18 research outputs found
Homework-Does It Impact Student Performance?
This study examined the impact of homework on performance in the content areas of mathematics and science. The participants were a fourth grade, inner city classroom in Rochester New York. Data was collected over two semesters. The first semester data served as a baseline for the amount of homework completed and the resulting grade for each of the 19 students. Homework strategies were implemented in the second semester to increase the amount of homework completed by the students. The amount of homework completed in both subject areas increased overall. The overall semester grades increased in mathematics more than in the area of science. Findings suggest that homework completion contributes to higher performance in academics
Impact of antibiotic timing on mortality from Gram-negative bacteraemia in an English district general hospital: the importance of getting it right every time
Objectives:
There is limited evidence that empirical antimicrobials affect patient-oriented outcomes in Gram-negative bacteraemia. We aimed to establish the impact of effective antibiotics at four consecutive timepoints on 30 day all-cause mortality and length of stay in hospital.
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Methods:
We performed a multivariable survival analysis on 789 patients with Escherichia coli, Klebsiella spp. and Pseudomonas aeruginosa bacteraemias. Antibiotic choices at the time of the blood culture (BC), the time of medical clerking and 24 and 48 h post-BC were reviewed.
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Results:
Patients that received ineffective empirical antibiotics at the time of the BC had higher risk of mortality before 30 days (HR = 1.68, 95% CI = 1.19–2.38, P = 0.004). Mortality was higher if an ineffective antimicrobial was continued by the clerking doctor (HR = 2.73, 95% CI = 1.58–4.73, P < 0.001) or at 24 h from the BC (HR = 1.83, 95% CI = 1.05–3.20, P = 0.033) when compared with patients who received effective therapy throughout. Hospital-onset infections, ‘high inoculum’ infections and elevated C-reactive protein, lactate and Charlson comorbidity index were independent predictors of mortality. Effective initial antibiotics did not statistically significantly reduce length of stay in hospital (−2.98 days, 95% CI = −6.08–0.11, P = 0.058). The primary reasons for incorrect treatment were in vitro antimicrobial resistance (48.6%), initial misdiagnosis of infection source (22.7%) and non-adherence to hospital guidelines (15.7%).
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Conclusions:
Consecutive prescribing decisions affect mortality from Gram-negative bacteraemia
Long-term outcome and risk factors for late mortality in Gram-negative bacteraemia: a retrospective cohort study
OBJECTIVES: The long-term outcomes of patients following Gram-negative bacteraemia (GNB) are poorly understood. We describe a cohort of patients with GNB over a two-year period and determine factors associated with late mortality (death between days 31 and 365 after detection of bacteraemia). METHODS: This is a single center retrospective observational cohort study of 789 patients with confirmed Escherichia coli, Klebsiella spp and Pseudomonas aeruginosa bacteraemias with a follow-up of one year. Multivariable survival analysis was used to determine the risk factors for late mortality in patients who survived the initial 30-day period of infection. RESULTS: Overall, one-year all-cause mortality was 36.2%, with 18.1% of patients dying within 30 days and 18.1% of patients suffering late mortality. An adverse antimicrobial resistance profile (HR 1.095 per any additional antimicrobial category, 95% CI 1.018 - 1.178, p = 0.014) and infection with Pseudomonas aeruginosa (HR 2.08, 95% CI 1.11 - 3.88, p = 0.022) were independent predictors of late mortality. Other significant factors included the Charlson Comorbidity Index and hospitalization length after the index blood culture. CONCLUSION: Patients with GNB have a poor long-term prognosis. Risk factors for greater mortality at one year include comorbidity, hospitalization length, the infecting organism, and its resistance profile
Antiviral resistance during pandemic influenza: implications for stockpiling and drug use
<p>Abstract</p> <p>Background</p> <p>The anticipated extent of antiviral use during an influenza pandemic can have adverse consequences for the development of drug resistance and rationing of limited stockpiles. The strategic use of drugs is therefore a major public health concern in planning for effective pandemic responses.</p> <p>Methods</p> <p>We employed a mathematical model that includes both sensitive and resistant strains of a virus with pandemic potential, and applies antiviral drugs for treatment of clinical infections. Using estimated parameters in the published literature, the model was simulated for various sizes of stockpiles to evaluate the outcome of different antiviral strategies.</p> <p>Results</p> <p>We demonstrated that the emergence of highly transmissible resistant strains has no significant impact on the use of available stockpiles if treatment is maintained at low levels or the reproduction number of the sensitive strain is sufficiently high. However, moderate to high treatment levels can result in a more rapid depletion of stockpiles, leading to run-out, by promoting wide-spread drug resistance. We applied an antiviral strategy that delays the onset of aggressive treatment for a certain amount of time after the onset of the outbreak. Our results show that if high treatment levels are enforced too early during the outbreak, a second wave of infections can potentially occur with a substantially larger magnitude. However, a timely implementation of wide-scale treatment can prevent resistance spread in the population, and minimize the final size of the pandemic.</p> <p>Conclusion</p> <p>Our results reveal that conservative treatment levels during the early stages of the outbreak, followed by a timely increase in the scale of drug-use, will offer an effective strategy to manage drug resistance in the population and avoid run-out. For a 1918-like strain, the findings suggest that pandemic plans should consider stockpiling antiviral drugs to cover at least 20% of the population.</p
Exploring the views of infection consultants in England on a novel delinked funding model for antimicrobials: the SMASH study
OBJECTIVES: A novel 'subscription-type' funding model was launched in England in July 2022 for ceftazidime/avibactam and cefiderocol. We explored the views of infection consultants on important aspects of the delinked antimicrobial funding model. METHODS: An online survey was sent to all infection consultants in NHS acute hospitals in England. RESULTS: The response rate was 31.2% (235/753). Most consultants agreed the model is a welcome development (69.8%, 164/235), will improve treatment of drug-resistant infections (68.5%, 161/235) and will stimulate research and development of new antimicrobials (57.9%, 136/235). Consultants disagreed that the model would lead to reduced carbapenem use and reported increased use of cefiderocol post-implementation. The presence of an antimicrobial pharmacy team, requirement for preauthorization by infection specialists, antimicrobial stewardship ward rounds and education of infection specialists were considered the most effective antimicrobial stewardship interventions. Under the new model, 42.1% (99/235) of consultants would use these antimicrobials empirically, if risk factors for antimicrobial resistance were present (previous infection, colonization, treatment failure with carbapenems, ward outbreak, recent admission to a high-prevalence setting).Significantly higher insurance and diversity values were given to model antimicrobials compared with established treatments for carbapenem-resistant infections, while meropenem recorded the highest enablement value. Use of both 'subscription-type' model drugs for a wide range of infection sites was reported. Respondents prioritized ceftazidime/avibactam for infections by bacteria producing OXA-48 and KPC and cefiderocol for those producing MBLs and infections with Stenotrophomonas maltophilia, Acinetobacter spp. and Burkholderia cepacia. CONCLUSIONS: The 'subscription-type' model was viewed favourably by infection consultants in England
Exploring the views of infection consultants in England on a novel delinked funding model for antimicrobials: the SMASH study
OBJECTIVES: A novel ‘subscription-type’ funding model was launched in England in July 2022 for ceftazidime/avibactam and cefiderocol. We explored the views of infection consultants on important aspects of the delinked antimicrobial funding model. METHODS: An online survey was sent to all infection consultants in NHS acute hospitals in England. RESULTS: The response rate was 31.2% (235/753). Most consultants agreed the model is a welcome development (69.8%, 164/235), will improve treatment of drug-resistant infections (68.5%, 161/235) and will stimulate research and development of new antimicrobials (57.9%, 136/235). Consultants disagreed that the model would lead to reduced carbapenem use and reported increased use of cefiderocol post-implementation. The presence of an antimicrobial pharmacy team, requirement for preauthorization by infection specialists, antimicrobial stewardship ward rounds and education of infection specialists were considered the most effective antimicrobial stewardship interventions. Under the new model, 42.1% (99/235) of consultants would use these antimicrobials empirically, if risk factors for antimicrobial resistance were present (previous infection, colonization, treatment failure with carbapenems, ward outbreak, recent admission to a high-prevalence setting).
Significantly higher insurance and diversity values were given to model antimicrobials compared with established treatments for carbapenem-resistant infections, while meropenem recorded the highest enablement value. Use of both ‘subscription-type’ model drugs for a wide range of infection sites was reported. Respondents prioritized ceftazidime/avibactam for infections by bacteria producing OXA-48 and KPC and cefiderocol for those producing MBLs and infections with Stenotrophomonas maltophilia, Acinetobacter spp. and Burkholderia cepacia. CONCLUSIONS: The ‘subscription-type’ model was viewed favourably by infection consultants in England
Post-exposure prophylaxis during pandemic outbreaks
<p>Abstract</p> <p>Background</p> <p>With the rise of the second pandemic wave of the novel influenza A (H1N1) virus in the current season in the Northern Hemisphere, pandemic plans are being carefully re-evaluated, particularly for the strategic use of antiviral drugs. The recent emergence of oseltamivir-resistant in treated H1N1 patients has raised concerns about the prudent use of neuraminidase inhibitors for both treatment of ill individuals and post-exposure prophylaxis of close contacts.</p> <p>Methods</p> <p>We extended an established population dynamical model of pandemic influenza with treatment to include post-exposure prophylaxis of close contacts. Using parameter estimates published in the literature, we simulated the model to evaluate the combined effect of treatment and prophylaxis in minimizing morbidity and mortality of pandemic infections in the context of transmissible drug resistance.</p> <p>Results</p> <p>We demonstrated that, when transmissible resistant strains are present, post-exposure prophylaxis can promote the spread of resistance, especially when combined with aggressive treatment. For a given treatment level, there is an optimal coverage of prophylaxis that minimizes the total number of infections (final size) and this coverage decreases as a higher proportion of infected individuals are treated. We found that, when treatment is maintained at intermediate levels, limited post-exposure prophylaxis provides an optimal strategy for reducing the final size of the pandemic while minimizing the total number of deaths. We tested our results by performing a sensitivity analysis over a range of key model parameters and observed that the incidence of infection depends strongly on the transmission fitness of resistant strains.</p> <p>Conclusion</p> <p>Our findings suggest that, in the presence of transmissible drug resistance, strategies that prioritize the treatment of only ill individuals, rather than the prophylaxis of those suspected of being exposed, are most effective in reducing the morbidity and mortality of the pandemic. The impact of post-exposure prophylaxis depends critically on the treatment level and the transmissibility of resistant strains and, therefore, enhanced surveillance and clinical monitoring for resistant mutants constitutes a key component of any comprehensive plan for antiviral drug use during an influenza pandemic.</p
Influenza Pandemic Waves under Various Mitigation Strategies with 2009 H1N1 as a Case Study
A significant feature of influenza pandemics is multiple waves of morbidity and mortality over a few months or years. The size of these successive waves depends on intervention strategies including antivirals and vaccination, as well as the effects of immunity gained from previous infection. However, the global vaccine manufacturing capacity is limited. Also, antiviral stockpiles are costly and thus, are limited to very few countries. The combined effect of antivirals and vaccination in successive waves of a pandemic has not been quantified. The effect of acquired immunity from vaccination and previous infection has also not been characterized. In times of a pandemic threat countries must consider the effects of a limited vaccine, limited antiviral use and the effects of prior immunity so as to adopt a pandemic strategy that will best aid the population. We developed a mathematical model describing the first and second waves of an influenza pandemic including drug therapy, vaccination and acquired immunity. The first wave model includes the use of antiviral drugs under different treatment profiles. In the second wave model the effects of antivirals, vaccination and immunity gained from the first wave are considered. The models are used to characterize the severity of infection in a population under different drug therapy and vaccination strategies, as well as school closure, so that public health policies regarding future influenza pandemics are better informed