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.

UNASSIGNED: Carbapenem-resistant Enterobacterales (CRE) are considered urgent, antibiotic-resistant threats in the U.S. and are of global concern. Active collaboration between public health authorities and healthcare facilities and providers will be necessary to prevent and contain these organisms.
UNASSIGNED: To describe the epidemiology of CRE in Kentucky and to discuss challenges and successes with building and sustaining an effective prevention and containment program.
UNASSIGNED: Retrospective descriptive summary of CRE isolates reported by healthcare providers, facilities, and laboratories in Kentucky from 2013 through 2020. Data available from case reporting forms and laboratory testing are summarized.
UNASSIGNED: From 2013 through 2020, 1805 CRE were reported from 1666 individuals; median age was 66 years and 44% were male. Although most reports were from hospitalized individuals, nearly one-third were from individuals not hospitalized in acute-care hospital settings. The number of reports generally increased over time, with 111 CRE isolates in 2013 and 477 in 2020. Klebsiella pneumoniae was the most frequently reported CRE. Of the 29% of CRE with identified carbapenemase production (CP-CRE), Klebsiella pneumoniae carbapenemase (KPC) was most common (78%). Surveillance and reporting resulted in identification and active investigation of 11 outbreaks of CP-CRE.
UNASSIGNED: There are challenges with developing, implementing, and sustaining a consistent, effective response to identifying, preventing, and containing CRE. Ongoing public health and facility resources will be necessary to prevent and contain antibiotic-resistant threats and other concerning organisms.

Healthcare settings have a high prevalence of infectious agents. This narrative review examines the existing evidence regarding infection prevention and control (IPC) using the WHO Infection Prevention and Control Assessment Framework (IPCAF) tool in healthcare facilities. A total of 13 full length papers from Africa, Asia and Europe were considered for this review. The findings showed that there are discrepancies in the IPCAF values from insufficient to advanced level. The current review shows an advanced IPCAF level in middle income and high income countries. Low income countries showed a lower IPCAF score. There is a need to enhance the IPC capacity building and to supply infection prevention resources to prevent healthcare associated infection (HAI) with a focus on low income countries.

UNASSIGNED: Hospital-acquired infections constitute a significant source of morbidity and mortality for both patients and healthcare professionals. Nursing professionals constitute an integral component of any quality-related program in a hospital, given their oversight and provision of nearly all healthcare services. Nurses\' knowledge and attitudes play a significant role in healthcare delivery. Within Saudi Arabia, the prevalence of hospital-acquired infections in hospital settings has prompted a growing emphasis on evaluating nursing knowledge and adherence to practice standards aimed at hospital-acquired infection prevention.
UNASSIGNED: This single-center cross-sectional study was conducted at the emergency department of King Faisal Medical Complex, Taif, between October and December 2022, involving 168 nurses. The study utilized a pre-validated structured online questionnaire comprising three sections: demographics, knowledge assessment, and practice evaluation. Knowledge and practice levels were categorized as good, moderate, and poor using quartiles.
UNASSIGNED: The study encompassed 168 nurses employed in the emergency department of the hospital, revealing their proficiency in standard practices for preventing hospital-acquired infections. Notably, 63.8% of participants demonstrated a commendable \"Good\" level of knowledge, while 10.6% exhibited a \"Moderate\" level and 25.5% manifested a \"Poor\" level in terms of knowledge. Similarly, concerning practice levels, 56.4% showcased a commendable \"Good\" practice level, 22.3% maintained a \"Moderate\" practice level, and 21.3% presented a \"Poor\" practice level. Chi-square analysis unveiled a significant association between age and knowledge levels (p = 0.000). In addition, age (p = 0.000) and years of clinical experience (p = 0.000) were significantly linked to nurses\' practice levels The nurses aged 40-50 years (82%) and those with 10-15 years of clinical experience (83.3%) showed good levels of knowledge and practice, respectively. Overall, most of the nurses demonstrated effective knowledge and compliance with infection prevention practices.
UNASSIGNED: Sociodemographic factors such as age and clinical experience exert a notable impact on nurses\' knowledge and practices regarding hospital-acquired infections.

Healthcare-associated infections caused by multi-drug-resistant pathogens are increasing globally, and current antimicrobial options have limited efficacy against these robust species. The WHO details the critically important bacterial and fungal species that are often associated with medical device HAIs. The effective sterilization of medical devices plays a key role in preventing infectious disease morbidity and mortality. A lack of adherence to protocol and limitations associated with each sterilization modality, however, allows for the incidence of disease. Furthermore, issues relating to carcinogenic emissions from ethylene oxide gas (EtO) have motivated the EPA to propose limiting EtO use or seeking alternative sterilization methods for medical devices. The Food and Drug Administration supports the sterilization of healthcare products using low-temperature VH2O2 as an alternative to EtO. With advances in biomaterial and medical devices and the increasing use of combination products, current sterilization modalities are becoming limited. Novel approaches to disinfection and sterilization of medical devices, biomaterials, and therapeutics are warranted to safeguard public health. Bacteriophages, endolysins, and antimicrobial peptides are considered promising options for the prophylactic and meta-phylactic control of infectious diseases. This timely review discusses the application of these biologics as antimicrobial agents against critically important WHO pathogens, including ESKAPE bacterial species.

Effective disinfection procedures in healthcare facilities are essential to prevent transmission. Chemical disinfectants, hydrogen peroxide vapour (HPV) systems and ultraviolet (UV) light are commonly used methods. An emerging method, violet-blue light at 405 nm, has shown promise for surface disinfection. Its antimicrobial properties are based on producing reactive oxygen species (ROS) that lead to the inactivation of pathogens. Studies have shown significant efficacy in reducing bacterial levels on surfaces and in the air, reducing nosocomial infections. The aim of this study was to evaluate the antimicrobial effectiveness of violet-blue (405 nm) LED lamps on high-contact surfaces in a hospital infection-control laboratory. High-contact surfaces were sampled before and after 7 days of exposure to violet-blue light. In addition, the effect of violet-blue light on MRSA-contaminated surfaces was investigated. Exposure to violet-blue light significantly reduced the number of bacteria, yeasts and moulds on the sampled surfaces. The incubator handle showed a low microbial load and no growth after irradiation. The worktable and sink showed an inconsistent reduction due to shaded areas. In the second experiment, violet-blue light significantly reduced the microbial load of MRSA on surfaces, with a greater reduction on steel surfaces than on plastic surfaces. Violet-blue light at 405 nm has proven to be an effective tool for pathogen inactivation in healthcare settings Violet-blue light shows promise as an additional and integrated tool to reduce microbial contamination in hospital environments but must be used in combination with standard cleaning practices and infection control protocols. Further research is needed to optimise the violet-blue, 405 nm disinfection method.

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.

BACKGROUND: Increasing incidence of Enterococcus faecium resistant to key antimicrobials used in therapy of hospitalized patients is a worrisome phenomenon observed worldwide. Our aim was to characterize a tigecycline-, linezolid- and vancomycin-resistant E. faecium isolate with the vanA and vanB genes, originating from a hematoma of a patient hospitalized in an intensive care unit in Poland.
METHODS: Antimicrobial susceptibility (a broad panel) was tested using gradient tests with predefined antibiotic concentrations. The complete genome sequence was obtained from a mixed assembly of Illumina MiSeq and Oxford Nanopore\'s MinION reads. The genome was analyzed with appropriate tools available at the Center for Genomic Epidemiology, PubMLST and GenBank. Transferability of oxazolidinone, tigecycline and vancomycin resistance genes was investigated by conjugation, followed by PCR screen of transconjugants for antimicrobial resistance genes and plasmid rep genes characteristic for the donor and genomic sequencing of selected transconjugants.
RESULTS: The isolate was resistant to most antimicrobials tested; susceptibility to daptomycin, erythromycin and chloramphenicol was significantly reduced, and only oritavancin retained the full activity. The isolate represented sequence type 18 (ST18) and carried vanA, vanB, poxtA, fexB, tet(L), tet(M), aac(6\')-aph(2\'\'), ant(6)-Ia and ant(6\')-Ii. The vanA, poxtA and tet(M) genes located on ~ 40-kb plasmids were transferable by conjugation yielding transconjugants resistant to vancomycin, linezolid and tigecycline. The substitutions in LiaS, putative histidine kinase, SulP, putative sulfate transporter, RpoB and RpoC were potential determinants of an elevated daptomycin MIC. Comparative analyses of the studied isolate with E. faecium isolates from other countries revealed its similarity to ST18 isolates from Ireland and Uganda from human infections.
CONCLUSIONS: We provide the detailed characteristics of the genomic determinants of antimicrobial resistance of a clinical E. faecium demonstrating the concomitant presence of both vanA and vanB and resistance to vancomycin, linezolid, tigecycline and several other compounds and decreased daptomycin susceptibility. This isolate is a striking example of an accumulation of resistance determinants involving various mechanisms by a single hospital strain.

The prevalence of HAI among COVID-19 patients ranged between 4.8% and 42.8% with the highest occurrence observed in critically ill patients. The present study aimed to evaluate the clinical features of HAI in severe and critical COVID-19 patients, their microbiological characteristics, and the attributable risk factors.
This is an analytical observational, retrospective single-center, cohort study that included 723 patients with severe-critical COVID-19 admitted to Saint George Hospital between September 2020 and February 2021. Data collection included demographic variables (sex, age), comorbidities, laboratory findings, HAI types and agents, COVID-19 treatment modalities, hospitalization settings, length of stay, and mortality rate. Data was analyzed using SPSS version 25.
The prevalence of patients developing HAI was 7.3% (53 of 723). Five types of nosocomial bacterial infections were tracked noting ventilator-associated pneumonia (41.26%), catheter-associated urinary tract infection (28.6%), hospital-acquired pneumonia (17.44%), catheter-related bloodstream infection (6.35%), and bloodstream infection (6.35%). Binary logistic analysis showed that HAI are statistically affected by four factors noting patients\' age (p = 0.039), Length of Stay (p < 0.001), BIPAP (p = 0.019), and mechanical ventilation (p < 0.001). The risk of having HAI increases 3.930 times in case of mechanical ventilation, 2.366 times in case of BIPAP, 1.148 times when the LOS increases 1 day, and 1.029 times when the age is higher with 1 year.
Since the prevalence of HAI is high among severe and critical COVID-19 patients, it is important to prepare a treatment with diagnostic, preventative, and control measures for this infection.

BACKGROUND: Healthcare-associated infections (HAI) and bacterial antimicrobial resistance posed a therapeutic risk during the coronavirus disease 2019 (COVID-19) pandemic. The aim of this study was to analyze the HAIs in COVID-19 patients in the Intensive Care Unit (ICU) and non-ICU at the University Hospital in Krakow (UHK) with an emphasis on the susceptibility of the most frequently isolated pathogens and the prevalence of extensively drug resistant (XDR) microorganisms.
METHODS: This laboratory-based study was carried out at the University Hospital in Krakow in the ICU and non-ICUs dedicated to COVID-19 patients between May 2021 and January 2022. All isolates of Klebsiella pneumoniae were analyzed using PFGE protocol.
RESULTS: 292 independent HAI cases were identified, with the predominance of urinary tract infections (UTI), especially in the non-ICU setting. The most common ICU syndrome was pneumonia (PNA). The prevalence of XDR organisms was 22.6% in the ICU and 14.8% in non-ICUs among all isolates. The incidence of carbapenem-resistant Enterobacteriaceae infection was 24.8 cases per 10,000 hospitalizations and the carbapenem-resistant A. baumannii infection incidence was 208.8 cases per 10,000 hospitalizations. The prevalence of XDR strains was highest in Acinetobacter spp, in PNA cases. The PFGE typing demonstrated that almost all XDR strains varied widely from each other.
CONCLUSIONS: In this study, there was a high incidence of HAI in COVID-19 patients, especially when compared to Western Europe and the United States. Similarly, the prevalence of XDR microorganisms, especially XDR-A.baumannii, was also high. PFGE did not confirm the horizontal spread of any organism strains.