Interventional Effect of Nanosilver Paint on Fungal Load of Indoor Air in a Hospital Ward

Hospital ward environments contain various types of microorganisms, in which fungal agents are one of the main contaminants that may cause hospital-acquired infections. Regarding this, the aim of the present study was to evaluate the effect of nanosilver paint on reducing fungal contaminants of indoor air in an educational, research, and treatment center. Two rooms in the hematology ward were selected. One room was painted using usual paint (control room) and the other room was painted with paint containing nanosilver particles (experimental room). One hundred and twelve samples were collected using active (Anderson BioSampler) and passive (settle plate or open plate) air sampling techniques. The samples were incubated for 3–7 days at 35°C, and the positive fungal cultures were examined according to morphological and microscopic characteristics. Following active sampling, the mean and standard deviation of the number of colony-forming units (CFU/m3) of fungi colonies in the experimental and control rooms were 29.21 ± 17.99 and 22.50 ± 10.02 before intervention and 13.79 ± 6.20 and 31.07 ± 21.1 after intervention, respectively. Following passive sampling, the number of CFU/plate in the experimental and control rooms was 6 and 0 before and 1and 1 after intervention, respectively. The use of the nanosilver paint was effective in reducing air fungal contamination. Moreover, the active sampling method was more sensitive to measuring the concentration changes for fungal bioaerosols.

Spatiotemporal Prediction of the Occurrence of Vancomycin-resistant Enterococcus

Background: Vancomycin-resistant enterococci (VRE) is the cause of severe patient health and monetary burdens. Antibiotic use is a confounding effect to predict VRE in patients, but the antibiotic use of patients who may have frequented the same ward as the patient in question is often neglected. This study investigated how the occurrence and spread of VRE can be explained by patient movements between hospital wards and their antibiotic use.Methods: Intrahospital patient movements, antibiotic use and PCR screening data were used from a hospital in the Netherlands. The PageRank algorithm was used to calculate two daily centrality measures based on the spatiotemporal graph to summarise the flow of patients and antibiotics at the ward level. A decision tree model was used to determine a simple set of rules to estimate the daily probability of VRE occurrence for each hospital ward. The model performance was improved using a random forest model and compared using 30% test sample.Results: Centrality covariates summarising the flow of patients and their antibiotic use between hospital wards can be used to predict the daily occurrence of VRE at the hospital ward level. The decision tree model produced a simple set of rules that can be used to determine the daily probability of VRE occurrence for each hospital ward. An acceptable area under the ROC curve (AUC) of 0.755 was achieved using the decision tree model and an excellent AUC of 0.883 by the random forest model on the test set. These results confirms that the random forest model performs better than a single decision tree for all levels of model sensitivity and specificity on data not used to estimate the models.Conclusion: This study showed how the movements of patients inside hospitals and their use of antibiotics could predict VRE occurrence at the ward level. Two daily centrality measures were proposed to summarise the flow of patients and antibiotics at the ward level. An early warning system for VRE can be developed to test and further develop infection prevention plans and outbreak strategies using these results.

Organization of a Hospital Ward Aimed at Admitting Patients with SARS-CoV-2: An Economic and Epidemiological Perspective

The SARS-CoV-2 epidemic requires dynamic action on the part of the entire health care system to provide infected patients whose condition requires hospitalization with access to appropriate medical care and infrastructure, including oxygen devices and ventilators. The demand for specialized inpatient care has increased rapidly and in many areas exceeds the resources available to date. Individual hospitals must make investment and organizational decisions to increase their capacity to handle patients with SARS-CoV-2. The aim of the article is to present the organizational and investment steps taken to establish and maintain an infectious hospital ward as well as the clinical and financial consequences of this decision. The study was conducted in a hospital ward that was launched at the end of October 2020 to care for patients with SARS-CoV-2. A case study method was used. The department was characterized taking into account its importance for: (1) the regional level of health coverage of the population, (2) the organization of the hospital’s activities, (3) the financial and economic situation of the hospital.

Evaluation of the Initial General Ward Early Warning Score and ICU Admission, Hospital Length of Stay and Mortality

Introduction: Despite widespread implementation of the Early Warning Score (EWS) in hospitals, its effect on patient outcomes remains mostly unknown. We aimed to evaluate associations between the initial EWS and in-hospital mortality, intensive care unit (ICU) admission, and hospital length of stay (LOS). Methods: We performed a retrospective cohort study of adult patients admitted to a general hospital ward between July 1, 2014–December 31, 2017. Data were obtained from electronic health records (EHR). The primary outcome was in-hospital mortality. Secondary outcomes were ICU admission and hospital LOS. We categorized patients into three risk groups (low, medium or high risk of clinical deterioration) based on EWS. Descriptive analyses were used. Results: After applying inclusion and exclusion criteria, we included 53,180 patients for analysis. We found that the initial (low- vs high-risk) EWS was associated with an increased in-hospital mortality (1.5% vs 25.3%, P <0.001), an increased ICU admission rate (3.1% vs 17.6%, P <0.001), and an extended hospital LOS (4.0 days vs 8.0 days, P <0.001). Conclusion: Our findings suggest that an initial high-risk EWS in patients admitted to a general hospital ward was associated with an increased risk of in-hospital mortality, ICU admission, and prolonged hospital LOS. Close monitoring and precise documentation of the EWS in the EHR may facilitate predicting poor outcomes in individual hospitalized patients and help to identify patients for whom timely and adequate management may improve outcomes.