Quantization of Midisuperspace Models

We give a comprehensive review of the quantization of midisuperspace models. Though the main focus of the paper is on quantum aspects, we also provide an introduction to several classical points related to the definition of these models. We cover some important issues, in particular, the use of the principle of symmetric criticality as a very useful tool to obtain the required Hamiltonian formulations. Two main types of reductions are discussed: those involving metrics with two Killing vector fields and spherically symmetric models. We also review the more general models obtained by coupling matter fields to these systems. Throughout the paper we give separate discussions for standard quantizations using geometrodynamical variables and those relying on loop quantum gravity inspired methods.Comment: To appear in Living Review in Relativit

Hospital-level associations with 30-day patient mortality after cardiac surgery: a tutorial on the application and interpretation of marginal and multilevel logistic regression

Background: Marginal and multilevel logistic regression methods can estimate associations between hospital-level factors and patient-level 30-day mortality outcomes after cardiac surgery. However, it is not widely understood how the interpretation of hospital-level effects differs between these methods. Methods. The Australasian Society of Cardiac and Thoracic Surgeons (ASCTS) registry provided data on 32,354 patients undergoing cardiac surgery in 18 hospitals from 2001 to 2009. The logistic regression methods related 30-day mortality after surgery to hospital characteristics with concurrent adjustment for patient characteristics. Results: Hospital-level mortality rates varied from 1.0% to 4.1% of patients. Ordinary, marginal and multilevel regression methods differed with regard to point estimates and conclusions on statistical significance for hospital-level risk factors; ordinary logistic regression giving inappropriately narrow confidence intervals. The median odds ratio, MOR, from the multilevel model was 1.2 whereas ORs for most patient-level characteristics were of greater magnitude suggesting that unexplained between-hospital variation was not as relevant as patient-level characteristics for understanding mortality rates. For hospital-level characteristics in the multilevel model, 80% interval ORs, IOR-80%, supplemented the usual ORs from the logistic regression. The IOR-80% was (0.8 to 1.8) for academic affiliation and (0.6 to 1.3) for the median annual number of cardiac surgery procedures. The width of these intervals reflected the unexplained variation between hospitals in mortality rates; the inclusion of one in each interval suggested an inability to add meaningfully to explaining variation in mortality rates. Conclusions: Marginal and multilevel models take different approaches to account for correlation between patients within hospitals and they lead to different interpretations for hospital-level odds ratios. © 2012 Sanagou et al; licensee BioMed Central Ltd

Empathy among undergraduate medical students: A multi-centre cross-sectional comparison of students beginning and approaching the end of their course

BACKGROUND: Although a core element in patient care the trajectory of empathy during undergraduate medical education remains unclear. Empathy is generally regarded as comprising an affective capacity: the ability to be sensitive to and concerned for, another and a cognitive capacity: the ability to understand and appreciate the other person's perspective. The authors investigated whether final year undergraduate students recorded lower levels of empathy than their first year counterparts, and whether male and female students differed in this respect. METHODS: Between September 2013 and June 2014 an online questionnaire survey was administered to 15 UK, and 2 international medical schools. Participating schools provided both 5-6 year standard courses and 4 year accelerated graduate entry courses. The survey incorporated the Jefferson Scale of Empathy-Student Version (JSE-S) and Davis's Interpersonal Reactivity Index (IRI), both widely used to measure medical student empathy. Participation was voluntary. Chi squared tests were used to test for differences in biographical characteristics of student groups. Multiple linear regression analyses, in which predictor variables were year of course (first/final); sex; type of course and broad socio-economic group were used to compare empathy scores. RESULTS: Five medical schools (4 in the UK, 1 in New Zealand) achieved average response rates of 55 % (n = 652) among students starting their course and 48 % (n = 487) among final year students. These schools formed the High Response Rate Group. The remaining 12 medical schools recorded lower response rates of 24.0 % and 15.2 % among first and final year students respectively. These schools formed the Lower Response Rate Group. For both male and female students in both groups of schools no significant differences in any empathy scores were found between students starting and approaching the end of their course. Gender was found to significantly predict empathy scores, with females scoring higher than males. CONCLUSIONS: Participant male and female medical students approaching the end of their undergraduate education, did not record lower levels of empathy, compared to those at the beginning of their course. Questions remain concerning the trajectory of empathy after qualification and how best to support it through the pressures of starting out in medical practice

Does the early frog catch the worm? Disentangling potential drivers of a parasite age–intensity relationship in tadpoles

The manner in which parasite intensity and aggregation varies with host age can provide insights into parasite dynamics and help identify potential means of controlling infections in humans and wildlife. A significant challenge is to distinguish among competing mechanistic hypotheses for the relationship between age and parasite intensity or aggregation. Because different mechanisms can generate similar relationships, testing among competing hypotheses can be difficult, particularly in wildlife hosts, and often requires a combination of experimental and model fitting approaches. We used field data, experiments, and model fitting to distinguish among ten plausible drivers of a curvilinear age–intensity relationship and increasing aggregation with host age for echinostome trematode infections of green frogs. We found little support for most of these proposed drivers but did find that the parsimonious explanation for the observed age–intensity relationship was seasonal exposure to echinostomes. The parsimonious explanation for the aggregated distribution of parasites in this host population was heterogeneity in exposure. A predictive model incorporating seasonal exposure indicated that tadpoles hatching early or late in the breeding season should have lower trematode burdens at metamorphosis, particularly with simulated warmer climates. Application of this multi-pronged approach (field surveys, lab experiments, and modeling) to additional parasite–host systems could lead to discovery of general patterns in the drivers of parasite age–intensity and age–distribution relationships