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PubMed2000

Measuring the costs and benefits of heart disease monitoring.

OBJECTIVE: To evaluate the costs and benefits of alternative systems of coronary heart disease monitoring in Scotland. DESIGN: An option appraisal was conducted to evaluate the costs and benefits of implementing a coronary heart disease monitoring system. This involved a review of existing Scottish datasets and relevant reports, specification of options, definition and weighting of benefit criteria by key stakeholders, assessment of options by experts, and costing of options. The options were assessed by 33 stakeholders (grouped as cardiologists, patient representatives, general practitioners, public health physicians, and policy makers), plus 13 topic experts. SETTING: Scotland (population 5.1 million). RESULTS: Between group mean benefit weights were: mortality rates and case fatality (10.6), quality of life (9.8), patient function (8.8), hospital activity (7.8), primary care activity (9.25), prescribing (5.72), socioeconomic impact (4.0), risk factors (7.4), prevalence (5.0), incidence (6.0), case registration (6.82), international comparability (4.2), breadth of coverage (8.8), and frequency (5.8). Differences between group weights were significant for prevalence (p = 0.048) and international comparability (p = 0.032). Four monitoring options were identified: a community epidemiology model, based on MONICA (monitoring trends and determinants in cardiovascular disease) study methodology applied to a series of eight representative communities, had the highest benefits, at an average annual discounted cost of approximately pound 360,000; models based on the Australian cardiovascular disease monitoring scheme and on enhanced routine data offered fewer benefits at discounted average annual costs ranging from pound 165,000 to pound 195,000; finally, a coronary heart disease registry modelled on the Scottish Cancer Registry scheme would have had fewer benefits and substantially higher costs than the other options. CONCLUSIONS: The most beneficial coronary heart disease monitoring system is the community epidemiology model, based on MONICA methodology. Option appraisal potentially offers an explicit and transparent methodology for evidence based policy development.

Coronary Disease↗

PubMed1993

A bivariate approach to meta-analysis.

The usual meta-analysis of a sequence of randomized clinical trials only considers the difference between two treatments and produces a point estimate and a confidence interval for a parameter that measures this difference. The usual parameter is the log(odds ratio) linked to Mantel-Haenszel methodology. Inference is made either under the assumption of homogeneity or in a random effects model that takes account of heterogeneity between trials. This paper has two goals. The first is to present a likelihood based method for the estimation of the parameters in the random effects model, which avoids the use of approximating Normal distributions. The second goal is to extend this method to a bivariate random effects model, in which the effects in both groups are supposed random. In this way inference can be made about the relationship between improvement and baseline effect. The method is demonstrated by a meta-analysis dataset of Collins and Langman.

Analysis of Variance↗

PubMed2002

Databases and tools for browsing genomes.

To maximize the value of genome sequences they need to be integrated with other types of biological data and with each other. The entire collection of data then needs to be made available in a way that is easy to view and mine for complex relationships. The recently determined vertebrate genome sequences of human and mouse are so large that building the infrastructure to manage these datasets is a major challenge. This article reviews the database systems and tools for analysis that have so far been developed to address this.

Animals↗

PubMed1998

Nursing terminology: a comparison of the ICNP and the nursing intervention lexicon and taxonomy.

The purpose of this paper is to provide an overview of nursing terminology work done to date and to compare the labels and subsumed terms of the recent alpha version of the International Classification of Nursing Practice (ICNP) with the verb terms (n = 147) of the interventions in a dataset of interventions (n = 7292) categorized using the Nursing Intervention Lexicon and Taxonomy (NILT). Two estimates were used to evaluate the adequacy of the ICNP terms for representing intervention terminology. Term matches were done using the NILT categories most similar to the ICNP action types. The ICNP action type 'observing' (and its subsumed terms) was best, accounting for 20% of the NILT verbs. The ICNP label 'observing' (and its subsumed terms) ranked first in accounting for 69% of the interventions in the NILT categories (CND & CV). The remaining action types had many fewer matches for the verbs and interventions in the NILT dataset. Thus it is possible to conclude that a relatively small subset of the verb terms, and interventions in a dataset of natural language interventions categorized using NILT have been captured by the INCP alpha version of Axis A.

Humans↗

PubMed2006

Lateral impact injuries with side airbag deployments--a descriptive study.

The present study was designed to provide descriptive data on side impact injuries in vehicles equipped with side airbags using the United States National Automotive Sampling System (NASS). The database was queried with the constraint that all vehicles must adhere to the Federal Motor Vehicle Safety Standards FMVSS 214, injured occupants be in the front outboard seats with no rollovers or ejections, and side impacts airbags be deployed in lateral crashes. Out of the 7812 crashes in the 1997-2004 weighted NASS files, AIS > or = 2 level injuries occurred to 5071 occupants. There were 3828 cases of torso-only airbags, 955 cases of torso-head bag combination, and 288 inflatable tubular structure/curtain systems. Side airbags were not attributed to be the cause of head or chest injury to any occupant at this level of severity. The predominance of torso-only airbags followed by torso-head airbag combination reflected vehicle model years and changing technology. Head and chest injuries were coupled for the vast majority of occupants with injuries to more than one body region. Comparing literature data for side impacts without side airbag deployments, the presence of a side airbag decreased AIS=2 head, chest, and extremity injuries when examining raw data incidence rates. Although this is the first study to adopt strict inclusion-exclusion criteria for side crashes with side airbag deployments, future studies are needed to assess side airbag efficacy using datasets such as matched-pair occupants in side impacts.

Abdominal Injuries↗

PubMed2004

How do insect nuclear and mitochondrial gene substitution patterns differ? Insights from Bayesian analyses of combined datasets.

We analyzed 12 combined mitochondrial and nuclear gene datasets in seven orders of insects using both equal weights parsimony (to evaluate phylogenetic utility) and Bayesian methods (to investigate substitution patterns). For the Bayesian analyses we used relatively complex models (e.g., general time reversible models with rate variation) that allowed us to quantitatively compare relative rates among genes and codon positions, patterns of rate variation among genes, and substitution patterns within genes. Our analyses indicate that nuclear and mitochondrial genes differ in a number of important ways, some of which are correlated with phylogenetic utility. First and most obviously, nuclear genes generally evolve more slowly than mitochondrial genes (except in one case), making them better markers for deep divergences. Second, nuclear genes showed universally high values of CI and (generally) contribute more to overall tree resolution than mitochondrial genes (as measured by partitioned Bremer support). Third, nuclear genes show more homogeneous patterns of among-site rate variation (higher values of alpha than mitochondrial genes). Finally, nuclear genes show more symmetrical transformation rate matrices than mitochondrial genes. The combination of low values of alpha and highly asymmetrical transformation rate matrices may explain the overall poor performance of mitochondrial genes when compared to nuclear genes in the same analysis. Our analyses indicate that some parameters are highly correlated. For example, A/T bias was positively and significantly associated with relative rate and CI was positively and significantly associated with alpha (the shape of the gamma distribution). These results provide important insights into the substitution patterns that might characterized high quality genes for phylogenetic analysis: high values of alpha, unbiased base composition, and symmetrical transformation rate matrices. We argue that insect molecular systematists should increasingly focus on nuclear rather than mitochondrial gene datasets because nuclear genes do not suffer from the same substitutional biases that characterize mitochondrial genes.

Animals↗

PubMed2005

Promoter classifier: software package for promoter database analysis.

Promoter Classifier is a package of seven stand-alone Windows-based C++ programs allowing the following basic manipulations with a set of promoter sequences: (i) calculation of positional distributions of nucleotides averaged over all promoters of the dataset; (ii) calculation of the averaged occurrence frequencies of the transcription factor binding sites and their combinations; (iii) division of the dataset into subsets of sequences containing or lacking certain promoter elements or combinations; (iv) extraction of the promoter subsets containing or lacking CpG islands around the transcription start site; and (v) calculation of spatial distributions of the promoter DNA stacking energy and bending stiffness. All programs have a user-friendly interface and provide the results in a convenient graphical form. The Promoter Classifier package is an effective tool for various basic manipulations with eukaryotic promoter sequences that usually are necessary for analysis of large promoter datasets. The program Promoter Divider is described in more detail as a representative component of the package.

Algorithms↗

PubMed1998

A comparative study on different methods of automatic mesh generation of human femurs.

The aim of this study was to evaluate comparatively five methods for automating mesh generation (AMG) when used to mesh a human femur. The five AMG methods considered were: mapped mesh, which provides hexahedral elements through a direct mapping of the element onto the geometry; tetra mesh, which generates tetrahedral elements from a solid model of the object geometry; voxel mesh which builds cubic 8-node elements directly from CT images; and hexa mesh that automatically generated hexahedral elements from a surface definition of the femur geometry. The various methods were tested against two reference models: a simplified geometric model and a proximal femur model. The first model was useful to assess the inherent accuracy of the meshes created by the AMG methods, since an analytical solution was available for the elastic problem of the simplified geometric model. The femur model was used to test the AMG methods in a more realistic condition. The femoral geometry was derived from a reference model (the "standardized femur") and the finite element analyses predictions were compared to experimental measurements. All methods were evaluated in terms of human and computer effort needed to carry out the complete analysis, and in terms of accuracy. The comparison demonstrated that each tested method deserves attention and may be the best for specific situations. The mapped AMG method requires a significant human effort but is very accurate and it allows a tight control of the mesh structure. The tetra AMG method requires a solid model of the object to be analysed but is widely available and accurate. The hexa AMG method requires a significant computer effort but can also be used on polygonal models and is very accurate. The voxel AMG method requires a huge number of elements to reach an accuracy comparable to that of the other methods, but it does not require any pre-processing of the CT dataset to extract the geometry and in some cases may be the only viable solution.

Algorithms↗

PubMed2003

Application of independent component analysis to microarrays.

We apply linear and nonlinear independent component analysis (ICA) to project microarray data into statistically independent components that correspond to putative biological processes, and to cluster genes according to over- or under-expression in each component. We test the statistical significance of enrichment of gene annotations within clusters. ICA outperforms other leading methods, such as principal component analysis, k-means clustering and the Plaid model, in constructing functionally coherent clusters on microarray datasets from Saccharomyces cerevisiae, Caenorhabditis elegans and human.

Algorithms↗

PubMed1993

Animated visualization of a high resolution color three dimensional digital computer model of the whole human head.

The interactive visualization of animated images through a computerized three dimensional (3D) full color model of an unstained cadaveric human head is presented. Serial full color images were taken of the blockface of a cryomicrotomed frozen human head every 200 microns. From this series of images a three dimensional digital model with a resultant pixel resolution of 200 microns3 was created on a UNIX workstation. Using this database, resampled images were computed along orthogonal axes and written sequentially to a write-once-read-many times (WORM) videodisc unit. Playback of this customized videodisc dataset provides animations of the digitally reconstructed slices and 3D reconstructed surface models. An interactive interface to the animated sequences is provided through a PC based tutorial package. This tutorial program is able to access videodisc frames to display animations and labeled still images in a software window to illustrate various neuroanatomic topics. The technique of animation as applied to this high resolution 3D model provides insight into complex spatial relationships and has great potential in research and as a teaching tool in the neurosciences.

Brain↗

PubMed2003

Cluster analysis of structural stage classes to map wildland fuels in a Madrean ecosystem.

Geospatial information technology is changing the nature of fire mapping science and management. Geographic information systems (GIS) and global positioning system technology coupled with remotely sensed data provide powerful tools for mapping, assessing, and understanding the complex spatial phenomena of wildland fuels and fire hazard. The effectiveness of these technologies for fire management still depends on good baseline fuels data since techniques have yet to be developed to directly interrogate understory fuels with remotely sensed data. We couple field data collections with GIS, remote sensing, and hierarchical clustering to characterize and map the variability of wildland fuels within and across vegetation types. One hundred fifty six fuel plots were sampled in eight vegetation types ranging in elevation from 1150 to 2600 m surrounding a Madrean 'sky island' mountain range in the southwestern US. Fuel plots within individual vegetation types were divided into classes representing various stages of structural development with unique fuel load characteristics using a hierarchical clustering method. Two Landsat satellite images were then classified into vegetation/fuel classes using a hybrid unsupervised/supervised approach. A back-classification accuracy assessment, which uses the same pixels to test as used to train the classifier, produced an overall Kappa of 50% for the vegetation/fuels map. The map with fuel classes within vegetation type collapsed into single classes was verified with an independent dataset, yielding an overall Kappa of 80%.

Cluster Analysis↗

PubMed2006

Substring selection for biomedical document classification.

MOTIVATION: Attribute selection is a critical step in development of document classification systems. As a standard practice, words are stemmed and the most informative ones are used as attributes in classification. Owing to high complexity of biomedical terminology, general-purpose stemming algorithms are often conservative and could also remove informative stems. This can lead to accuracy reduction, especially when the number of labeled documents is small. To address this issue, we propose an algorithm that omits stemming and, instead, uses the most discriminative substrings as attributes. RESULTS: The approach was tested on five annotated sets of abstracts from iProLINK that report on the experimental evidence about five types of protein post-translational modifications. The experiments showed that Naive Bayes and support vector machine classifiers perform consistently better [with area under the ROC curve (AUC) accuracy in range 0.92-0.97] when using the proposed attribute selection than when using attributes obtained by the Porter stemmer algorithm (AUC in 0.86-0.93 range). The proposed approach is particularly useful when labeled datasets are small.

Abstracting and Indexing↗

PubMed2002

Effective size of fluctuating salmon populations.

Pacific salmon are semelparous but have overlapping year classes, which presents special challenges for the application of standard population genetics theory to these species. This article examines the relationship between the effective number of breeders per year (N(b)) and single-generation and multigeneration effective population size (N(e)) in salmon populations that fluctuate in size. A simple analytical model is developed that allows calculation of N(e) on the basis of the number of spawners in individual years and their reproductive contribution (productivity) to the next generation. Application of the model to a 36-year time series of data for a threatened population of Snake River chinook salmon suggests that variation in population dynamic processes across years reduced the multigeneration N(e) by approximately 40-60%, and reductions may have been substantially greater within some generations. These reductions are comparable in magnitude to, and in addition to, reductions in N(b) within a year due to unequal sex ratio and nonrandom variation in reproductive success. Computer simulations suggest that the effects of variable population dynamics on N(e) observed in this dataset are not unexpected for species with a salmon life history, as random variation in productivity can lead to similar results.

Computer Simulation↗

PubMed2005

Bayesian analysis for generalized linear models with nonignorably missing covariates.

We propose Bayesian methods for estimating parameters in generalized linear models (GLMs) with nonignorably missing covariate data. We show that when improper uniform priors are used for the regression coefficients, phi, of the multinomial selection model for the missing data mechanism, the resulting joint posterior will always be improper if (i) all missing covariates are discrete and an intercept is included in the selection model for the missing data mechanism, or (ii) at least one of the covariates is continuous and unbounded. This impropriety will result regardless of whether proper or improper priors are specified for the regression parameters, beta, of the GLM or the parameters, alpha, of the covariate distribution. To overcome this problem, we propose a novel class of proper priors for the regression coefficients, phi, in the selection model for the missing data mechanism. These priors are robust and computationally attractive in the sense that inferences about beta are not sensitive to the choice of the hyperparameters of the prior for phi and they facilitate a Gibbs sampling scheme that leads to accelerated convergence. In addition, we extend the model assessment criterion of Chen, Dey, and Ibrahim (2004a, Biometrika 91, 45-63), called the weighted L measure, to GLMs and missing data problems as well as extend the deviance information criterion (DIC) of Spiegelhalter et al. (2002, Journal of the Royal Statistical Society B 64, 583-639) for assessing whether the missing data mechanism is ignorable or nonignorable. A novel Markov chain Monte Carlo sampling algorithm is also developed for carrying out posterior computation. Several simulations are given to investigate the performance of the proposed Bayesian criteria as well as the sensitivity of the prior specification. Real datasets from a melanoma cancer clinical trial and a liver cancer study are presented to further illustrate the proposed methods.

Bayes Theorem↗

PubMedDate not supplied

Counting crises: US hospital evacuations, 1971-1999.

OBJECTIVES: To investigate the relative distribution of hazards causing hospital evacuations, thereby to provide rudimentary risk information for hospital disaster planning. METHODS: Cases of hospital evacuations were retrieved from newspaper and publication databases and classified according to hazard type, proximate and original cause, duration, and casualties. Both partial and full evacuations were included. The total number of evacuation incidents for all hazards were compared to the total number of hospital incidents for the one hazard, fire, for which national data is available. RESULTS: There were 275 reported evacuation incidents from 1971-1999, with an annual average of 21 in the 1990s, the period for which databases were more reliable. The most, 33, were recorded in 1994, the year of the Northridge Earthquake. Of all incidents, 63 (23%) were attributable primarily to internal fire, followed by internal hazardous materials (HazMat) events (18%), hurricane (14%), human threat (13%), earthquake (9%), external fire (6%), flood (6%), utility failure (5%), and external HazMat (4%). CONCLUSIONS: More than 50% of the hospital evacuations occurred because of hazards originating in the hospital facility itself or from human intruders. While natural disasters were not the preponderant causes of evacuations, they caused severe problems when multiple hospitals in the same urban area were incapacitated simultaneously. Clearly, as hospitals are vulnerable to many hazards, mitigation investments should be assessed not in terms of single-hazard risk-cost-benefit analysis, but in terms of capacity to mitigate multiple hazards. In view of the many qualifications and limitations of the dataset used here, but value of such data for disaster planning, hospitals should be asked to submit standardized incident reports to permit national data gathering on major disruptions.

Databases as Topic↗

PubMed2001

Genome-wide detection of alternative splicing in expressed sequences of human genes.

We have identified 6201 alternative splice relationships in human genes, through a genome-wide analysis of expressed sequence tags (ESTs). Starting with approximately 2.1 million human mRNA and EST sequences, we mapped expressed sequences onto the draft human genome sequence and only accepted splices that obeyed the standard splice site consensus. A large fraction (47%) of these were observed multiple times, indicating that they comprise a substantial fraction of the mRNA species. The vast majority of the detected alternative forms appear to be novel, and produce highly specific, biologically meaningful control of function in both known and novel human genes, e.g. specific removal of the lysosomal targeting signal from HLA-DM beta chain, replacement of the C-terminal transmembrane domain and cytoplasmic tail in an FC receptor beta chain homolog with a different transmembrane domain and cytoplasmic tail, likely modulating its signal transduction activity. Our data indicate that a large proportion of human genes, probably 42% or more, are alternatively spliced, but that this appears to be observed mainly in certain types of molecules (e.g. cell surface receptors) and systemic functions, particularly the immune system and nervous system. These results provide a comprehensive dataset for understanding the role of alternative splicing in the human genome, accessible at http://www.bioinformatics.ucla.edu/HASDB.

Alternative Splicing↗

PubMed2000

Stochastic heuristic algorithms for target motif identification (extended abstract).

Target motifs are motifs that are "close" to one or more substrings in each sequence in one given set of sequences but are far from every substring in another given set of sequences. Target motifs have pharmaceutical applications; unfortunately, the problem of identifying target motifs is NP-hard and is thus unlikely to have efficient optimal solution algorithms. In this paper, we propose a set of simple modifications to the Gibbs Sampling heuristic for finding motifs which allows this heuristic to detect target motifs. We also present the results of several experiments relative to both simulated and real datasets which suggest that this modified heuristic is good at detecting target motifs under a variety of conditions.

Algorithms↗

PubMed1995

A quantitative structure-activity relationship for the eye irritation potential of neutral organic chemicals.

Quantitative structure-activity relationships (QSARs) have been derived relating eye irritation data of a set of neutral organic chemicals to log(octanol-water partition coefficient), the minor principal inertial axes (Ry and Rz) and dipole moment. Datasets were analysed using principal components analysis; plots of the first 2 principal components of the above parameters showed that the analysis was able to discriminate well between the irritant and non-irritant chemicals in the dataset. The derived QSAR could be useful for the prediction of the eye irritation potential of new or untested chemicals within this category.

Animal Testing Alternatives↗