Abstract Background There is emerging evidence that implementation of an automated hand hygiene monitoring system (AHHMS) must be part of a multimodal hand hygiene (HH) program that includes complementary strategies. There are few published studies describing in detail the intervention strategies used with an AHHMS. Methods An AHHMS that provides group HH performance rates (100 x HH product dispenses divided by the number of room entries plus exits) was implemented on two Acute Care (AC) units and six long-term care (LTC) units at a Veterans Affairs Medical Center from March 2021 through April 2022. After a 4-week baseline period and 2.5-week washout period, the 52-week intervention period included many components, such as weekly huddles, unit nurse manager engagement, vendor provided clinician-based training and feedback, leadership support, unit recognition, signage and development of a new slogan to remind colleagues to perform HH. Statistical analysis was performed with a Poisson general additive mixed model. Results During the 4-week baseline period, the median HH performance rate was 18.6 (95% CI: [16.5, 21.0]) for all 8 units. During the intervention period, the median HH rate increased to 21.6 [19.1, 24.4], and during the last 4 weeks of the intervention period (exactly 1 year after baseline), the 8 units exhibited a median HH rate of 25.1 [22.2, 28.4], (p < 0.0001) [Figure 1]. The median HH rate increased from 17.5 to 20.0 (p < 0.0001) in LTC units and from 22.9 to 27.2 (p < 0.0001) in AC units. The intervention increased the use of hand sanitizer from 57.5% during baseline to 65.1% (p < 0.0001). The increase in HH rates was due to HH events increasing from 88,758 dispenses during the baseline to 123,722 dispenses during the last 4 weeks of the intervention. Direct observation results during the same periods showed HH compliance ranging from 61-86%. Figure 1- Monthly Hand Hygiene Performance Rates for all Units The green curve shows the change in the median HH rate during the intervention period compared to the baseline and washout periods, with vertical bars showing 95% confidence intervals for the monthly HH rate. Conclusion The intervention increased hand sanitizer usage and HH performance rates for all units. AC units were consistently better than LTC units, which have more visitors and more mobile veterans. Further HH improvement will rely on continued implementation of complementary strategies and long-term monitoring. Disclosures James W. Arbogast, PhD, GOJO Industries, Inc.: employee Pamela Wagner, RN MSN CPPS, GOJO Industries, Inc: Employee of GOJO Gregory A. Robbins, BS, GOJO Industries, Inc.: Current employee of GOJO Industries, Inc. Albert E. Parker, PhD, GOJO Industries: Advisor/Consultant John M. Boyce, MD, Diversey: Advisor/Consultant|Diversey: Expert Testimony|Diversey: Travel support|GOJO Industries: Advisor/Consultant|GOJO Industries: Expert Testimony|GOJO Industries: Travel support|Sodexo Healthcare: Advisor/Consultant.
Standard Gibbs sampling applied to a multivariate normal distribution with a specified precision matrix is equivalent in fundamental ways to the Gauss-Seidel iterative solution of linear equations in the precision matrix. Specifically, the iteration operators, the conditions under which convergence occurs, and geometric convergence factors (and rates) are identical. These results hold for arbitrary matrix splittings from classical iterative methods in numerical linear algebra giving easy access to mature results in that field, including existing convergence results for antithetic-variable Gibbs sampling, REGS sampling, and generalizations. Hence, efficient deterministic stationary relaxation schemes lead to efficient generalizations of Gibbs sampling. The technique of polynomial acceleration that significantly improves the convergence rate of an iterative solver derived from a \emph{symmetric} matrix splitting may be applied to accelerate the equivalent generalized Gibbs sampler. Identicality of error polynomials guarantees convergence of the inhomogeneous Markov chain, while equality of convergence factors ensures that the optimal solver leads to the optimal sampler. Numerical examples are presented, including a Chebyshev accelerated SSOR Gibbs sampler applied to a stylized demonstration of low-level Bayesian image reconstruction in a large 3-dimensional linear inverse problem.
Biofilm methods consist of four distinct steps: growing the biofilm in a relevant model, treating the mature biofilm, harvesting the biofilm from the surface and disaggregating the clumps, and analyzing the sample. Of the four steps, harvesting and disaggregation are the least studied but nonetheless critical when considering the potential for test bias. This article demonstrates commonly used harvesting and disaggregation techniques for biofilm grown on three different surfaces. The three biofilm harvesting and disaggregation techniques, gleaned from an extensive literature review, include vortexing and sonication, scraping and homogenization, and scraping, vortexing and sonication. Two surface types are considered: hard non-porous (polycarbonate and borosilicate glass) and porous (silicone). Additionally, we provide recommendations for the minimum information that should be included when reporting the harvesting technique followed and an accompanying method to check for bias.
Over the period January 2004 to present, the seas have experienced the lack of any warming, as finally properly measured in the ARGO project where a global array of more than 3,600 free-drifting profiling floats has measured the temperature of the upper 2000 m of the sea as it was not possible before.The warming of the seas has been a negligible 1.1 10 3 °C/year on average over the layer 0 -2000 dbar below the accuracy of the measure.Over the period January 2000 to present, the measured land and sea temperatures of the less reliable GISS, NCDC and HADCRUT4 data sets have shown a small warming of 4.2 10 3 °C/year on average.Same period, the climate models propose for the land and sea temperatures an unrealistic warming of 20.5 10 3 °C/year (average of CMIP3) and 18.2 10 3 °C/year (average of the CMIP5).The "inconvenient truth" is that climate models are predicting a warming when there is no warming rather than simply overestimating the warming as discussed so far.The paper presents the failed validation of the climate models since their introduction and suggests the reasons of their failure in the overrated effect of the changed composition of the atmosphere and the neglected natural oscillations.
The AOAC Use-dilution methods (UDM) 955.15 (Staphylococcus aureus) and 964.02 (Pseudomonas aeruginosa) are laboratory methods used to substantiate antimicrobial efficacy claims for liquid disinfectants on inanimate surfaces. The UDM is accepted by the U.S. Environmental Protection Agency for the purpose of product registration. To attain a hospital-level claim, testing against S. aureus and P. aeruginosa is required, and the product must pass against both microbes. Currently, the UDM's performance standard for a single 60-carrier test is the same for both microbes, and allows up to one positive carrier for the product to be considered as a pass. In this paper, the performance standards for these methods are reassessed using data from a 2009 five-laboratory collaborative study and a recently published statistical model. The reassessment focuses on the pass-error rate for ineffective products and the fail-error rate for highly effective products. The calculations indicate that the pass-error rate is between 9 and 24% and the fail-error rate between 18 and 23% when the current performance standard is used for a single test. For product registration, a smaller pass-error rate (1%) historically has been maintained by requiring that a disinfectant pass three UDM tests for each of the two microbes; however, the calculations also indicate that the fail-error rate is between 42 and 45%. This large fail-error rate is a compelling reason to consider a new performance standard for the two UDM methods, 955.15 (S. aureus) and 964.02 (P. aeruginosa). One alternative performance standard allows no more than six positive carriers out of 60 as a pass when using P. aeruginosa and no more than three positive carriers out of 60 when using S. aureus. In addition, the new performance standard requires that three UDM tests be performed with each of the two microbes, and the disinfectant must pass all six tests to be considered efficacious. The statistical calculations for this alternative performance standard indicate that the pass-error rate is no more than 3%, while the fail-error rate is as small as 5%. Based on these error rate calculations, proposed revisions to the performance standards for AOAC Methods 955.15 and 964.02 are provided.
Alcohol-based hand rubs (ABHR) range in alcohol concentration from 60-95% and are available in a variety of delivery formats, such as rinses, gels, and foams. Recent studies suggest that some ABHR foams dry too slowly, thereby encouraging the use of inadequate volumes. This study investigates the influence of product volume, delivery format, and alcohol concentration on dry-time and antimicrobial efficacy of ABHR foams, gels and rinses. ABHR dry-times were measured using volunteers to determine the influences of product volume, delivery format, and alcohol concentration. ABHR efficacies were evaluated according to the European Standard for Hygienic Hand Disinfection (EN 1500) using 3-mL application volumes rubbed for 30 s, and additionally, using volumes of the products determined to rub dry in 30 s. Volumes of six ABHR determined to rub dry in 30 s ranged from 1.7 mL to 2.1 mL, and the rate of drying varied significantly between products. ABHR dry-times increased linearly with application volume and decreased linearly with increasing alcohol concentration, but were not significantly influenced by product format. An ABHR foam (70% EtOH), rinse (80% EtOH), and gel (90% EtOH) each met EN 1500 efficacy requirements when tested at a volume of 3 mL, but failed when tested at volumes that dried in 30 s. Application volume is the primary driver of ABHR dry-time and efficacy, whereas delivery format does not significantly influence either. Although products with greater alcohol concentration dry more quickly, volumes required to meet EN 1500 can take longer than 30 s to dry, even when alcohol concentration is as high as 90%. Future studies are needed to better understand application volumes actually used by healthcare workers in practice, and to understand the clinical efficacy of ABHR at such volumes.
A performance standard for a disinfectant test method can be evaluated by quantifying the (Type I) pass-error rate for ineffective products and the (Type II) fail-error rate for highly effective products. This paper shows how to calculate these error rates for test methods where the log reduction in a microbial population is used as a measure of antimicrobial efficacy. The calculations can be used to assess performance standards that may require multiple tests of multiple microbes at multiple laboratories. Notably, the error rates account for among-laboratory variance of the log reductions estimated from a multilaboratory data set and the correlation among tests of different microbes conducted in the same laboratory. Performance standards that require that a disinfectant product pass all tests or multiple tests on average, are considered. The proposed statistical methodology is flexible and allows for a different acceptable outcome for each microbe tested, since, for example, variability may be different for different microbes. The approach can also be applied to semiquantitative methods for which product efficacy is reported as the number of positive carriers out of a treated set and the density of the microbes on control carriers is quantified, thereby allowing a log reduction to be calculated. Therefore, using the approach described in this paper, the error rates can also be calculated for semiquantitative method performance standards specified solely in terms of the maximum allowable number of positive carriers per test. The calculations are demonstrated in a case study of the current performance standard for the semiquantitative AOAC Use-Dilution Methods for Pseudomonas aeruginosa (964.02) and Staphylococcus aureus (955.15), which allow up to one positive carrier out of a set of 60 inoculated and treated carriers in each test. A simulation study was also conducted to verify the validity of the model's assumptions and accuracy. Our approach, easily implemented using the computer code provided, offers a quantitative decision-making tool for assessing a performance standard for any disinfectant test method for which log reductions can be calculated.
Although practiced clinically for more than 40 years, the use of hematopoietic stem cell (HSC) transplants remains limited by the ability to expand these cells ex vivo. An unbiased screen with primary human HSCs identified a purine derivative, StemRegenin 1 (SR1), that promotes the ex vivo expansion of CD34+ cells. Culture of HSCs with SR1 led to a 50-fold increase in cells expressing CD34 and a 17-fold increase in cells that retain the ability to engraft immunodeficient mice. Mechanistic studies show that SR1 acts by antagonizing the aryl hydrocarbon receptor (AHR). The identification of SR1 and AHR modulation as a means to induce ex vivo HSC expansion should facilitate the clinical use of HSC therapy.
