73 research outputs found
The SCottish Alcoholic Liver disease Evaluation: a population-level matched cohort study of hospital-based costs, 1991-2011
Studies assessing the costs of alcoholic liver disease are lacking. We aimed to calculate the costs of hospitalisations before and after diagnosis compared to population controls matched by age, sex and socio-economic deprivation. We aimed to use population level data to identify a cohort of individuals hospitalised for the first time with alcoholic liver disease in Scotland between 1991 and 2011.Incident cases were classified by disease severity, sex, age group, socio-economic deprivation and year of index admission. 5 matched controls for every incident case were identified from the Scottish population level primary care database.
Hospital costs were calculated for both cases and controls using length of stay from morbidity records and hospital-specific daily rates by specialty. Remaining lifetime costs were estimated using parametric survival models and predicted annual costs. 35,208 incident alcoholic liver disease hospitalisations were identified. Mean annual hospital costs for cases were 2.3 times that of controls pre diagnosis (£804 higher) and 10.2 times (£12,774 higher) post diagnosis. Mean incident admission cost was £6,663. Remaining lifetime cost for a male, 50-59 years old, living in the most deprived area diagnosed with acoholic liver disease was estimated to be £65,999 higher than the matched controls (£12,474 for 7.43 years remaining life compared to £1,224 for 21.8 years). In Scotland, alcoholic liver disease diagnosis is associated with significant increases in admissions to hospital both before and after diagnosis.
Our results provide robust population level estimates of costs of alcoholic liver disease for the purposes of health-care delivery, planning and future cost-effectiveness analyses
Computational Bacterial Genome-Wide Analysis of Phylogenetic Profiles Reveals Potential Virulence Genes of Streptococcus agalactiae
The phylogenetic profile of a gene is a reflection of its evolutionary history
and can be defined as the differential presence or absence of a gene in a set of
reference genomes. It has been employed to facilitate the prediction of gene
functions. However, the hypothesis that the application of this concept can also
facilitate the discovery of bacterial virulence factors has not been fully
examined. In this paper, we test this hypothesis and report a computational
pipeline designed to identify previously unknown bacterial virulence genes using
group B streptococcus (GBS) as an example. Phylogenetic profiles of all GBS
genes across 467 bacterial reference genomes were determined by
candidate-against-all BLAST searches,which were then used to identify candidate
virulence genes by machine learning models. Evaluation experiments with known
GBS virulence genes suggested good functional and model consistency in
cross-validation analyses (areas under ROC curve, 0.80 and 0.98 respectively).
Inspection of the top-10 genes in each of the 15 virulence functional groups
revealed at least 15 (of 119) homologous genes implicated in virulence in other
human pathogens but previously unrecognized as potential virulence genes in GBS.
Among these highly-ranked genes, many encode hypothetical proteins with possible
roles in GBS virulence. Thus, our approach has led to the identification of a
set of genes potentially affecting the virulence potential of GBS, which are
potential candidates for further in vitro and in
vivo investigations. This computational pipeline can also be
extended to in silico analysis of virulence determinants of
other bacterial pathogens
Imaging lung function in mice using SPECT/CT and per-voxel analysis.
Chronic lung disease is a major worldwide health concern but better tools are required to understand the underlying pathologies. Ventilation/perfusion (V/Q) single photon emission computed tomography (SPECT) with per-voxel analysis allows for non-invasive measurement of regional lung function. A clinically adapted V/Q methodology was used in healthy mice to investigate V/Q relationships. Twelve week-old mice were imaged to describe normal lung function while 36 week-old mice were imaged to determine how age affects V/Q. Mice were ventilated with Technegas™ and injected with (99m)Tc-macroaggregated albumin to trace ventilation and perfusion, respectively. For both processes, SPECT and CT images were acquired, co-registered, and quantitatively analyzed. On a per-voxel basis, ventilation and perfusion were moderately correlated (R = 0.58±0.03) in 12 week old animals and a mean log(V/Q) ratio of -0.07±0.01 and standard deviation of 0.36±0.02 were found, defining the extent of V/Q matching. In contrast, 36 week old animals had significantly increased levels of V/Q mismatching throughout the periphery of the lung. Measures of V/Q were consistent across healthy animals and differences were observed with age demonstrating the capability of this technique in quantifying lung function. Per-voxel analysis and the ability to non-invasively assess lung function will aid in the investigation of chronic lung disease models and drug efficacy studies
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