cleanSURFACES® intervention reduces microbial activity on surfaces in a senior care facility.

As one of the top public health challenges outlined by the Centers for Disease Control (CDC), estimates report that hospital acquired infections (HAIs) claim the lives of 99,000 Americans and cost healthcare providers over $28 billion each year. In addition to underlying conditions related to age, elderly patients in long-term care facilities are at an elevated risk of acquiring HAIs. A large percentage of HAIs is attributable to contaminated surfaces and medical devices. To that end, this study utilized a metatranscriptomic sequencing workflow (CSI-Dx™) to profile active microbial communities from surfaces in the HJ Heinz Community Living Center, a long-term care facility in the Veterans Affairs Pittsburgh Health Care System. Swabs were collected from high-touch surfaces (Keyboard, Ledge, Workstation on Wheels, Worksurfaces) before (Baseline) and after cleanSURFACES® were installed at 4 timepoints (Day 1, Day 7, Day 14, and Day 30). Microbial richness was significantly reduced after cleanSURFACES® intervention (Wilcoxon test with Holm correction, p=0.000179). Beta diversity results revealed distinct clustering between Baseline and Post-intervention samples (Adonis, p<0.001). Reduction in bacterial (Staphylococcus aureus, Staphylococcus epidermidis, Staphylococcus hominis) and fungal (Malassezia restricta, Candida albicans, Candida glabrata, and Candida orthopsilosis) expression of opportunistic pathogens was observed. Additionally, a subset of taxa (Corynebacterium, Cutibacterium acnes, and Ralstonia pickettii) was present in specific Post-intervention timepoints and surface types. This study revealed decreased microbial activity, highlighting the potential for the combinatorial application of cleanSURFACES® and regular decontamination practices to reduce the prevalence of microbes causing HAIs.

Selective Serotonin Reuptake Inhibitor/Serotonin-Norepinephrine Reuptake Inhibitor Use as a Predictor of a Diagnosis of Restless Legs Syndrome.

OBJECTIVE/BACKGROUND: Because restless legs syndrome (RLS) is a problematic syndrome, demonstrating an association between use of selective serotonin reuptake inhibitors (SSRIs)/serotonin-norepinephrine reuptake inhibitors (SNRIs) and RLS may help direct patient care. The goals of this study were (1) to establish the incidence of RLS in mental health patients being treated with SSRIs or SNRIs in a local Veterans Affairs medical center and (2) to evaluate the frequency with which certain SSRIs or SNRIs are associated with RLS and the trend in frequency of the diagnosis since the revision of the criteria for RLS offered by the International Restless Leg Syndrome Study Group (IRLSSG), the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), and the International Classification of Sleep Disorders, Revised (ICSD-3). METHODS: A retrospective chart review was used to evaluate the number of patients receiving SSRI/SNRI therapy with and without a diagnosis of RLS, with the date of the RLS diagnosis and initiation of SSRI/SNRI therapy noted. The frequency with which certain SSRIs/SNRIs were associated with RLS, and the frequency of RLS diagnoses since January 2012 were also noted. Descriptive statistics and logistic regression were used for data analysis. RESULTS: A total of 254 charts were reviewed. A majority of the patients (89.8%) were male, and 14 (5.5%) were diagnosed with RLS. A logistic regression equation approached significance in predicting RLS (P=0.053). Age and sex emerged as significant predictors of RLS. The prevalence of any individual SSRI or SNRI being associated with RLS was indeterminable. No difference was seen in the number of RLS diagnoses since the refining of the IRLSSG, DSM-5, and ICSD-3 criteria. CONCLUSIONS: The use of SSRIs/SNRIs does not seem to be associated with a diagnosis of RLS. In addition, the diagnosis of RLS does not seem to have become more common since the revision of the diagnostic criteria for the disorder.