Infection Control and Hospital Epidemiology最新文献

Background: In the neonatal intensive care unit (NICU), outbreaks caused by methicillin-susceptible Staphylococcus aureus (MSSA) are less commonly described than outbreaks caused by methicillin-resistant Staphylococcus aureus (MRSA) despite the increased burden of MSSA infections.

Objective: To investigate a NICU MSSA outbreak utilizing whole-genome sequencing (WGS) and multi-locus sequencing typing (MLST) to identify transmission events.

Methods: An investigation was initiated in a level IV NICU after four patients developed MSSA skin and soft tissue infections (SSTI) within three weeks. MLST and WGS were performed on MSSA isolates obtained from clinical and surveillance specimens.

Results: During the outbreak, 16 infants developed MSSA infections including SSTIs (n = 15) and bacteremia (n = 1). Thirteen SSTIs presented on neonates' faces, all of whom were on non-invasive respiratory support. During 7 rounds of surveillance, an additional 31 patients were found to be colonized with MSSA. MLST identified a predominant cluster (ST-121). WGS found that all ST-121 isolates were closely related (≤10 genetic variants between isolates) suggesting likely transmission events, harbored the mupA gene, exhibited mupirocin MIC values ≥1,024 µg/mL, and were associated with infection. Multiple infection control measures were implemented including the "bare below the elbows" practice. No further mupirocin-resistant isolates were recovered or ST-121 SSTIs identified after Week 26.

Conclusions: WGS analysis furthered the MLST analysis and identified a single MLST as the outbreak-related strain. Successful control of this outbreak was achieved with a multitude of infection prevention and control methods.

Background: Outbreak investigation and control are critical for preventing the spread of infectious diseases in healthcare settings. Traditional methods rely on manual processes, which are time-consuming and limited in scope. Whole genome sequencing (WGS) surveillance improves outbreak detection but still requires extensive manual chart reviews to identify transmission routes. Integrating artificial intelligence (AI) may enhance the efficiency and accuracy of these investigations.

Methods: We evaluated an AI tool developed to streamline healthcare outbreak investigations detected by the Enhanced Detection System for Healthcare-associated Transmission (EDS-HAT). For outbreaks detected between November 2021 and November 2023, multiple data elements were extracted from electronic health records (EHR) for all patients. The AI algorithm was applied to identify transmission routes, and its performance was assessed against expert manual reviews. Key measures included additional transmission routes identified and sensitivity.

Results: Data from 172 outbreaks involving 476 case patients were analyzed. The AI tool identified 37 transmission routes that were missed by manual review, including procedures and provider routes. The algorithm achieved a sensitivity of 76.0% (95% confidence interval [CI] 71.1%-81.1%) compared to manual review, increasing to 91.7% (95% CI 87.7%-94.7%) after accounting for transmission at other facilities and downstream exposures.

Conclusion: The EDS-HAT AI tool significantly improved outbreak investigations by automating the identification of transmission routes, both with concordant findings of manual review as well as finding additional routes of transmission missed by traditional chart review. AI with genomic surveillance has the potential to optimize outbreak detection and investigation to streamline interventions in healthcare settings.

Background: Recipients of hematopoietic cell transplantation (HCT) are at increased risk for Clostridioides difficile infection (CDI) and its recurrence, which are associated with significant morbidity. We aimed to characterize risk factors for primary and recurrent CDI in a large cohort of HCT recipients.

Methods: We conducted a retrospective cohort study of 2725 adults who underwent HCT from 2010-2023 to evaluate the epidemiology, timing, and risk factors for CDI. We compared patients who developed CDI with those who did not, adjusting for patient demographics, comorbidities, transplant factors, medications, and laboratory values. Among patients who developed CDI, we investigated risk factors for recurrent CDI.

Results: The cumulative 1-year incidence of CDI was 17.8% among allogeneic HCT recipients (181/1016) and 4.1% among autologous recipients (71/1709). Overall CDI incidence increased by 1.4% annually during the study period (95%CI: 1.24-1.53%). Independent risk factors for primary CDI included penicillin antibiotics (aOR 1.51; 95%CI: 1.13-2.02), prior chemotherapy (aOR 8.36; 95%CI: 2.95-23.69 for 1-3 regimens), and umbilical cord blood stem cells (aOR 1.95; 95%CI: 1.07-3.57). Autologous HCT was associated with decreased risk. Among 252 patients with primary CDI, 22 (8.7%) developed recurrence. Macrolide use before index CDI (aOR 7.25; 95%CI: 1.80-29.2) and allogeneic HCT (aOR 31.04; 95%CI: 1.37-731.58) were associated with recurrence.

Conclusion: CDI is a common, early complication of HCT particularly among allogeneic recipients. Penicillin exposure, prior chemotherapy, and cord blood stem cell source are key risk factors, while macrolide use is associated with recurrence. Our findings highlight potential targets for risk-stratified prevention strategies.

Objective: To evaluate the incidence of hospital-onset bacteremia and fungemia (HOB) among solid organ malignancy (SOM), hematologic malignancy (HM), and hematopoietic cell transplant (HCT) therapy patients at a large cancer care center.

Methods: A single-center, observational, retrospective analysis was conducted for hospitalizations between January 1, 2018, and September 30, 2024, to identify patients with a first positive blood culture on or after day four of hospitalization. Hospitalizations were grouped into three categories: SOM, HM with HCT, and HM without HCT. The primary objective was to study the incidence of HOB. Secondary objectives: identification of risk factors for HOB events and pathogens associated with HOB events.

Results: In 45,896 admissions, 1,470 HOB events were identified (incidence: 3.2%). The incidence of HOB was highest in the HM/HCT cohort (3.8%), followed by HM without HCT (2.3%) and SOM (0.9%). Risk factors of HOB identified included HM (OR 1.49), hospitalization within the past 90 days (OR 1.50), length of stay greater than or equal to 30 days (OR 6.74), intensive care unit (ICU) admission (OR 4.06), development of a CAUTI during admission (OR 23.23), or presence of a central line (OR 51.61). The most common pathogens were Escherichia coli (20.1%), coagulase-negative Staphylococci (19.0%), and Viridians streptococci (11.3%).

Conclusion: This study highlights the high incidence of HOB among cancer and HCT patients. The risk factors and differential rates of HOB in subpopulations of this demographic may help to inform targeted infection prevention efforts in cancer centers.

Objective: To analyze the correlation between scale of Candida auris clustering and extent of environmental contamination, exploring its implications for improving infection control measures in healthcare settings.

Design: Retrospective observational study.

Setting: An acute hospital and a convalescent hospital in Hong Kong.

Patients: Laboratory confirmed C. auris carriers diagnosed in two hospitals between March and October 2023.

Methods: C. auris screening was conducted on patients with defined risk factors and through regular surveillance. Environmental samples were collected from high-touch surfaces and air grilles in corresponding wards.

Results: One-hundred-seventy new C. auris patients were identified, including 65 from nine outbreaks and 105 sporadic cases. Environmental screening from eight outbreaks and 46 sporadic isolated cases was analyzed. The environmental contamination rate was significantly higher in the outbreak group (15.1% vs 2.6%, P < 0.05). Longer outbreak duration (34 vs 7 days, P < 0.05) and a higher median number of affected patients per outbreak (9 vs 5, P = 0.05) were associated with higher contamination rates. Notably, air grille samples had a significantly higher contamination rate than high-touch surfaces in both the outbreak (31.6% vs 10.2%, P < 0.05) and sporadic groups (4.6% vs 1.5%, P < 0.05).

Conclusion: Prolonged and sizeable C. auris clusterings were linked with more extensive environmental contamination, particularly in air grilles, which are often overlooked during decontaminationThese findings underscore the need for enhanced infection control measures, including thorough environmental decontamination of air ventilation systems, to mitigate transmission risks in healthcare settings.

We evaluated large language model (LLM)-based agents integrated with the electronic medical record to assess blood culture appropriateness. While sensitivity was high, specificity remained low. Performance was shaped by prompt phrasing, sycophantic behavior, and semantic triggers, reflecting both the potential and limitations of LLMs in real-world clinical decision support.

We aimed to improve diagnostic accuracy for healthcare facility-onset Clostridioides difficile (HO-CDI) infection by removing the result for C. difficile from the multiplex gastrointestinal polymerase chain reaction (PCR). The intervention resulted in an increase in positive PCR tests meeting testing criteria and decrease in median number of HO-CDI per month.