Pediatric Nurses\u27 Perspectives on Medication Teaching in a Children\u27s Hospital

Purpose To explore inpatient pediatric nurses\u27 current experiences and perspectives on medication teaching. Design and Methods A descriptive qualitative study was conducted at a Midwest pediatric hospital. Using convenience sampling, 26 nurses participated in six focus groups. Data were analyzed in an iterative group coding process. Results Three themes emerged. 1) Medication teaching is an opportunity. 2) Medication teaching is challenging. Nurses experienced structural and process challenges to deliver medication teaching. Structural challenges included the physical hospital environment, electronic health record, and institutional discharge workflow while process challenges included knowledge, relationships and interactions with caregivers, and available resources. 3) Medication teaching is amenable to improvement. Conclusion Effective medication teaching with caregivers is critical to ensure safe, quality care for children after discharge. Nursing teaching practices have not changed, despite advances in technology and major changes in hospital care. Nurses face many challenges to conduct effective medication teaching. Improving current teaching practices is imperative in order to provide the best and safest care. Practice Implications This study generated knowledge regarding pediatric nurses\u27 teaching practices, values and beliefs that influence teaching, barriers, and ideas for how to improve medication teaching. Results will guide the development of targeted interventions to promote successful medication teaching practices

Impact and Cost-Effectiveness of Point-Of-Care CD4 Testing on the HIV Epidemic in South Africa.

Rapid diagnostic tools have been shown to improve linkage of patients to care. In the context of infectious diseases, assessing the impact and cost-effectiveness of such tools at the population level, accounting for both direct and indirect effects, is key to informing adoption of these tools. Point-of-care (POC) CD4 testing has been shown to be highly effective in increasing the proportion of HIV positive patients who initiate ART. We assess the impact and cost-effectiveness of introducing POC CD4 testing at the population level in South Africa in a range of care contexts, using a dynamic compartmental model of HIV transmission, calibrated to the South African HIV epidemic. We performed a meta-analysis to quantify the differences between POC and laboratory CD4 testing on the proportion linking to care following CD4 testing. Cumulative infections averted and incremental cost-effectiveness ratios (ICERs) were estimated over one and three years. We estimated that POC CD4 testing introduced in the current South African care context can prevent 1.7% (95% CI: 0.4% - 4.3%) of new HIV infections over 1 year. In that context, POC CD4 testing was cost-effective 99.8% of the time after 1 year with a median estimated ICER of US$4,468/DALY averted. In healthcare contexts with expanded HIV testing and improved retention in care, POC CD4 testing only became cost-effective after 3 years. The results were similar when, in addition, ART was offered irrespective of CD4 count, and CD4 testing was used for clinical assessment. Our findings suggest that even if ART is expanded to all HIV positive individuals and HIV testing efforts are increased in the near future, POC CD4 testing is a cost-effective tool, even within a short time horizon. Our study also illustrates the importance of evaluating the potential impact of such diagnostic technologies at the population level, so that indirect benefits and costs can be incorporated into estimations of cost-effectiveness

On the orbits of the product of two permutations

AbstractWe consider the following problem: given three partitions A,B,C of a finite set Ω, do there exist two permutations α and β such that A,B,C are induced by α, β and αβ respectively? This problem is NP-complete. However it turns out that it can be solved by a polynomial time algorithm when some relations between the number of classes of A,B,C hold

How Can Viral Dynamics Models Inform Endpoint Measures in Clinical Trials of Therapies for Acute Viral Infections?

Acute viral infections pose many practical challenges for the accurate assessment of the impact of novel therapies on viral growth and decay. Using the example of influenza A, we illustrate how the measurement of infection-related quantities that determine the dynamics of viral load within the human host, can inform investigators on the course and severity of infection and the efficacy of a novel treatment. We estimated the values of key infection-related quantities that determine the course of natural infection from viral load data, using Markov Chain Monte Carlo methods. The data were placebo group viral load measurements collected during volunteer challenge studies, conducted by Roche, as part of the oseltamivir trials. We calculated the values of the quantities for each patient and the correlations between the quantities, symptom severity and body temperature. The greatest variation among individuals occurred in the viral load peak and area under the viral load curve. Total symptom severity correlated positively with the basic reproductive number. The most sensitive endpoint for therapeutic trials with the goal to cure patients is the duration of infection. We suggest laboratory experiments to obtain more precise estimates of virological quantities that can supplement clinical endpoint measurements

Big brother is watching - using digital disease surveillance tools for near real-time forecasting

Abstract for the International Journal of Infectious Diseases 79 (S1) (2019).https://www.ijidonline.com/article/S1201-9712(18)34659-9/abstractPublished versio

Acute pulmonary embolism in a child with ANCA-negative Idiopathic Pulmonary Capillaritis

Diffuse alveolar hemorrhage is an uncommon and often fatal condition in children that is characterized by distinct histopathological etiologies. Herein, we discuss the case of an 11-year-old girl who presented with acute worsening of hypoxia and left-sided chest pain. The patient had lung biopsy-proven idiopathic pulmonary capillaritis and was being treated with prednisolone every alternate day, azathioprine, and hydroxychloroquine. A contrast-computed tomography (CT) scan of the chest showed an acute left lower-lobe pulmonary embolism. Negative results were obtained on a test for thrombophilia. In children, pulmonary embolism with anti-neutrophil cytoplasmic antibody-negative idiopathic pulmonary capillaritis is a rare clinical condition. The exact cause of thrombus formation in this case is unknown; however, obesity, immobility, and chronic systemic corticosteroid therapy probably played a role.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Report 49: Growth, population distribution and immune escape of Omicron in England

To estimate the growth of the Omicron variant of concern (1) and its immune escape (2–9) characteristics, we analysed data from all PCR-confirmed SARS-CoV-2 cases in England excluding those with a history of recent international travel. We undertook separate analyses according to two case definitions. For the first definition, we included all cases with a definitive negative S-gene Target Failure (SGTF) result and specimen dates between 29/11/2021 and 11/12/2021 inclusive. For the second definition, we included cases with a positive genotype result and specimen date between 23/11/2021 and 11/12/2021 inclusive. We chose a later start date for the SGTF definition to ensure greater specificity of SGTF for Omicron. We used logistic and Poisson regression to identify factors associated with testing positive for Omicron compared to non-Omicron (mostly Delta) cases. We explored the following predictors: day, region, symptomatic status, sex, ethnicity, age band and vaccination status. Our results suggest rapid growth of the frequency of the Omicron variant relative to Delta, with the exponential growth rate of its frequency estimated to be 0.34/day (95% CI: 0.33-0.35) [2.0 day doubling time] over the study period from both SGTF and genotype data. The distribution of Omicron by age, region and ethnicity currently differs markedly from Delta, with 18–29-year-olds, residents in the London region, and those of African ethnicity having significantly higher rates of infection with Omicron relative to Delta. Hospitalisation and asymptomatic infection indicators were not significantly associated with Omicron infection, suggesting at most limited changes in severity compared with Delta. To estimate the impact of Omicron on vaccine effectiveness (VE) for symptomatic infection we used conditional Poisson regression to estimate the hazard ratio of being an Omicron case (using SGTF definition) compared with Delta, restricting our analysis to symptomatic cases and matching by day, region, 10-year age band, sex and ethnicity. We found a significant increased risk of an Omicron case compared to Delta for those with vaccine status AZ 2+weeks post-dose 2 (PD2) , Pfizer 2+w PD2, AZ 2+w post-dose 3 (PD3) and PF 2+w PD3 vaccine states with hazard ratios of 1.86 (95%CI: 1.67-2.08), 2.68 (95%CI: 2.54-2.83), 4.32 (95%CI: 3.84-4.85) and 4.07 (95%CI: 3.66-4.51), respectively, where PD3 states are categorised by the dose 1/2 vaccine used. Depending on the Delta VE estimates used (10), these estimates translate into Omicron VE estimates of between 0% and 20% PD2 and between 55% and 80% PD3 against Omicron, consistent with other estimates (11). Similar estimates were obtained using genotype data, albeit with greater uncertainty. To assess the impact of Omicron on reinfection rates we relied on genotype data, since SGTF is associated with a higher observed rate of reinfection, likely due to reinfections typically having higher Ct values than primary infections and therefore being subject to a higher rate of random PCR target failure. Controlling for vaccine status, age, sex, ethnicity, asymptomatic status, region and specimen date and using conditional Poisson regression to predict reinfection status, Omicron was associated with a 5.41 (95% CI: 4.87-6.00) fold higher risk of reinfection compared with Delta. This suggests relatively low remaining levels of immunity from prior infection

Temporal variability and social heterogeneity in disease transmission: The case of SARS in Hong Kong

The extent to which self-adopted or intervention-related changes in behaviors affect the course of epidemics remains a key issue for outbreak control. This study attempted to quantify the effect of such changes on the risk of infection in different settings, i.e., the community and hospitals. The 2002-2003 severe acute respiratory syndrome (SARS) outbreak in Hong Kong, where 27% of cases were healthcare workers, was used as an example. A stochastic compartmental SEIR (susceptible-exposed-infectious-removed) model was used: the population was split into healthcare workers, hospitalized people and general population. Super spreading events (SSEs) were taken into account in the model. The temporal evolutions of the daily effective contact rates in the community and hospitals were modeled with smooth functions. Data augmentation techniques and Markov chain Monte Carlo (MCMC) methods were applied to estimate SARS epidemiological parameters. In particular, estimates of daily reproduction numbers were provided for each subpopulation. The average duration of the SARS infectious period was estimated to be 9.3 days (±0.3 days). The model was able to disentangle the impact of the two SSEs from background transmission rates. The effective contact rates, which were estimated on a daily basis, decreased with time, reaching zero inside hospitals. This observation suggests that public health measures and possible changes in individual behaviors effectively reduced transmission, especially in hospitals. The temporal patterns of reproduction numbers were similar for healthcare workers and the general population, indicating that on average, an infectious healthcare worker did not infect more people than any other infectious person. We provide a general method to estimate time dependence of parameters in structured epidemic models, which enables investigation of the impact of control measures and behavioral changes in different settings. © 2009 Cori et al.published_or_final_versio