Using Radiological Data to Estimate Ischemic Stroke Severity

Background Risk-adjusted poststroke mortality has been proposed for use as a measure of stroke care quality. Although valid measures of stroke severity (e.g., the National Institutes of Health Stroke Scale [NIHSS]) are not typically available in administrative datasets, radiology reports are often available within electronic health records. We sought to examine whether admission head computed tomography data could be used to estimate stroke severity. Materials and Methods Using chart review data from a cohort of acute ischemic stroke patients (1998-2003), we developed a radiographic measure ([BIS]) of stroke severity in a two-third development set and assessed in a one-third validation set. The retrospective NIHSS was dichotomized as mild/moderate (<10) and severe (≥10). We compared the association of this radiographic score with NIHSS and in-hospital mortality at the patient level. Results Among 1348 stroke patients, 86.5% had abnormal findings on initial head computed tomography. The c-statistic for the BIS for modeling severe stroke (development, .581; validation, .579) and in-hospital mortality (development, .623; validation, .678) were generated. Conclusions Although the c-statistics were only moderate, the BIS provided significant risk stratification information with a 2-variable score. Until administrative data routinely includes a valid measure of stroke severity, radiographic data may provide information for use in risk adjustment

Prevalence, predictors, and outcomes of poststroke falls in acute hospital setting

Abstract—Falls are a serious medical complication following stroke. The objectives of this study were to (1) confirm the prevalence of falls among patients with stroke during acute hospitalization, (2) identify factors associated with falls during the acute stay, and (3) examine whether in-hospital falls were associated with loss of function after stroke (new dependence at discharge). We completed a secondary analysis of data from a retrospective cohort study of patients with ischemic stroke who were hospitalized at one of four hospitals. We used logistic regression to identify factors associated with inpatient falls and examine the association between falls and loss of function. Among 1,269 patients with stroke, 65 (5%) fell during the acute hospitalization period. We found two characteristics independently associated with falls: greater stroke severity (National Institutes of Health Stroke Scale [NIHSS] 8, adjusted odds ratio [OR] = 3.63, 95% confidence interval [CI]: 1.46–9.00) and history of anxiety (adjusted OR = 4.90, 95% CI: 1.70–13.90). Falls were independently associated with a loss of function (adjusted OR = 9.85, 95% CI: 1.22–79.75) even after adjusting for age, stroke severity, gait abnormalities, and past stroke. Stroke severity (NIHSS 8) may be clinically useful during the acute inpatient setting in identifying those at greatest risk of falling. Given the association between falls and poor patient outcomes, rehabilitation interventions should be implemented to prevent falls poststroke

Hanford Waste Physical and Rheological Properties: Data and Gaps

The Hanford Site in Washington State manages 177 underground storage tanks containing approximately 250,000 m3 of waste generated during past defense reprocessing and waste management operations. These tanks contain a mixture of sludge, saltcake and supernatant liquids. The insoluble sludge fraction of the waste consists of metal oxides and hydroxides and contains the bulk of many radionuclides such as the transuranic components and 90Sr. The saltcake, generated by extensive evaporation of aqueous solutions, consists primarily of dried sodium salts. The supernates consist of concentrated (5-15 M) aqueous solutions of sodium and potassium salts. The 177 storage tanks include 149 single-shell tanks (SSTs) and 28 double -hell tanks (DSTs). Ultimately the wastes need to be retrieved from the tanks for treatment and disposal. The SSTs contain minimal amounts of liquid wastes, and the Tank Operations Contractor is continuing a program of moving solid wastes from SSTs to interim storage in the DSTs. The Hanford DST system provides the staging location for waste feed delivery to the Department of Energy (DOE) Office of River Protection’s (ORP) Hanford Tank Waste Treatment and Immobilization Plant (WTP). The WTP is being designed and constructed to pretreat and then vitrify a large portion of the wastes in Hanford’s 177 underground waste storage tanks

Active, but not passive cigarette smoking was inversely associated with mammographic density

The opposing carcinogenic and antiestrogenic properties of tobacco smoke may explain why epidemiologic studies have not consistently reported positive associations for active smoking and breast cancer risk. A negative relation between mammographic density, a strong breast cancer risk factor, and active smoking would lend support for an antiestrogenic mechanism. We used multivariable linear regression to assess the associations of active smoking and secondhand smoke (SHS) exposure with mammographic density in 799 pre- and early perimenopausal women in the Study of Women’s Health Across the Nation (SWAN). We observed that current active smoking was associated with 7.2% lower mammographic density, compared to never active smoking and no SHS exposure (p = 0.02). Starting to smoke before 18 years of age and having smoked ≥20 cigarettes/day were also associated with statistically significantly lower percent densities. Among nulliparous women having smoked ≥20 cigarettes/day was associated with 23.8% lower density, compared to having smoked ≤9 cigarettes/day (p &lt; 0.001). Our findings support the hypothesis that tobacco smoke exerts an antiestrogenic effect on breast tissue, but counters the known increased risk of breast cancer with smoking prior to first full-term birth. Thus, our data suggest that the antiestrogenic but not the carcinogenic effects of smoking may be reflected by breast density

Minimum Technical Data Elements for Liquid Biopsy Data Submitted to Public Databases

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154656/1/cpt1747.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154656/2/cpt1747-sup-0001-FigS1.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154656/3/cpt1747_am.pd

Collaborative Depression Trial (CADET): multi-centre randomised controlled trial of collaborative care for depression - study protocol

<p>Abstract</p> <p>Background</p> <p>Comprising of both organisational and patient level components, collaborative care is a potentially powerful intervention for improving depression treatment in UK primary Care. However, as previous models have been developed and evaluated in the United States, it is necessary to establish the effect of collaborative care in the UK in order to determine whether this innovative treatment model can replicate benefits for patients outside the US. This Phase III trial was preceded by a Phase II patient level RCT, following the MRC Complex Intervention Framework.</p> <p>Methods/Design</p> <p>A multi-centre controlled trial with cluster-randomised allocation of GP practices. GP practices will be randomised to usual care control or to "collaborative care" - a combination of case manager coordinated support and brief psychological treatment, enhanced specialist and GP communication. The primary outcome will be symptoms of depression as assessed by the PHQ-9.</p> <p>Discussion</p> <p>If collaborative care is demonstrated to be effective we will have evidence to enable the NHS to substantially improve the organisation of depressed patients in primary care, and to assist primary care providers to deliver a model of enhanced depression care which is both effective and acceptable to patients.</p> <p>Trial Registration Number</p> <p>ISRCTN32829227</p

Ventricular Geometry From Non-contrast Non-ECG-gated CT Scans:An Imaging Marker of Cardiopulmonary Disease in Smokers

Cardiovascular disease is a major cause of morbidity in smokers, and as much as 50% of the estimated 24 million patients in the United States with chronic obstructive pulmonary disease (COPD) die of cardiovascular causes (1,2). Although echocardiography and cardiac magnetic resonance imaging (MRI) are often used to study cardiac structure and function in COPD (3), these are not routinely deployed in all smokers. Computed tomographic (CT) imaging of the chest is broadly used in clinical care and is increasingly used for lung cancer screening in high-risk smokers (4). Assessment of cardiac structure on those CT scans may help identify patients with COPD at greater risk of developing cardiac dysfunction. Rapid, noninvasive assessments of cardiac morphology and a better understanding of the functional interdependence of heart and lung may improve healthcare outcomes through early detection and initiation of treatment

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same regio

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives