative polymerase chain reaction (RT-qPCR) targeting the RSV matrix gene. Information on the daily number of emergencies related with pediatric RSV infections was provided by the hospital.

Aerosol samples collected from a pediatric hospital corridor revealed detectable RSV RNA, particularly during peak infection seasons. RSV RNA was detected in 35 of 200 aerosol samples with a median concentration (interquartile range) of 1.8 (4.1) gc/m3. During the month of the peak season of RSV infections (November), RSV RNA was detected in 95% of the aerosol samples. Correlation analysis suggests a link between pediatric RSV cases and airborne RSV RNA concentration.

RSV RNA has been detected in aerosols in a healthcare setting, particularly during peak infection periods. This does not constitute evidence of transmission of the RSV via aerosols. However, the observed correlation with pediatric RSV cases suggests that further research on viral viability and infectivity from RSV detected in aerosols should be conducted. It also shows the potential of characterizing RSV RNA in aerosols for environmental surveillance purposes.

To assess differences in SARS-CoV-2 infection rates between patients receiving hemodialysis in outpatient centers (in-center) and those receiving dialysis in their homes (hemodialysis and peritoneal dialysis) from December 29, 2020, through May 9, 2023.

Retrospective cohort study.

Outpatient dialysis facilities in the United States reporting to the Centers for Disease Control and Prevention’s National Healthcare Safety Network.

Maintenance dialysis patients that received hemodialysis treatment at or were affiliated with outpatient dialysis facilities.

SARS-CoV-2 infection rates were assessed by dialysis setting (in-center and home). Weeks were categorized as surge (rate of infection > median) and non-surge (rate of infection ≤ median) and by variant predominance. A negative binomial regression model with generalized estimating equations was constructed to examine differences in rates of infection among patients.

A total of 7,974 dialysis facilities reported 171,338 SARS-CoV-2 infections among patients. In-center hemodialysis patients had higher average rates of SARS-CoV-2 infection at 2.85 infections per 1000 patient-weeks than home patients at 1.69 infections per 1000 patient-weeks. During surge weeks, the differences in rates of infection between in-center and home patients were more pronounced than during non-surge weeks for all variant predominance categories: Delta (relative rate ratio (RRR) = 1.20, CI: 1.09–1.32), B.1 and Other (RRR = 1.11, CI: 1.02–1.22), and Omicron (RRR = 1.07, CI: 1.01–1.12).

Rates of SARS-CoV-2 infection among patients receiving outpatient hemodialysis were persistently higher than rates among patients receiving dialysis treatments at home; these differences were more pronounced during surge weeks.

We aimed to evaluate the impact of transitioning from a conventional antimicrobial stewardship team (AST) to an interdisciplinary infectious disease support team (IDST) on patient mortality.

Single-center retrospective cohort study.

Yamanashi Prefectural Central Hospital.

We included patients with bacteremia during the AST and IDST periods.

We implemented an interdisciplinary IDST that provided comprehensive support beyond antimicrobial selection and treatment. We compared 28-day mortality outcomes in hospitalized patients with bacteremia during the AST-only period (April 2021–March 2022) and the IDST-intervention period (April 2022–March 2023). Cox proportional hazards modeling was used to assess 28-day mortality; multivariable logistic regression served as a prespecified sensitivity analysis. Between-group differences were tested using two-sided tests (P < .05), and 95% confidence intervals (CIs) were reported.

Among the 854 patients (413 in the AST group and 441 in the IDST group), AST interventions did not significantly decrease 28-day mortality compared with no-intervention cases (20.8% vs 23.3%, P = .630). However, intervention by the IDST significantly reduced 28-day mortality compared with the no-IDST group (16.1% vs 25.2%, P = .019). In the multivariate Cox proportional hazards model, IDST interventions remained independently associated with a reduced 28-day mortality (hazard ratio, 0.518; 95% CI, 0.325–0.826; P = .006).

Transitioning from an AST to an interdisciplinary IDST model was associated with lower 28-day mortality in bacteremia cases, possibly due to sustained diagnostic and therapeutic interventions. Our findings support stewardship as a team-based process and may significantly impact patient outcomes by maintaining involvement until treatment completion and clinical stabilization.

Community-acquired pneumonia (CAP) is a leading cause of hospitalization and mortality in the US. Studies report racial disparities in various infectious syndromes. Our objective was to assess the relationship between patient race and antibiotic prescribing in inpatient CAP management.

Retrospective cohort study.

11 Cleveland Clinic community hospitals.

Patients aged ≥18 years hospitalized with CAP between November 1, 2022, and January 31, 2025.

Parametric and non-parametric methods were used to describe demographic and clinical differences by race. The association between race and extended spectrum antibiotic (ESA) guideline concordance was assessed using multivariable logistic regression models adjusting for age, gender, admission source, area deprivation index (ADI), hospital, diabetes, cardiovascular disease, chronic respiratory disease, renal failure, liver disease, immunocompromising condition, alcohol and substance use disorder, dialysis, and clinical instability and severity on day 1.

In bivariate analyses, Non-Hispanic Black (NHB) patients were less likely than NHW patients to receive ESA guideline-concordant CAP therapy (63.2% vs 64.4%; OR = 0.91, P = .2). After adjusting for patient characteristics, there were no differences between NHB and NHW patients in receipt of ESA therapy (adjusted OR = 0.93; 95% CI = 0.83, 1.00). After adjusting for hospital, NHB patients were more likely to receive ESA guideline-concordant CAP therapy (adjusted OR = 1.17; 95% CI = 1.06, 1.30).

NHB patients were more likely to receive ESA-guideline concordant therapy, but this was influenced by where they sought care. Further studies are needed to understand why prescribing varies across hospitals.

To develop an approach for creating facility-specific urinary antibiograms accounting for the low number of isolates recovered in nursing homes (NHs).

Retrospective analysis of urine culture data collected in NHs in five states.

Data on 5097 urine culture isolates collected across 59 study NHs from January 1, 2020 to December 31, 2021. Four consulting microbiology laboratories served the study homes.

We compared a Clinical and Laboratory Standards Institute (CLSI) standard antibiogram model to four weighted-incidence syndromic antibiogram (WISCA) models utilizing alternate formatting rules. Ability to produce a facility-specific antibiogram with at least 30 isolates and the impact on susceptibility predictions were compared.

Only one facility could generate a CLSI standard antibiogram for the three most commonly recovered Gram-negative isolates over a one-year period. Ability to generate an antibiogram increased with each of the four WISCA models trialed (36%, 54%, 85%, 85%) with the most successful models combining all Gram-negative isolates over a two-year period. Shortening the definition of duplicate isolates from 12 to 3 months did not improve performance. Using all Gram-negative isolates, rather than the three most recovered pathogens, resulted in meaningful changes in the predicted activity of ampicillin-sulbactam, cefazolin, ceftriaxone, and trimethoprim-sulfamethoxazole in several study NHs.

These results suggest that WISCAs using 2-years of urinary culture data including all gram-negative isolates and excluding duplicate isolates within twelve months maximizes the number of NHs able to create a valid antibiogram.