Traumatic brain injury: Age at injury influences dementia risk after TBI

Traumatic brain injury (TBI) is increasingly recognized as a risk factor for dementia. New data provide further support for this association and demonstrate the influence of age at injury and injury severity on dementia risk after TBI, revealing that even mild TBI increases dementia risk in those aged ≥65 years

‘Concussion’ is not a true diagnosis

In current usage, ‘concussion’ describes a clinical presentation, but does not identify the underlying pathological process and therefore cannot be considered a true diagnosis. However, mounting evidence indicates diffuse axonal injury as a likely pathological substrate for concussion, thereby providing a framework to develop true diagnostic criteria

An Analysis of Preliminary and Post-Discussion Priority Scores for Grant Applications Peer Reviewed by the Center for Scientific Review at the NIH

There has been the impression amongst many observers that discussion of a grant application has little practical impact on the final priority scores. Rather the final score is largely dictated by the range of preliminary scores given by the assigned reviewers. The implication is that the preliminary and final scores are the same and the discussion has little impact. The purpose of this examination of the peer review process at the National Institutes of Health is to describe the relationship between preliminary priority scores of the assigned reviewers and the final priority score given by the scientific review group. This study also describes the practical importance of any differences in priority scores. Priority scores for a sample of standard (R01) research grant applications were used in this assessment. The results indicate that the preliminary meeting evaluation is positively correlated with the final meeting outcome but that they are on average significantly different. The results demonstrate that discussion at the meeting has an important practical impact on over 13% of the applications

Bayesian inference for an illness-death model for stroke with cognition as a latent time-dependent risk factor.

Longitudinal data can be used to estimate the transition intensities between healthy and unhealthy states prior to death. An illness-death model for history of stroke is presented, where time-dependent transition intensities are regressed on a latent variable representing cognitive function. The change of this function over time is described by a linear growth model with random effects. Occasion-specific cognitive function is measured by an item response model for longitudinal scores on the Mini-Mental State Examination, a questionnaire used to screen for cognitive impairment. The illness-death model will be used to identify and to explore the relationship between occasion-specific cognitive function and stroke. Combining a multi-state model with the latent growth model defines a joint model which extends current statistical inference regarding disease progression and cognitive function. Markov chain Monte Carlo methods are used for Bayesian inference. Data stem from the Medical Research Council Cognitive Function and Ageing Study in the UK (1991-2005)

A New Calibrated Bayesian Internal Goodness-of-Fit Method: Sampled Posterior p-Values as Simple and General p-Values That Allow Double Use of the Data

Background: Recent approaches mixing frequentist principles with Bayesian inference propose internal goodness-of-fit (GOF) p-values that might be valuable for critical analysis of Bayesian statistical models. However, GOF p-values developed to date only have known probability distributions under restrictive conditions. As a result, no known GOF p-value has a known probability distribution for any discrepancy function. Methodology/Principal Findings: We show mathematically that a new GOF p-value, called the sampled posterior p-value (SPP), asymptotically has a uniform probability distribution whatever the discrepancy function. In a moderate finite sample context, simulations also showed that the SPP appears stable to relatively uninformative misspecifications of the prior distribution. Conclusions/Significance: These reasons, together with its numerical simplicity, make the SPP a better canonical GOF p-value than existing GOF p-values

The relationship between target joints and direct resource use in severe haemophilia

Objectives Target joints are a common complication of severe haemophilia. While factor replacement therapy constitutes the majority of costs in haemophilia, the relationship between target joints and non drug-related direct costs (NDDCs) has not been studied. Methods Data on haemophilia patients without inhibitors was drawn from the ‘Cost of Haemophilia across Europe – a Socioeconomic Survey’ (CHESS) study, a cost assessment in severe haemophilia A and B across five European countries (France, Germany, Italy, Spain, and the United Kingdom) in which 139 haemophilia specialists provided demographic and clinical information for 1285 adult patients. NDDCs were calculated using publicly available cost data, including 12-month ambulatory and secondary care activity: haematologist and other specialist consultant consultations, medical tests and examinations, bleed-related hospital admissions, and payments to professional care providers. A generalized linear model was developed to investigate the relationship between NDDCs and target joints (areas of chronic synovitis), adjusted for patient covariates. Results Five hundred and thirteen patients (42% of the sample) had no diagnosed target joints; a total of 1376 target joints (range 1–10) were recorded in the remaining 714 patients. Mean adjusted NDDCs for persons with no target joints were EUR 3134 (standard error (SE) EUR 158); for persons with one or more target joints, mean adjusted NDDCs were EUR 3913 (SE EUR 157; average mean effect EUR 779; p < 0.001). Conclusions Our analysis suggests that the presence of one or more target joints has a significant impact on NDDCs for patients with severe haemophilia, ceteris paribus. Prevention and management of target joints should be an important consideration of managing haemophilia patients

Management of asthma in pregnant women by general practitioners: A cross sectional survey

<p>Abstract</p> <p>Background</p> <p>Poorly controlled asthma can lead to maternal and fetal complications. Despite the known risks of poorly controlled asthma during pregnancy and the need for stepping up therapy when appropriate, there are concerns that management is suboptimal in primary care.</p> <p>Our objective was to investigate the management of asthma during pregnancy by general practitioners providing shared maternity care.</p> <p>Methods</p> <p>A pre-piloted, anonymous mail survey was sent to all general practitioners (n = 842) involved in shared maternity care at six maternity hospitals in Victoria, Australia. Respondents were asked about their perceived safety of individual asthma medications during pregnancy. Approach to asthma management during pregnancy was further explored using scenarios of pregnant women with stable and deteriorating asthma and poor medication adherence.</p> <p>Results</p> <p>Inhaled corticosteroids (ICS) were perceived to be the safest and were the preferred preventive medication in first trimester (74.1%), whilst leukotriene receptor antagonists were the least preferred (2.9%). A quarter (25.8%) of respondents would stop or decrease patients' ICS doses during pregnancy, even when their asthma was well controlled by current therapy. In addition, 12.1% of respondents were not sure how to manage deteriorating asthma during pregnancy and opted to refer to another health professional. Almost half the respondents (48.9%) reported encountering medication nonadherence during pregnancy.</p> <p>Conclusion</p> <p>A lack of confidence and/or knowledge among general practitioners in managing deteriorating asthma in pregnancy was observed despite a good understanding of the safety of asthma medications during pregnancy, compliance with evidence-based guidelines in the selection of preventive medications, and self reported good asthma knowledge.</p

A multidimensional systems biology analysis of cellular senescence in aging and disease.

BACKGROUND: Cellular senescence, a permanent state of replicative arrest in otherwise proliferating cells, is a hallmark of aging and has been linked to aging-related diseases. Many genes play a role in cellular senescence, yet a comprehensive understanding of its pathways is still lacking. RESULTS: We develop CellAge (http://genomics.senescence.info/cells), a manually curated database of 279 human genes driving cellular senescence, and perform various integrative analyses. Genes inducing cellular senescence tend to be overexpressed with age in human tissues and are significantly overrepresented in anti-longevity and tumor-suppressor genes, while genes inhibiting cellular senescence overlap with pro-longevity and oncogenes. Furthermore, cellular senescence genes are strongly conserved in mammals but not in invertebrates. We also build cellular senescence protein-protein interaction and co-expression networks. Clusters in the networks are enriched for cell cycle and immunological processes. Network topological parameters also reveal novel potential cellular senescence regulators. Using siRNAs, we observe that all 26 candidates tested induce at least one marker of senescence with 13 genes (C9orf40, CDC25A, CDCA4, CKAP2, GTF3C4, HAUS4, IMMT, MCM7, MTHFD2, MYBL2, NEK2, NIPA2, and TCEB3) decreasing cell number, activating p16/p21, and undergoing morphological changes that resemble cellular senescence. CONCLUSIONS: Overall, our work provides a benchmark resource for researchers to study cellular senescence, and our systems biology analyses reveal new insights and gene regulators of cellular senescence