Retirement Behavior and the Global Financial Crisis

Recent economic conditions have vastly changed the retirement landscape. Declines in assets as well as high unemployment changed the retirement plans of many Americans. Shocks to employment and wealth have likely influenced retirement behavior. This chapter provides a survey of the current literature on the influence of employment and wealth shocks on retirement and then makes use of administrative records on benefit applications to provide a preliminary analysis of changes in early retirement (age 62) claiming resulting from the recent economic downturn and implications. Since early claiming can have long lasting implications for retirement well being, we address how Americans learn about their retirement options

Prospective cohort study of procalcitonin levels in children with cancer presenting with febrile neutropenia

BACKGROUND: Febrile neutropenia (FNP) causes significant morbidity and mortality in children undergoing treatment for cancer. The development of clinical decision rules to help stratify risks in paediatric FNP patients and the use of inflammatory biomarkers to identify high risk patients is an area of recent research. This study aimed to assess if procalcitonin (PCT) levels could be used to help diagnose or exclude severe infection in children with cancer who present with febrile neutropenia, both as a single measurement and in addition to previously developed clinical decision rules. METHODS: This prospective cohort study of a diagnostic test included patients between birth and 18 years old admitted with febrile neutropenia to the Paediatric Oncology and Haematology Ward in Leeds between 1(st) October 2012 and 30(th) September 2013. Each admission with FNP was treated as a separate episode. Blood was taken for a procalcitonin level at admission with routine investigations. 'R' was used for statistical analysis. Likelihood ratios were calculated and multivariable logistic regression. RESULTS: Forty-eight episodes from 27 patients were included. PCT >2 ng/dL was strongly associated with increased risk of severe infection (likelihood ratio of 26 [95% CI 3.5, 190]). The data suggests that the clinical decision rules are largely ineffective at risk stratification, frequently over-stating the risk of individual episodes. High procalcitonin levels on admission are correlated with a greatly increased risk of severe infection. CONCLUSIONS: This study does not show a definitive benefit in using PCT in FNP though it supports further research on its use. The benefit of novel biomarkers has not been proven and before introducing new tests for patients it is important their benefit above existing features is proven, particularly due to the increasing importance of health economics

Superimposition of 3D cone-beam CT models of orthognathic surgery patients

To evaluate the registration of 3D models from cone-beam CT (CBCT) images taken before and after orthognathic surgery for the assessment of mandibular anatomy and position

The Views of Mental Health Manager Towards the Use of a Family Work Model for Psychosis in Guangzhou, China

Family Interventions in Psychosis (FIP) have been promoted internationally but have been criticised for being based on western cultural models. This paper reports on a focus group study with 10 Integrated Mental Health Service Managers in Guangzhou, China using thematic analysis. Managers believed FIP might benefit families but identified potential difficulties due to (a) families avoiding services due to the ‘shame’ of mental illness (b) unrealistic expectations of services amongst families (c) deferral to ‘key decision-makers’ within families when discussing family issues with workers. The findings indicate that FIP work should focus on interaction between carers in the first instance with service users being introduced into sessions at a later date and that more attention needs to be given by the research community to how FIP may be adapted to cultural norms within China

Predicting microbiologically defined infection in febrile neutropenic episodes in children : global individual participant data multivariable meta-analysis

BACKGROUND: Risk-stratified management of fever with neutropenia (FN), allows intensive management of high-risk cases and early discharge of low-risk cases. No single, internationally validated, prediction model of the risk of adverse outcomes exists for children and young people. An individual patient data (IPD) meta-analysis was undertaken to devise one. METHODS: The 'Predicting Infectious Complications in Children with Cancer' (PICNICC) collaboration was formed by parent representatives, international clinical and methodological experts. Univariable and multivariable analyses, using random effects logistic regression, were undertaken to derive and internally validate a risk-prediction model for outcomes of episodes of FN based on clinical and laboratory data at presentation. RESULTS: Data came from 22 different study groups from 15 countries, of 5127 episodes of FN in 3504 patients. There were 1070 episodes in 616 patients from seven studies available for multivariable analysis. Univariable analyses showed associations with microbiologically defined infection (MDI) in many items, including higher temperature, lower white cell counts and acute myeloid leukaemia, but not age. Patients with osteosarcoma/Ewings sarcoma and those with more severe mucositis were associated with a decreased risk of MDI. The predictive model included: malignancy type, temperature, clinically 'severely unwell', haemoglobin, white cell count and absolute monocyte count. It showed moderate discrimination (AUROC 0.723, 95% confidence interval 0.711-0.759) and good calibration (calibration slope 0.95). The model was robust to bootstrap and cross-validation sensitivity analyses. CONCLUSIONS: This new prediction model for risk of MDI appears accurate. It requires prospective studies assessing implementation to assist clinicians and parents/patients in individualised decision making

One Problem, Many Solutions: Simple Statistical Approaches Help Unravel the Complexity of the Immune System in an Ecological Context

The immune system is a complex collection of interrelated and overlapping solutions to the problem of disease. To deal with this complexity, researchers have devised multiple ways to measure immune function and to analyze the resulting data. In this way both organisms and researchers employ many tactics to solve a complex problem. One challenge facing ecological immunologists is the question of how these many dimensions of immune function can be synthesized to facilitate meaningful interpretations and conclusions. We tackle this challenge by employing and comparing several statistical methods, which we used to test assumptions about how multiple aspects of immune function are related at different organizational levels. We analyzed three distinct datasets that characterized 1) species, 2) subspecies, and 3) among- and within-individual level differences in the relationships among multiple immune indices. Specifically, we used common principal components analysis (CPCA) and two simpler approaches, pair-wise correlations and correlation circles. We also provide a simple example of how these techniques could be used to analyze data from multiple studies. Our findings lead to several general conclusions. First, relationships among indices of immune function may be consistent among some organizational groups (e.g. months over the annual cycle) but not others (e.g. species); therefore any assumption of consistency requires testing before further analyses. Second, simple statistical techniques used in conjunction with more complex multivariate methods give a clearer and more robust picture of immune function than using complex statistics alone. Moreover, these simpler approaches have potential for analyzing comparable data from multiple studies, especially as the field of ecological immunology moves towards greater methodological standardization

Updated Systematic Review and Meta-Analysis of the Performance of Risk Prediction Rules in Children and Young People with Febrile Neutropenia

Introduction: Febrile neutropenia is a common and potentially life-threatening complication of treatment for childhood cancer, which has increasingly been subject to targeted treatment based on clinical risk stratification. Our previous meta-analysis demonstrated 16 rules had been described and 2 of them subject to validation in more than one study. We aimed to advance our knowledge of evidence on the discriminatory ability and predictive accuracy of such risk stratification clinical decision rules (CDR) for children and young people with cancer by updating our systematic review. Methods: The review was conducted in accordance with Centre for Reviews and Dissemination methods, searching multiple electronic databases, using two independent reviewers, formal critical appraisal with QUADAS and meta-analysis with random effects models where appropriate. It was registered with PROSPERO: CRD42011001685. Results: We found 9 new publications describing a further 7 new CDR, and validations of 7 rules. Six CDR have now been subject to testing across more than two data sets. Most validations demonstrated the rule to be less efficient than when initially proposed; geographical differences appeared to be one explanation for this. Conclusion: The use of clinical decision rules will require local validation before widespread use. Considerable uncertainty remains over the most effective rule to use in each population, and an ongoing individual-patient-data meta-analysis should develop and test a more reliable CDR to improve stratification and optimise therapy. Despite current challenges, we believe it will be possible to define an internationally effective CDR to harmonise the treatment of children with febrile neutropenia

A Minimal Model of Metabolism Based Chemotaxis

Since the pioneering work by Julius Adler in the 1960's, bacterial chemotaxis has been predominantly studied as metabolism-independent. All available simulation models of bacterial chemotaxis endorse this assumption. Recent studies have shown, however, that many metabolism-dependent chemotactic patterns occur in bacteria. We hereby present the simplest artificial protocell model capable of performing metabolism-based chemotaxis. The model serves as a proof of concept to show how even the simplest metabolism can sustain chemotactic patterns of varying sophistication. It also reproduces a set of phenomena that have recently attracted attention on bacterial chemotaxis and provides insights about alternative mechanisms that could instantiate them. We conclude that relaxing the metabolism-independent assumption provides important theoretical advances, forces us to rethink some established pre-conceptions and may help us better understand unexplored and poorly understood aspects of bacterial chemotaxis

Pretest expectations strongly influence interpretation of abnormal laboratory results and further management

Contains fulltext : 89631.pdf (publisher's version ) (Open Access)BACKGROUND: Abnormal results of diagnostic laboratory tests can be difficult to interpret when disease probability is very low. Although most physicians generally do not use Bayesian calculations to interpret abnormal results, their estimates of pretest disease probability and reasons for ordering diagnostic tests may--in a more implicit manner--influence test interpretation and further management. A better understanding of this influence may help to improve test interpretation and management. Therefore, the objective of this study was to examine the influence of physicians' pretest disease probability estimates, and their reasons for ordering diagnostic tests, on test result interpretation, posttest probability estimates and further management. METHODS: Prospective study among 87 primary care physicians in the Netherlands who each ordered laboratory tests for 25 patients. They recorded their reasons for ordering the tests (to exclude or confirm disease or to reassure patients) and their pretest disease probability estimates. Upon receiving the results they recorded how they interpreted the tests, their posttest probability estimates and further management. Logistic regression was used to analyse whether the pretest probability and the reasons for ordering tests influenced the interpretation, the posttest probability estimates and the decisions on further management. RESULTS: The physicians ordered tests for diagnostic purposes for 1253 patients; 742 patients had an abnormal result (64%). Physicians' pretest probability estimates and their reasons for ordering diagnostic tests influenced test interpretation, posttest probability estimates and further management. Abnormal results of tests ordered for reasons of reassurance were significantly more likely to be interpreted as normal (65.8%) compared to tests ordered to confirm a diagnosis or exclude a disease (27.7% and 50.9%, respectively). The odds for abnormal results to be interpreted as normal were much lower when the physician estimated a high pretest disease probability, compared to a low pretest probability estimate (OR = 0.18, 95% CI = 0.07-0.52, p < 0.001). CONCLUSIONS: Interpretation and management of abnormal test results were strongly influenced by physicians' estimation of pretest disease probability and by the reason for ordering the test. By relating abnormal laboratory results to their pretest expectations, physicians may seek a balance between over- and under-reacting to laboratory test results