BACKGROUND: Health care-associated infections due to multidrug-resistant organisms (MDROs), such as methicillin-resistant Staphylococcus aureus (MRSA) and Clostridioides difficile (CDI), place a significant burden on our health care infrastructure.
OBJECTIVE: Screening for MDROs is an important mechanism for preventing spread but is resource intensive. The objective of this study was to develop automated tools that can predict colonization or infection risk using electronic health record (EHR) data, provide useful information to aid infection control, and guide empiric antibiotic coverage.
METHODS: We retrospectively developed a machine learning model to detect MRSA colonization and infection in undifferentiated patients at the time of sample collection from hospitalized patients at the University of Virginia Hospital. We used clinical and nonclinical features derived from on-admission and throughout-stay information from the patient\'s EHR data to build the model. In addition, we used a class of features derived from contact networks in EHR data; these network features can capture patients\' contacts with providers and other patients, improving model interpretability and accuracy for predicting the outcome of surveillance tests for MRSA. Finally, we explored heterogeneous models for different patient subpopulations, for example, those admitted to an intensive care unit or emergency department or those with specific testing histories, which perform better.
RESULTS: We found that the penalized logistic regression performs better than other methods, and this model\'s performance measured in terms of its receiver operating characteristics-area under the curve score improves by nearly 11% when we use polynomial (second-degree) transformation of the features. Some significant features in predicting MDRO risk include antibiotic use, surgery, use of devices, dialysis, patient\'s comorbidity conditions, and network features. Among these, network features add the most value and improve the model\'s performance by at least 15%. The penalized logistic regression model with the same transformation of features also performs better than other models for specific patient subpopulations.
CONCLUSIONS: Our study shows that MRSA risk prediction can be conducted quite effectively by machine learning methods using clinical and nonclinical features derived from EHR data. Network features are the most predictive and provide significant improvement over prior methods. Furthermore, heterogeneous prediction models for different patient subpopulations enhance the model\'s performance.

BACKGROUND: Nosocomial infections or hospital-acquired infections are a growing public health threat that increases patient morbidity and mortality. Patients at the highest risk are those in intensive care units. Therefore, our objective was to provide a pattern analysis of nosocomial infections that occurred in an adult surgical intensive care unit (ICU).
METHODS: This study was a retrospective observational study conducted in a 6-bed surgical intensive care unit (SICU) at An-Najah National University Hospital (NNUH) to detect the incidence of nosocomial infections from January 2020 until December 2021. The study group included 157 patients who received antibiotics during their stay in the SICU.
RESULTS: The incidence of nosocomial infections, either suspected or confirmed, in the SICU was 26.9% (95 out of 352 admitted patients). Pneumonia (36.8%) followed by skin and soft tissue infections (35.8%) were the most common causes. The most common causative microorganisms were in the following order: Pseudomonas aeruginosa (26.3%), Acinetobacter baumannii (25.3%), extended-spectrum beta lactamase (ESBL)-Escherichia coli (23.2%) and Klebsiella pneumonia (15.8%). The average hospital stay of patients with nosocomial infections in the SICU was 18.5 days.
CONCLUSIONS: The incidence of nosocomial infections is progressively increasing despite the current infection control measures, which accounts for an increased mortality rate among critically ill patients. The findings of this study may be beneficial in raising awareness to implement new strategies for the surveillance and prevention of hospital-acquired infections in Palestinian hospitals and health care centers.

UNASSIGNED: Healthcare-associated infections (HAIs) are among the most critical challenges for patients and healthcare providers. To achieve the goals of the surveillance system, it is necessary to identify its barriers and problems. This study aimed to identify the barriers and problems of the surveillance system for HAIs.
UNASSIGNED: This qualitative study was conducted using the content analysis method to investigate the challenges of this surveillance system from the perspective of 18 infection control nurses from hospitals in different cities of Iran with work experience of 1 to 15 years. Data were collected through semi-structured interviews and analyzed using the Lundman and Graneheim qualitative content analysis method.
UNASSIGNED: In this study, we found 2 categories and 7 subcategories. Two categories were barriers related to human resources and organizational barriers to infection control. The 7 subcategories included weakness of medical staff in adherence to health principles, obstacles related to patients, high workload and insufficient motivation, lack of staff knowledge, lack of human resources, functional and logistical weaknesses, and weaknesses in the surveillance system.
UNASSIGNED: To reduce problems and improve HAIs reporting, the HAIs surveillance system needs the support of health system officials and managers. This administrative and support focus can establish the framework for removing and lowering other barriers, such as the number of reported cases, physician and staff noncooperation, and the prevalence of HAIs. It can also bring HAIs cases closer to reality.

Microbial contamination in the hospital environment is a major concern for public health, since it significantly contributes to the onset of healthcare-associated infections (HAIs), which are further complicated by the alarming level of antimicrobial resistance (AMR) of HAI-associated pathogens. Chemical disinfection to control bioburden has a temporary effect and can favor the selection of resistant pathogens, as observed during the COVID-19 pandemic. Instead, probiotic-based sanitation (probiotic cleaning hygiene system, PCHS) was reported to stably abate pathogens, AMR, and HAIs. PCHS action is not rapid nor specific, being based on competitive exclusion, but the addition of lytic bacteriophages that quickly and specifically kill selected bacteria was shown to improve PCHS effectiveness. This study aimed to investigate the effect of such combined probiotic-phage sanitation (PCHSφ) in two Italian hospitals, targeting staphylococcal contamination. The results showed that PCHSφ could provide a significantly higher removal of staphylococci, including resistant strains, compared with disinfectants (-76%, p < 0.05) and PCHS alone (-50%, p < 0.05). Extraordinary sporadic chlorine disinfection appeared compatible with PCHSφ, while frequent routine chlorine usage inactivated the probiotic/phage components, preventing PCHSφ action. The collected data highlight the potential of a biological sanitation for better control of the infectious risk in healthcare facilities, without worsening pollution and AMR concerns.

Up to 48% of ventilated coronavirus disease 2019 (COVID-19) patients develop ventilator-associated pneumonia (VAP) during hospitalization in an ICU. Dysbiotic oral microbiota can colonize the lower respiratory tract and lead to VAP. It is recommended to introduce oral care strategies in the ICU to prevent VAP. In this study, we observed the impact of an oral hygienic protocol with tooth brushing on cultivable oral bacteriota, the incidence of HAI and patient safety among mechanically ventilated COVID-19 patients in an ICU setting.
In this prospective cohort study, we recruited 56 adult COVID-19 patients who qualified for mechanical ventilation. Patients were divided into 2 groups depending on the oral care procedure: standard and extended oral procedures with tooth brushing. Oral bacteriota samples were taken first within 36 h and after 7 days of intubation. Microorganisms were identified by MALDI/TOF mass spectrometry. bacterial health care-associated infection (HAI) cases were retrospectively analyzed by etiology. A PFGE study was performed for Klebsiella pneumoniae to check for clonal spreading of strains from oral bacteriota samples and HAI cases.
We observed significant dysbiosis and a decrease in cultivable oral bacteriota diversity, with a high frequency of potentially pathogenic species, including Acinetobacter baumannii and K. pneumoniae. The HAI incidence rate was high (55.2/1000 patient-days), most commonly of K. pneumoniae and A. baumannii etiologies, which correlated with the presence of A. baumannii and K. pneumoniae in the oral samples. Strains isolated from VAP cases were the same as oral isolates in 8 cases. The procedure with tooth brushing led to less frequent identification of A. baumannii in oral samples (55.6% vs. 5.3%, p = 0.001); however, it did not decrease the incidence of HAIs.
Dysbiotic oral bacteriota is an important source of respiratory pathogens. The introduction of tooth brushing in oral hygiene protocols in an ICU setting was effective in decreasing the extent of oral bacteriota dysbiosis; however, it did not reduce the risk of HAIs or mortality.
1072.6120.333.2020.

BACKGROUND: Multidrug-resistant organisms (MDROs) are prevalent on high-touch surfaces in multi-patient rooms.
OBJECTIVE: To quantify the impact of hanging single-use cleaning/disinfecting wipes next to each bed. Pre-specified outcomes were: (1) hospital-acquired infections (HAIs), (2) cleaning frequency, (3) MDRO room contamination, (4) new MDRO acquisitions, and (5) mortality.
METHODS: Clustered randomized crossover trial at Shamir Medical Center, Israel (October 2016 to January 2018). Clusters were randomly assigned to use for cleaning either single-use quaternary ammonium wipes (Clinell) or standard practices (reusable cloths and buckets with bleach). Six-month intervention periods were implemented in alternating sequence, separated by a washout period. Five high-touch surfaces were monitored by fluorescent markers. Study outcomes were compared between periods using generalized estimating equations, Poisson regression, and Cox proportional hazards models.
RESULTS: Overall, 7725 patients were included (47,670 person-days), 3793 patients in rooms with intervention cleaning and 3932 patients in rooms with standard practices. During the intervention, there was no significant difference in HAI rates (incidence rate ratio: 1.6; 95% confidence interval (CI): 0.7-3.5; P = 0.3). However, in intervention rooms, the frequency of environmental cleaning was higher (odds ratio: 3.73; 95% CI: 2.0-7.1; P < 0.0001), MDRO environmental contamination rate was insignificantly lower (odds ratio: 0.7; 95% CI: 0.5-1.0; P = 0.06), new MDRO acquisition rate was lower (hazard ratio: 0.4; 95% CI: 0.2-1.0; P = 0.04), and in-hospital mortality rate was lower (incidence rate ratio: 0.8; 95% CI: 0.7-1.0; P = 0.03).
CONCLUSIONS: Hanging single-use cleaning/disinfecting wipes next to each bed did not affect the HAI rates but did improve the frequency of cleaning, reduce MDRO environmental contamination, and was associated with reduced incidence of new MDRO acquisitions and reduced mortality. This is a feasible, recommended practice to improve patient outcomes in multi-patient rooms.

BACKGROUND: Cockroaches are common pests in homes and hospitals. They cause allergic reactions in some individuals and are potential vectors for various infectious pathogens. The study investigated the extent to which hospital cockroaches act as vectors and reservoirs of medically important fungal pathogens on their external surfaces.
METHODS: Cockroaches were captured from the selected hospital locations including the burn unit, adult surgical wards, pediatric oncology wards, intern hostel kitchen, and the central kitchen of a national referral teaching hospital in Tanzania. Normal saline washings from the external surface of cockroaches were cultured on standard mycological media to facilitate isolation and identification of medically important molds and yeasts. The susceptibility of Candida species isolates to fluconazole was tested using the Clinical and Laboratory Standards Institute (CLSI) M27-A3 microdilution method.
RESULTS: A total of 69 cockroaches were captured from various hospital sites between February and April 2017. All cockroaches captured were shown to carry medically important fungi. A total of 956 medically important fungi were isolated; 554 (57.9%) were of Candida species, 222 (23.2%) were of Aspergillus species, 30 (3.1%) were of​​​​​​​ Cladosporium species, 17 (1.8%) were of​​​​​​​ Rhizopus species, 11 (1.2%) were of​​​​​​​ Geotrichum species, nine (0.9%) were of​​​​​​​ Penicillium species, seven (0.7%) were of​​​​​​​ Alternaria species, six (0.6%) were of​​​​​​​ Fusarium species, three (0.3%) were of​​​​​​​ Mucor species, and 97 (10.1%) were of other species. Of the Aspergillus species, Aspergillus fumigatus (111, 50.0%) was the most commonly isolated, followed by Aspergillus niger (35, 15.8%) among the Aspergillus isolates. Out of the 103 selected isolates, 18 (17.5%) of the Candida isolates normally not intrinsically resistant to fluconazole demonstrated resistance to this drug. Resistance was most frequently found in Candida parapsilosis (3, 30%), Candida pseudotropicalis (10, 23.8%), and Candida glabrata (2, 18.2%). The isolates with the least proportion of resistance to fluconazole were Candida albicans (2, 6.3%).
CONCLUSIONS: Cockroaches from this hospital may act as reservoirs of medically important opportunistic fungi exhibiting resistance to fluconazole.

BACKGROUND: Co-infection rates increase in patients admitted to the Intensive Care Units. The aim of this study was to examine the Healthcare Associated Infections in critically ill adult patients infected with SARS-CoV-2.
METHODS: A retrospective observational study in adults with confirmed SARS-CoV-2 infection requiring intensive care unit admission was performed. From February 2020 to September 2021, healthcare records from a total of 118 patients were evaluated.
RESULTS: In the study period, 39 patients were diagnosed with at least 1 Healthcare Associated Infection (33.1%). The co-infection/co-colonisation rate >48 hours after admission was 29.0 per 1,000 person/ days (95 % CI 19.1-33.9). A total of 94 isolates were identified, the most common being Klebsiella spp, Clostridium difficile, Acinetobacter baumanii and Enterococcus spp. Associated outcomes for Healthcare Associated Infections have been identified: age >64 years (p= .003), length of Intensive Care Unit stay> 7 days (p= .002), Type 2 Diabetes mellitus (p= .019), cardiovascular disease (p= .021), inserted central venous catheter (p= .014), intubation (p< .001), APACHE II score >25 (p< .001), mechanical ventilation >48 hours (p= .003), and inserted urinary catheter (p= .002). The overall fatality rate of patients included in the study was 41.5% (n= 49), and it was found to be significantly higher in patients who acquired a Healthcare Associated Infection (n=26/39, 66.7%) compared to those who did not acquire it (n= 23/79, 29.1%) (OR= 4.87; 95% CI = 2.14-11.10; p< .001).
CONCLUSIONS: Our study showed high rates of Healthcare Associated Infections in critically ill adults with COVID-19. Associated factors for Healthcare Associated Infections acquisition and fatality in Intensive Care Units patients were identified as a good reason for a revision of existing infection control policies.

Case studies are utilized for training on National Healthcare Safety Network (NHSN) healthcare associated infection surveillance definitions. Item discrimination and item analysis were applied to case studies to identify questions that most accurately assess infection preventionists (IPs) application of surveillance definitions.

BACKGROUND: The ability of healthcare associate infection (HAI) pathogens to persist on fomites is crucial to their transmission within the healthcare setting, this study evaluated the persistence of three common HAI pathogens on fabrics materials commonly used in healthcare settings.
METHODS: Persistence of bacteria species on fabric was investigate by inoculating standardised inoculum prepared from the clinical isolates of Pseudomonas aeruginosa, Escherichia coli and Acinetobacter baumannii on sterile swatches of 100% cotton, microfibre and polyester. Viable bacteria persisting on the inoculated fabrics were evaluated immediate after inoculation and subsequently at 96-hour interval for 32 days using the drop plate technique. The effect of moisture on the persistence of the studied bacteria isolates was also evaluated.
RESULTS: Between 3 to 6 log reduction in the viability of the inoculated bacteria cells were observed after 32 days of inoculation on fabrics. Generally, lower viable cells were recovered from the microfibre fabrics compared to others, while higher viable cells were recovered from wet fabrics compared to the dry fabrics in this study.
CONCLUSIONS: This study demonstrated that HAI bacteria pathogens can persist for more than a month on hospital fabrics, and that their persistence can be enhanced by moisture.