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PubMed2005

Eliminating diagnostic drift in the validation of acute in-hospital myocardial infarction--implication for documenting trends across 25 years: the Minnesota Heart Survey.

Long-term trends in epidemiologic studies of acute myocardial infarction (AMI) require application of a consistent diagnostic algorithm. Typically an algorithm includes chest pain, cardiac enzymes, electrocardiographic findings, and autopsy results. The Minnesota Heart Survey (MHS) has determined trends for incident AMI and for in-hospital and long-term outcomes over a 25-year period (1970-1995). However, dramatic changes have occurred that seriously challenge the ability of the MHS and other epidemiologic studies to use a consistent diagnostic algorithm. These include newer and more sensitive cardiac biomarkers, introduction of diagnosis-related groups, and change in International Classification of Diseases coding. In the MHS, the electrocardiogram is the only diagnostic element consistently available and consistently classified over this 25-year period. The authors identified eight dichotomous Minnesota Code criteria that provided a consistent diagnostic method from 1970 to 1995 as documented by extensive cross-validation. These criteria were combined into a logistic score and used to define incident, recurrent, and attack AMI rates over this 25-year period. For both men and women, AMI rates determined by electrocardiogram are parallel to rates based on the International Classification of Diseases and parallel over adjacent survey periods to the standard MHS algorithm. The electrocardiogram classified by Minnesota Code provides the only consistent long-term diagnostic tool for AMI trends over this 25-year period.

Adult↗

PubMed2006

The clinical and physiological spectrum of interferon-alpha induced thyroiditis: toward a new classification.

Interferon-alpha (IFNalpha) is a major treatment modality for several malignant and nonmalignant diseases, especially hepatitis C. Prospective studies have shown that up to 15% of patients with hepatitis C receiving IFNalpha develop clinical thyroid disease, and up to 40% were reported to develop thyroid antibodies. Some of these complications may result in discontinuation of interferon therapy. Thus, interferon induced thyroiditis (IIT) is a major clinical problem for patients receiving interferon therapy. IIT can be classified as autoimmune type and non-autoimmune type. Autoimmune IIT may manifest by the development of thyroid antibodies without clinical disease, or by clinical disease which includes both autoimmune hypothyroidism (Hashimoto's thyroiditis) and autoimmune thyrotoxicosis (Graves' disease). Non-autoimmune IIT can manifest as destructive thyroiditis or as hypothyroidism with negative thyroid antibodies. Early detection and therapy of these conditions is important in order to avoid complications of thyroid disease such as cardiac arrhythmias. While it is not clear which factors contribute to the susceptibility to IIT, recent evidence suggests that genetic factors, gender, and hepatitis C virus infection may play a role. In contrast, viral genotype and therapeutic regimen do not influence susceptibility to IIT. The etiology of IIT is unknown and may be secondary to immune modulation by IFNalpha and/or direct effects of interferon on the thyroid. In this review we discuss the clinical and pathophysiological aspects of IIT, and we are proposing a new, etiology-based classification of IIT, as well as an algorithm for diagnosis and treatment of IIT.

Disease Susceptibility↗

PubMed2003

Applications of Fourier transform infrared microspectroscopy in studies of benign prostate and prostate cancer. A pilot study.

Fourier transform infrared (FTIR) microspectroscopy has been applied to a study of prostate cancer cell lines derived from different metastatic sites and to tissue from benign prostate and Gleason-graded malignant prostate tissue. Paraffin-embedded tissue samples were analysed by FTIR, after mounting onto a BaF(2) plate and subsequent removal of wax using Citroclear followed by acetone. Cell lines were analysed as aliquots of cell suspension held between two BaF(2) plates. It was found that the ratio of peak areas at 1030 and 1080 cm(-1), corresponding to the glycogen and phosphate vibrations respectively, suggests a potential method for the differentiation of benign from malignant cells. The use of this ratio in association with FTIR spectral imaging provides a basis for estimating areas of malignant tissue within defined regions of a specimen. Initial chemometric treatment of FTIR spectra, using the linear discriminant algorithm, demonstrates a promising method for the classification of benign and malignant tissue and the separation of Gleason-graded CaP spectra. Using the principle component analysis, this study has achieved for the first time the separation of FTIR spectra of prostate cancer cell lines derived from different metastatic sites.

Adenocarcinoma↗

PubMed2003

Tree-based disease classification using protein data.

A reliable and precise classification of diseases is essential for successful diagnosis and treatment. Using mass spectrometry from clinical specimens, scientists may find the protein variations among disease and use this information to improve diagnosis. In this paper, we propose a novel procedure to classify disease status based on the protein data from mass spectrometry. Our new tree-based algorithm consists of three steps: projection, selection and classification tree. The projection step aims to project all observations from specimens into the same bases so that the projected data have fixed coordinates. Thus, for each specimen, we obtain a large vector of 'coefficients' on the same basis. The purpose of the selection step is data reduction by condensing the large vector from the projection step into a much lower order of informative vector. Finally, using these reduced vectors, we apply recursive partitioning to construct an informative classification tree. This method has been successfully applied to protein data, provided by the Department of Radiology and Chemistry at Duke University.

Computational Biology↗

PubMed1983

An empirical evaluation of qualitative Hennigian analyses of protein electrophoretic data.

In an empirical evaluation of a qualitative approach to construction of phylogenetic trees from protein-electrophoretic data, we have employed Hennigian cladistic principles to generate molecular trees for water-fowl, rodents, bats, and other phylads. This procedure of tree construction is described in detail. Branching structures of molecular trees produced by three different algorithms were compared against those of "model" classifications previously proposed by other systematists. In each case, the qualitative cladistic trees provided fits to model phylogenies which were strong and as good or better than those resulting from phenetic-clustering or distance-Wagner trees based on manipulation of quantitative values in matrices of genetic distance. The qualitative Hennigian approach has several pragmatic (as well as theoretical) advantages for analyzing routine sets of electrophoretic data: (1) the analyses are simple and can be performed by hand; (2) they provide the researcher with a strong "feel" for the data; (3) additional data (from new loci or species) can readily be added to the tree without need to recalculate distance matrices; and (4) the qualitative output of the analyses explicitly defines character states along all branches of the tree, and hence affords a high degree of testability. However, these advantages are counterbalanced by a number of serious disadvantages which will likely limit the general applicability of this qualitative approach. These drawbacks are also discussed in detail. For a deeper appreciation of electrophoretic-based protein phylogenies, it is suggested that both quantitative phenetic and qualitative cladistic analyses be employed when possible, and that results of the two approaches be contrasted.

Animals↗

PubMed2005

On line extraction of temporal episodes from ICU high-frequency data: a visual support for signal interpretation.

This paper presents a method to extract on line temporal episodes from high-frequency physiological parameters monitored in ICU, as a visual support for signal interpretation. Temporal episodes are expressions such as: "systolic blood pressure is steady at 120 mmHg from time t(0) until time t(1); it increases from 120 to 160 mmHg from time t(1) to time t(2) ...". Three words are used to describe the data evolution: {steady, increasing, decreasing}. The method deals with noisy data and missing values. It uses a segmentation algorithm that was developed previously and a classification of the segments into temporal patterns. The results obtained on simulated data are quite satisfactory. They show that the method is able to detect rapid variations as well as slow trends. Episodes extracted from real S(p)o(2) data recorded over a period of 44 h from 10 different adult patients are analysed. The visual representation of the temporal episodes is a powerful tool to help the physicians analyse in a glance the evolution in time of the variables monitored. It can help carer personnel to make quicker decisions in alarm situations.

Computer Simulation↗

PubMed2005

Surgical thrombectomy followed by intraoperative endovascular reconstruction for symptomatic ilio-femoral venous thrombosis.

OBJECTIVES: To evaluate the efficacy of surgical thrombectomy combined with endovascular reconstruction for acute ilio-femoral/caval venous thrombosis. METHODS: Twenty consecutive patients with acute, symptomatic ilio-femoral/-caval thrombosis underwent valve-preserving thrombectomy with immediate endovascular repair between October 1996 and October 2003. Thrombectomy was classified by intraoperative venography as: TYPE I=complete, TYPE II=partial, TYPE III=complete with stenosis other than thrombus, TYPE IV=permanent occlusion. TYPEs I and IV were excluded from this analysis because endovascular repair was not performed. RESULTS: Left-sided venous thrombosis predominated (90%). Lesions were located in the common iliac vein (85%), the external iliac vein (10%), and the inferior vena cava (5%). Three TYPE II lesions and 17 TYPE III lesions (11 spurs, one hypoplasia, one fibrosis, one haematoma, and three others) were diagnosed. Catheter-directed recanalisation (thrombectomy/thrombolysis) resolved TYPE II lesions in three patients. Balloon angioplasty (one patient), iliac stenting (15 patients [two with thrombolysis]), and caval stenting (one patient) were employed in TYPE III stenoses. No serious complication or death occurred. Mean follow-up was 21 months. Of 20 patients clinical results were excellent in 18 patients who maintained patency of their reconstructed iliac veins. Primary and secondary patency rates were 80 and 90%, respectively. CONCLUSIONS: Ilio-caval venous obstructions detected intraoperatively can be reconstructed in a one-stage combined procedure. The specific endovascular approach depends on the type of residual venous obstruction. Excellent mid-term results indicate that the proposed thrombectomy classification (TYPE I-IV) and treatment algorithm optimises the results in selected patients with symptomatic venous thrombosis.

Adolescent↗

PubMed2004

Comprehensive vertical sample-based KNN/LSVM classification for gene expression analysis.

Classification analysis of microarray gene expression data has been widely used to uncover biological features and to distinguish closely related cell types that often appear in the diagnosis of cancer. However, the number of dimensions of gene expression data is often very high, e.g., in the hundreds or thousands. Accurate and efficient classification of such high-dimensional data remains a contemporary challenge. In this paper, we propose a comprehensive vertical sample-based KNN/LSVM classification approach with weights optimized by genetic algorithms for high-dimensional data. Experiments on common gene expression datasets demonstrated that our approach can achieve high accuracy and efficiency at the same time. The improvement of speed is mainly related to the vertical data representation, P-tree,Patents are pending on the P-tree technology. This work is partially supported by GSA Grant ACT#:K96130308. and its optimized logical algebra. The high accuracy is due to the combination of a KNN majority voting approach and a local support vector machine approach that makes optimal decisions at the local level. As a result, our approach could be a powerful tool for high-dimensional gene expression data analysis.

Algorithms↗

PubMed2006

Machine learning in soil classification.

In a number of engineering problems, e.g. in geotechnics, petroleum engineering, etc. intervals of measured series data (signals) are to be attributed a class maintaining the constraint of contiguity and standard classification methods could be inadequate. Classification in this case needs involvement of an expert who observes the magnitude and trends of the signals in addition to any a priori information that might be available. In this paper, an approach for automating this classification procedure is presented. Firstly, a segmentation algorithm is developed and applied to segment the measured signals. Secondly, the salient features of these segments are extracted using boundary energy method. Based on the measured data and extracted features to assign classes to the segments classifiers are built; they employ Decision Trees, ANN and Support Vector Machines. The methodology was tested in classifying sub-surface soil using measured data from Cone Penetration Testing and satisfactory results were obtained.

Algorithms↗

PubMed2006

Protein structure comparison: implications for the nature of 'fold space', and structure and function prediction.

The identification of geometric relationships between protein structures offers a powerful approach to predicting the structure and function of proteins. Methods to detect such relationships range from human pattern recognition to a variety of mathematical algorithms. A number of schemes for the classification of protein structure have found widespread use and these implicitly assume the organization of protein structure space into discrete categories. Recently, an alternative view has emerged in which protein fold space is seen as continuous and multidimensional. Significant relationships have been observed between proteins that belong to what have been termed different 'folds'. There has been progress in the use of these relationships in the prediction of protein structure and function.

Computational Biology↗

PubMed2005

Development and validation of an in vivo analysis tool to identify changes in carotid plaque tissue types in serial 3-D ultrasound scans.

We have developed a three-dimensional (3-D) B-mode acquisition system suitable for imaging carotid plaques in vivo. A texture classification system using 157 statistical and textural algorithms, previously developed in our laboratory and shown to predict the contents of in vitro carotid plaques, was applied to in vivo 3-D image sets obtained from patients with both symptomatic and asymptomatic carotid artery plaques. Delineation of plaque boundaries is more difficult using in vivo images than in vitro images of excised plaques embedded in agar. This study has examined inter- and intraobserver variability studies to assess the degree of selectivity of the plaque region-of-interest (ROI) and assess the degree of repeatability for potential use in comparing serial scans. An interobserver limit of agreement of +/-12.9% and an intraobserver limit of repeatability of <2% were obtained. These results show that the plaque ROI selection is subjective, but is repeatable within acceptable limits.

Carotid Arteries↗

PubMed2006

Persistent mild cognitive impairment in geriatric depression.

BACKGROUND: Cognitive impairment often occurs with geriatric depression and impairments may persist despite remission of depression. Although clinical definitions of mild cognitive impairment (MCI) have typically excluded depression, a neuropsychological model of MCI in depression has utility for identifying individuals whose cognitive impairments may persist or progress to dementia. METHODS: At baseline and 1-year follow-up, 67 geriatric patients with depression had a comprehensive clinical examination that included depression assessment and neuropsychological testing. We defined MCI by a neuropsychological algorithm and examined the odds of MCI classification at Year 1 for remitted depressed individuals with baseline MCI, and examined clinical, functional and genetic factors associated with MCI. RESULTS: Fifty-four percent of the sample had MCI at baseline. Odds of MCI classification at Year 1 were four times greater among patients with baseline MCI than those without. Instrumental activities of daily living were associated with MCI at Year 1, while age and APOE genotype was not. CONCLUSIONS: These results confirm previous observations that MCI is highly prevalent among older depressed adults and that cognitive impairment occurring during acute depression may persist after depression remits. Self-reported decline in functional activities may be a marker for persistent cognitive impairment, which suggests that assessments of both neuropsychological and functional status are important prognostic factors in the evaluation of geriatric depression.

Aged↗

PubMed1999

[Exclusion of receptive speech disorders with the ADOS (Autism Diagnostic Observation Schedule)].

OBJECTIVE: The purpose of our pilot study was to assess the reliability and diagnostic validity of the Autism Diagnostic Observation Schedule (ADOS). The usefulness of the schedule in the differentiation between children with autism and children with a severe specific receptive language disorder is examined. METHOD: Eight boys with early infantile autism and eight age- and IQ-matched boys with a specific receptive language disorder were examined with the ADOS. The reliability of the instrument was assessed using the ratings of eight pairs of raters. The agreement between diagnostic classification based on the ADOS ICD-10 algorithm and the independent clinical psychiatric diagnosis of two experts was used as the measure of validity. RESULTS: The reliability of the different ADOS items proved to be good among experienced raters. Various ADOS items clearly discriminate both groups. Using the ADOS ICD-10 algorithm, the clinical diagnosis of infantile autism could be confirmed for five of the eight children in this group. None of the children with the clinical diagnosis of a receptive language disorder was identified as autistic according to the algorithm. CONCLUSIONS: In the hands of experienced raters the ADOS is a reliable diagnostic instrument. It can support the differentiation between autism and specific receptive language disorder, but additional parent information is needed to confirm the diagnosis.

Auditory Perceptual Disorders↗

PubMed2004

Support vector machine classification on the web.

The support vector machine (SVM) learning algorithm has been widely applied in bioinformatics. We have developed a simple web interface to our implementation of the SVM algorithm, called Gist. This interface allows novice or occasional users to apply a sophisticated machine learning algorithm easily to their data. More advanced users can download the software and source code for local installation. The availability of these tools will permit more widespread application of this powerful learning algorithm in bioinformatics.

Algorithms↗

PubMed1999

Integrating disease management and wound care critical pathways in home care.

This article discusses the need for an integration of the concepts of disease management and critical pathways as a foundation of a healthcare delivery system. The steps in the process for development, implementation, and evaluation of a wound care critical pathway are reviewed and variance classifications are defined. Co-pathways and algorithms are presented as methodologies for dealing with variances. A template of a wound care critical pathway that has been developed for use in the home care setting is included.

Algorithms↗

PubMed1993

Clinical classification as a predictor of therapeutic outcome after cervical epidural steroid injection.

A retrospective analysis was done on 100 patients who had received cervical epidural steroid injections for neck pain and cervical radiculopathy to identify the predictors of outcome after such treatment. Potential predictors of outcome were assessed individually and then simultaneously with a multiple-regression model. Patients with radicular symptoms and signs had the best pain relief in contradistinction to those with axial (neck) pain. A clinical classification model predicting the outcome and an algorithm for the use of such injections in the treatment of cervical radiculopathy were developed.

Adult↗

PubMed2004

Impact of headache on quality of life in a general population survey in France (GRIM2000 Study).

OBJECTIVES: The objectives of this study were to determine the impact of headache on health-related quality of life in a nationwide sample of the French general population using a disease-specific measure, the Qualité de Vie et Migraine (QVM), to compare quality of life in subjects reporting different headache to types, and to evaluate the relationship between quality of life and severity, frequency, associated disability, and treatment responsiveness of headaches. METHODS: The QVM questionnaire was included within a large epidemiological survey of 1486 headache sufferers. Diagnosis was assigned retrospectively using an algorithm based on the International Headache Society classification. Headache severity was assessed with the MIGSEV scale and disability with the MIDAS scale. RESULTS: The mean global QVM score in the sample was 80.2. Quality of life was poorer in subjects with chronic daily headache (QVM score: 66.2) than in those with migraine (QVM score: 76.7), while those with other forms of episodic headache had the best quality of life (QVM score: 91.7). Quality-of-life scores were correlated with frequency, severity, disability, and treatment resistance of headaches (P <.001). CONCLUSION: The QVM scale is a sensitive tool to measure health-related quality of life in headache sufferers in the general population.

Adolescent↗

PubMed2002

Prediction of response to hormonal treatment in metastatic breast cancer.

Prediction of outcome and individualization of therapeutic strategies are challenging problems in oncology. Predictive parameters for response to hormonal treatment include the expression of hormone receptor, the extent and location of metastatic spread, disease-free interval, patient age, response to prior hormonal therapy, grading, and more recently, some molecular markers like the expression of HER-2/neu. The use of conventional statistics for prediction of response to hormonal treatment is limited by non-linearities and complex interactions between predictive factors. Modern computational mathematical models like artificial neural networks, entropy-based inductive algorithms or chi(2) interaction detection algorithms can describe these interactions and generate classification models and decision structures. They can be used to predict the clinical outcome for individual patients. In contrast to conventional methods, the level of confidence for the predictions can reach 90% and more. This might be an important step towards further individualization of therapeutic strategies.

Antineoplastic Agents, Hormonal↗