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Background:Staphylococcus aureus–colonized hospitalized patients are at risk for invasive infection and can transmit S. aureus to other patients in the absence of symptoms. Infection isolation precautions do not reduce the risk of infection in colonized patients and are untenable in health systems with high rates of S. aureus colonization. Objective: We implemented an inpatient S. aureus screening and targeted decolonization program across hospital campuses to reduce transmission and invasive infection. We screen and decolonize for methicillin-susceptible S. aureus (MSSA) and methicillin-resistant S. aureus (MRSA) because MSSA makes up more than half of all S. aureus isolated from clinical cultures in our health system. Methods: All medicine, pediatrics, and transplant patients receive S. aureus nares culture at admission and upon change in level of care for medicine, and at admission and weekly for pediatrics and transplant patients. All S. aureus–colonized patients receive decolonization with nasal mupirocin ointment and chlorhexidine baths. Two implementation frameworks guide our processes for S. aureus screening and decolonization: the Consolidated Framework for Implementation Research, to evaluate factors affecting implementation at different levels of the health system, and the Dynamic Sustainability Framework, to account for iterative changes as the hospital setting and patient population change over time. Implementation interventions focus on education of patients and bedside nurses who perform S. aureus screening and decolonization; utilization of the electronic health record to identify patients for screening and/or decolonization and avoid human error; and introduction of a clinical nurse specialist to oversee the program and to provide iterative feedback. Results: At baseline, 21% of patients had S. aureus colonization, 20% of which was MRSA, and the MRSA bloodstream infection rate was 0.06 per 1,000 patient days. After program implementation, there was no change in S. aureus colonization and the MRSA bloodstream infection rate fell to 0.04 per 1,000 patient days. Screening compliance improved from 39% (N = 1,805) of eligible patients in the 6-month period before the introduction of the clinical nurse specialist to 52% (N = 2,024) after the introduction of the clinical nurse specialist. In the same periods, decolonization increased from 18.6% to 41% of eligible patients. Conclusions: We used 2 implementation frameworks to design our S. aureus screening and decolonization program and to make iterative changes to the program as it evolved to include new patient populations and different hospital settings. This resulted in a large-scale, sustainable, health system program for S. aureus control that avoids reliance on infection isolation precautions.
Background: Contaminated surfaces within patient rooms and on shared equipment is a major driver of healthcare-acquired infections (HAIs). The emergence of Candida auris in the New York City metropolitan area, a multidrug-resistant fungus with extended environmental viability, has made a standardized assessment of cleaning protocols even more urgent for our multihospital academic health system. We therefore sought to create an environmental surveillance protocol to detect C. auris and to assess patient room contamination after discharge cleaning by different chemicals and methods, including touch-free application using an electrostatic sprayer. Surfaces disinfected using touch-free methods may not appear disinfected when assessed by fluorescent tracer dye or ATP bioluminescent assay. Methods: We focused on surfaces within the patient zone which are touched by the patient or healthcare personnel prior to contact with the patient. Our protocol sampled the over-bed table, call button, oxygen meter, privacy curtain, and bed frame using nylon-flocked swabs dipped in nonbacteriostatic sterile saline. We swabbed a 36-cm2 surface area on each sample location shortly after the room was disinfected, immediately inoculated the swab on a blood agar 5% TSA plate, and then incubated the plate for 24 hours at 36°C. The contamination with common environmental bacteria was calculated as CFU per plate over swabbed surface area and a cutoff of 2.5 CFU/cm2 was used to determine whether a surface passed inspection. Limited data exist on acceptable microbial limits for healthcare settings, but the aforementioned cutoff has been used in food preparation. Results: Over a year-long period, terminal cleaning had an overall fail rate of 6.5% for 413 surfaces swabbed. We used the protocol to compare the normal application of either peracetic acid/hydrogen peroxide or bleach using microfiber cloths to a new method using sodium dichloroisocyanurate (NaDCC) applied with microfiber cloths and electrostatic sprayers. The normal protocol had a fail rate of 9%, and NaDCC had a failure rate of 2.5%. The oxygen meter had the highest normal method failure rate (18.2%), whereas the curtain had the highest NaDCC method failure rate (11%). In addition, we swabbed 7 rooms previously occupied by C. auris–colonized patients for C. auris contamination of environmental surfaces, including the mobile medical equipment of the 4 patient care units that contained these rooms. We did not find any C. auris, and we continue data collection. Conclusions: A systematic environmental surveillance system is critical for healthcare systems to assess touch-free disinfection and identify MDRO contamination of surfaces.
Background: Whole-genome sequencing (WGS) has a high discriminatory power in confirming outbreaks. Outbreak investigation models that categorize the possibility of an outbreak based on the degree of genetic relatedness of isolates are highly dependent on the single-nucleotide polymorphism (SNP) threshold used. Methods: NYU Langone Medical center is a 725-bed academic center that has implemented WGS of methicillin-resistant Staphylococcus aureus (MRSA) isolates since 2016. Patients admitted to a medical or intensive care unit were screened on admission and transfer. The first surveillance and clinical MRSA isolate during each hospitalization was sequenced. We conducted a retrospective analysis to identify strong epidemiologic links among patients involved in genetically related clusters. We used different SNP thresholds to define genetic relatedness to identify the optimal threshold that should prompt an outbreak investigation. We considered strong hospital epidemiologic links sharing the same room or unit or having resided in the same room or unit within 7 days. A pairwise analysis was conducted to compare the epidemiologic links among patients involved in genetically related clusters. Results: Among 1,070 isolates, our analysis focused on 777 belonging to USA100 and USA300 clones. For USA100 isolates, we identified 8, 14, and 20 clusters comprising of 16, 29, and 42 patients when the threshold for genetic relatedness was set at 20, 40, and 60 SNP differences, respectively. Patients identified in a cluster yielded a strong hospital epidemiologic link in 62.5%, 87.5%, and 91.7% of cases (Fig. 1). For USA300 isolates, SNP differences of 10, 20, and 30 were used, identifying 20, 34, and 40 clusters of 43, 79, and 127 patients. The expansion of the threshold from 10 to 30 resulted in a decrease of the percentage of pairwise analyses with a strong hospital epidemiologic link from 57.7% to 13.6% by increasing 13-fold the number of analyses that were conducted to identify only 3 times more cases with strong epidemiologic links (Fig. 2). Conclusions: The results of our study indicate that SNPs thresholds determined by intrapatient variability of MRSA isolates might need to be tailored to the individual setting to guide infection control interventions because optimal thresholds might vary depending on characteristics of the population, MRSA isolates, and screening practices. Establishing conservative thresholds might allow the identification and quantification over time of the locations (eg, rooms or units) where transmission is occurring as well as the investigation of the clusters without strong epidemiologic links that might be valuable in elucidating unrecognized routes of transmission.
The aim of this study was to examine cross-sectionally whether higher cardiorespiratory fitness (CRF) might favorably modify amyloid-β (Aβ)-related decrements in cognition in a cohort of late-middle-aged adults at risk for Alzheimer’s disease (AD). Sixty-nine enrollees in the Wisconsin Registry for Alzheimer’s Prevention participated in this study. They completed a comprehensive neuropsychological exam, underwent 11C Pittsburgh Compound B (PiB)-PET imaging, and performed a graded treadmill exercise test to volitional exhaustion. Peak oxygen consumption (VO2peak) during the exercise test was used as the index of CRF. Forty-five participants also underwent lumbar puncture for collection of cerebrospinal fluid (CSF) samples, from which Aβ42 was immunoassayed. Covariate-adjusted regression analyses were used to test whether the association between Aβ and cognition was modified by CRF. There were significant VO2peak*PiB-PET interactions for Immediate Memory (p=.041) and Verbal Learning & Memory (p=.025). There were also significant VO2peak*CSF Aβ42 interactions for Immediate Memory (p<.001) and Verbal Learning & Memory (p<.001). Specifically, in the context of high Aβ burden, that is, increased PiB-PET binding or reduced CSF Aβ42, individuals with higher CRF exhibited significantly better cognition compared with individuals with lower CRF. In a late-middle-aged, at-risk cohort, higher CRF is associated with a diminution of Aβ-related effects on cognition. These findings suggest that exercise might play an important role in the prevention of AD. (JINS, 2015, 21, 841–850)