Infection Control and Hospital Epidemiology最新文献

Background: 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).

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

Setting: 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.

Methods: 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.

Results: 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.

Conclusion: 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.

Objective: Estimate bacterial pathogen contamination of healthcare workers' (HCW) long-sleeved attire.

Design: Prospective observational study.

Setting: Tertiary care hospital.

Participants: HCWs wearing long-sleeved attire providing direct inpatient care.

Intervention: 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.

Results: 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.

Conclusions: 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.

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

Design: Retrospective, matched case-control study.

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

Participants: 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).

Methods: 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.

Results: 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).

Conclusions: 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.

Objective: 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.

Methods: 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.

Results: 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.

Conclusions: 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.

In this post hoc analysis of a quasi-experimental pilot/feasibility trial, a bundled diagnostic stewardship intervention safely reduced respiratory culturing rates without increasing ventilator-associated events (VAEs). Using difference-in-differences methodology, we observed a significant reduction in possible ventilator-associated pneumonia (PVAP) events, suggesting the intervention may reduce pneumonia overdiagnosis without compromising patient safety.

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

Methods: 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.

Results: 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.

Conclusions: 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.