246 research outputs found
A quantitative analysis of the prevalence of clinical depression and anxiety in patients with prostate cancer undergoing active surveillance
No full textObjective: To quantitatively determine the prevalence of anxiety and depression in men on active surveillance (AS).Design: Cross-sectional questionnaire survey.Setting: Secondary care prostate cancer (PCa) clinics across South, Central and Western England.Participants: 313 men from a total sample of 426 with a histological diagnosis of PCa currently managed with AS were identified from seven UK urology departments. The mean age of respondents was 70 (51–86) years with the majority (76%) being married or in civil partnerships. 94% of responders were of white British ethnicity.Primary outcome measures: The prevalence of clinically meaningful depression and anxiety as assessed by the Hospital Anxiety and Depression Scale (HADS; score ?8/21).Secondary outcome measures: Patient demographic data (age, employment, relationship, ethnic and educational status). Each demographic variable was cross-tabulated against patients identified as depressed or anxious to allow for the identification of variables that were significantly associated with depression and anxiety. In order to determine predictors for depression and anxiety among the demographic variables, logistic regression analyses were conducted, with p<0.05 considered as indicating statistical significance.Results: The prevalence of clinical anxiety and depression as determined via the HADS (HADS ?8) was 23% (n=73) and 12.5% (n=39), respectively. Published data from men in the general population of similar age has shown prevalence rates of 8% and 6%, respectively, indicating a twofold increase in depression and a threefold increase in anxiety among AS patients. Our findings also suggest that AS patients experience substantially greater levels of anxiety than patients with PCa treated radically. The only demographic predictor for anxiety or depression was divorce.Conclusions: Patients with PCa managed with AS experienced substantially higher rates of anxiety and depression than that expected in the general population. Strategies to address this are needed to improve the management of this population and their quality of life.<br/
Accuracy, Estimates, and Representation Results
No full textMeasures of accuracy usually score how accurate a specified credence depending on whether the proposition is true or false. A key requirement for such measures is strict propriety; that probabilities expect themselves to be most accurate. We discuss characterisation results for strictly proper measures of accuracy.
By making some restrictive assumptions, we present the proof of the characterisation result of Schervish (1989) in an accessible way. We will also present the characterisation in terms of Bregman divergences and the relationship between the two characterisations.
The new contribution of the paper is to show that the Schervish form characterises proper measures of accuracy for estimates of random variables more generally, by offering a converse to Schervish, Seidenfeld, and Kadane (2014, Lemma 1). We also provide a Bregman divergence characterisation in the estimates setting, using the close relationship between the two forms
Results about sets of desirable gamble sets
No full textCoherent sets of desirable gamble sets is used as a model for representing an
agents opinions and choice preferences under uncertainty. In this paper we
provide some results about the axioms required for coherence and the natural
extension of a given set of desirable gamble sets. We also show that coherent
sets of desirable gamble sets can be represented by a proper filter of coherent
sets of desirable gambles
Antimicrobial susceptibility of uropathogens isolated from Cambodian children
No full textWe thank Anirban Mandal and Puneet Kaur Sahi for their comments on our study and welcome the opportunity to respond
Knocking Out Antimicrobial Resistance editorial: reflections on the United Nations General Assembly high-level meeting on antimicrobial resistance
No full text
Arctic synoptic activity associated with sea ice variability using self-organizing maps
No full textRelationships between synoptic activity and sea ice variability in the Arctic are studied using self-organizing maps (SOMs) to categorize observed weather patterns over the 1979-2010 period. The European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-interim, or ERAI) provides the daily sea level pressures from which the SOMs are computed. Time series of frequencies and durations of synoptic weather patterns are correlated with two sea ice metrics, Fram Strait ice outflow and year-to-year changes in September pan-Arctic sea ice extent. When compared to teleconnection indices commonly associated with sea ice variability, the Arctic Oscillation (AO), North Atlantic Oscillation (NAO), and Arctic Dipole (AD), some SOM patterns correlate more strongly with sea ice metrics. For example, Beaufort High synoptic patterns are increasing in frequency in spring and summer and their spring frequencies are associated with ice loss. Icelandic Low patterns show opposing influences on sea ice from wind-forcing and thermal advection. The phase lags between the SOM occurrences and sea ice variability offer the potential for augmentation of other approaches to seasonal sea ice prediction. The ERA-interim SOM analysis is used to quantify how the Community Climate System Model, Version 4 (CCSM4) captures synoptic activity in the twentieth and twenty-first centuries. The model undersimulates patterns important for ice loss, such as broad high pressures over the continents and ice cover, and simulates strong storm track features at a higher-than-observed frequency. Large-scale teleconnection patterns, such as the AO and AD, are reasonably captured but there are spatial shifts in centers of action (which are associated with ice motion biases) and enhanced interannual variability relative to the observations. Relationships between synoptic activity and year-to-year changes in sea ice extent are not as prominent in the 20th century model experiment and further weaken in the 21st century. Accounting for seasonal SLP biases in the model enhances SOM frequency-ice correlations, suggesting that the model captures closer-to-observed atmosphere-ice linkages when SLPs are reasonably simulated. Strong low pressures over the Arctic predominate over the ice-free central Arctic during summer and fall in the 21st century.Item withdrawn by Mark Zulauf ([email protected]) on 2014-04-24T13:49:43Z
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Variation in excess all-cause mortality by age, sex, and province during the first wave of the COVID-19 pandemic in Italy
No full textAlthough previous evidence suggests that the infection fatality rate from COVID-19 varies by age and sex, and that transmission intensity varies geographically within countries, no study has yet explored the age-sex-space distribution of excess mortality associated with the COVID pandemic. By applying the principles of small-area estimation to existing model formulations for excess mortality, this study develops a novel method for assessing excess mortality across small populations and assesses the pattern of COVID excess mortality by province, year, week, age group, and sex in Italy from March through May 2020. We estimate that 53,200 excess deaths occurred across Italy during this time period, compared to just 35,500 deaths where COVID-19 was registered as the underlying cause of death. Out of the total excess mortality burden, 97% of excess deaths occurred among adults over age 60, and 68% of excess deaths were concentrated among adults over age 80. The burden of excess mortality was unevenly distributed across the country, with just three of Italy’s 107 provinces accounting for 32% of all excess mortality. This method for estimating excess mortality can be adapted to other countries where COVID-19 diagnostic capacity is still insufficient, and could be incorporated into public health rapid response systems
Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis
No full textBackground
Antimicrobial resistance (AMR) poses a major threat to human health around the world. Previous publications have estimated the effect of AMR on incidence, deaths, hospital length of stay, and health-care costs for specific pathogen–drug combinations in select locations. To our knowledge, this study presents the most comprehensive estimates of AMR burden to date.
Methods
We estimated deaths and disability-adjusted life-years (DALYs) attributable to and associated with bacterial AMR for 23 pathogens and 88 pathogen–drug combinations in 204 countries and territories in 2019. We obtained data from systematic literature reviews, hospital systems, surveillance systems, and other sources, covering 471 million individual records or isolates and 7585 study-location-years. We used predictive statistical modelling to produce estimates of AMR burden for all locations, including for locations with no data. Our approach can be divided into five broad components: number of deaths where infection played a role, proportion of infectious deaths attributable to a given infectious syndrome, proportion of infectious syndrome deaths attributable to a given pathogen, the percentage of a given pathogen resistant to an antibiotic of interest, and the excess risk of death or duration of an infection associated with this resistance. Using these components, we estimated disease burden based on two counterfactuals: deaths attributable to AMR (based on an alternative scenario in which all drug-resistant infections were replaced by drug-susceptible infections), and deaths associated with AMR (based on an alternative scenario in which all drug-resistant infections were replaced by no infection). We generated 95% uncertainty intervals (UIs) for final estimates as the 25th and 975th ordered values across 1000 posterior draws, and models were cross-validated for out-of-sample predictive validity. We present final estimates aggregated to the global and regional level.
Findings
On the basis of our predictive statistical models, there were an estimated 4·95 million (3·62–6·57) deaths associated with bacterial AMR in 2019, including 1·27 million (95% UI 0·911–1·71) deaths attributable to bacterial AMR. At the regional level, we estimated the all-age death rate attributable to resistance to be highest in western sub-Saharan Africa, at 27·3 deaths per 100 000 (20·9–35·3), and lowest in Australasia, at 6·5 deaths (4·3–9·4) per 100 000. Lower respiratory infections accounted for more than 1·5 million deaths associated with resistance in 2019, making it the most burdensome infectious syndrome. The six leading pathogens for deaths associated with resistance (Escherichia coli, followed by Staphylococcus aureus, Klebsiella pneumoniae, Streptococcus pneumoniae, Acinetobacter baumannii, and Pseudomonas aeruginosa) were responsible for 929 000 (660 000–1 270 000) deaths attributable to AMR and 3·57 million (2·62–4·78) deaths associated with AMR in 2019. One pathogen–drug combination, meticillin-resistant S aureus, caused more than 100 000 deaths attributable to AMR in 2019, while six more each caused 50 000–100 000 deaths: multidrug-resistant excluding extensively drug-resistant tuberculosis, third-generation cephalosporin-resistant E coli, carbapenem-resistant A baumannii, fluoroquinolone-resistant E coli, carbapenem-resistant K pneumoniae, and third-generation cephalosporin-resistant K pneumoniae.
Interpretation
To our knowledge, this study provides the first comprehensive assessment of the global burden of AMR, as well as an evaluation of the availability of data. AMR is a leading cause of death around the world, with the highest burdens in low-resource settings. Understanding the burden of AMR and the leading pathogen–drug combinations contributing to it is crucial to making informed and location-specific policy decisions, particularly about infection prevention and control programmes, access to essential antibiotics, and research and development of new vaccines and antibiotics. There are serious data gaps in many low-income settings, emphasising the need to expand microbiology laboratory capacity and data collection systems to improve our understanding of this important human health threat.
Funding
Bill & Melinda Gates Foundation, Wellcome Trust, and Department of Health and Social Care using UK aid funding managed by the Fleming Fund
The Trenton Afterschool Partnership: Expanding Learning Time Citywide Through Public/Private Collaboration
No full text· High quality after-school programs have been demonstrated to have significant impact on student performance.
· Preceding the Trenton Afterschool Partnership (TAP) was a hodgepodge of programs that cost various contributors about $9 million. These programs, of unequal quality, served about 1,500 students in 15 out of Trenton’s 21 public schools.
· TAP (which includes the Princeton Area Community Foundation) was able to successfully implement programs in all of the Trenton schools.
· Budget cuts have forced the reduction of the programs, but about half of the schools have been able to maintain programs.
· Foundations are encouraged to support advocacy capacity and to provide general operating support to community based organizations that have an established record of successful service delivery and strong partnerships
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