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PubMed2006

Remission from pathological gambling among Hispanics and Native Americans.

This community survey studied remission from pathological gambling (PG) among American Indian (AI) and Hispanic American (HA) veterans. Remission was defined as having a lifetime diagnosis of PG, but no gambling symptoms in the last year. Sample consisted of 1624 AI and Hispanic veterans. Instruments included demographic data, the computer-based algorithmic Quick Diagnostic Interview Schedule Symptom, and three symptom checklists, one each for substance related problems (MAST/AD), anxiety and depressive symptoms (BSI-57), and combat-related post-trauma symptoms (PCL/M). Remission was associated with absence of a current Axis 1 diagnosis, especially absence of a current post-traumatic stress disorder.

Adult↗
PubMed2006

Advances in the diagnosis of venous thromboembolism.

This review summarizes recent information about the diagnosis of deep venous thrombosis (DVT) and pulmonary embolism (PE) using noninvasive imaging tests, clinical assessment, and D-dimer assays, and describes how these tests can be employed in diagnostic testing algorithms for the investigation of patients with suspected DVT and PE. The clinical diagnosis of deep venous thrombosis is unreliable, but clinical prediction rules based on signs and symptoms do facilitate the categorization of patients into high, low, or medium risk categories. High sensitivity D-dimer assays further help in excluding cases but do not help in ruling in venous thromboembolism. D-dimer assays and clinical prediction rules also help in the diagnosis of pulmonary embolism. These assessments, along with objective imaging studies such as compression ultrasonography for DVT or computerized tomographic pulmonary angiograms for PE can be used in a systematic way to reliably rule in or exclude venous thromboembolism.

Fibrin Fibrinogen Degradation Products↗
PubMed1990

Diagnosis of venous thrombosis and pulmonary embolism.

Venous thrombosis and pulmonary embolism are closely related disorders. As many as 70 to 80% of patients with pulmonary embolism have associated proximal deep venous thrombosis. The clinical diagnosis alone of both venous thrombosis and pulmonary embolism is inaccurate because of the insensitivity and nonspecificity of findings, a problem that also occurs with a variety of other disorders. Invasive, objective tests are still the reference standard, but they are not always easy to perform, they cannot be used for a considerable number of very ill patients, and they create some patient discomfort. There is an increasing trend toward using noninvasive methods, either alone or in combination. These methods entail less risk, can be performed more quickly and conveniently, and are usually more cost-effective. Practical approaches to diagnosing venous thrombosis and pulmonary embolism in the clinical setting are discussed.

Algorithms↗
PubMed1993

Minimizing the risk of inappropriately administering thrombolytic therapy (Thrombolysis and Angioplasty in Myocardial Infarction [TAMI] study group).

Despite the proven benefits of thrombolytic therapy in acute myocardial infarction, concern for its complications, especially in patients misdiagnosed with myocardial infarction, has led to hesitancy in its use. Historical, clinical and electrocardiographic criteria were developed for enrolling patients with suspected acute myocardial infarction into thrombolytic trials by noncardiovascular specialists. The incidence of misdiagnosis of myocardial infarction and the clinical outcomes when these criteria were used were evaluated for 1,387 consecutive patients given thrombolytic therapy. Twenty-five community hospitals and 7 interventional centers were the sites of enrollment. Most patients (63%) were enrolled from community hospitals. Criteria for thrombolytic therapy included: symptoms of acute myocardial infarction < 6 hours but > 20 minutes, and not relieved by nitroglycerin; and ST-segment elevation > or = 1 mm in 2 contiguous leads or ST-segment depression of posterior myocardial infarction. Exclusion criteria reflecting increased risk of bleeding were used. A final diagnosis of myocardial infarction was based on creatinine kinase-MB, electrocardiographic and ventriculographic evaluation. Acute myocardial infarction was misdiagnosed in 20 patients (1.4%; 95% confidence interval 0.8-2.0%). These patients were demographically similar to those with acute myocardial infarction. All misdiagnosed patients survived; no significant adverse events occurred. Thus, in several clinical settings, a simple algorithm with specific criteria was used for diagnosing acute myocardial infarction and administering thrombolytic therapy. The inclusion criteria used in this study led to a low rate of misdiagnosis.

Algorithms↗
PubMedDate not supplied

Interpretation of microscopic image analysis of cell nuclei.

This study shows that microscopic image analyses of nuclear DNA have common characteristics among fixation methods and tissue types. We find that microscopic imaging measurements require both nuclear area and DNA concentration to properly convey diagnostic information. Algorithms are developed which enable infiltrating lymphocytes to act as internal DNA controls for each sample. The DNA content and patterns measured by microscopic imaging were found to be related to patient survival and to cytologic diagnosis.

Algorithms↗
PubMed2006

Advances in diagnosis of adolescent substance abuse.

Screening and diagnosis of adolescent substance abuse is a challenging but achievable component of primary care practice. Successful integration of these procedures into office visits requires an understanding of prevalence, risk factors, and strategies for prevention and treatment. The authors provide a synopsis of recent advances and important issues in this area and propose a stepwise, evidence-based approach to evaluation of substance abuse in adolescents.

Adolescent↗
PubMed2004

A hierarchical parametric algorithm for deformable multimodal image registration.

Image fusion is of utmost importance for many applications in image analysis. Particularly in medical imaging, images of different modalities are necessary because they provide complementary information that must be merged for an optimal use. The fusion of these images, which can be achieved through a registration process, makes it possible to superimpose all available information on the same frame. In many cases, a rigid transformation is sufficient to align correctly the images. However, there are cases where a non-rigid transformation is needed: geometrical distortions present in one image, non-rigid motion, etc. The purpose of this paper is to propose a generic method to account for these deformations in case of multimodal images. We have applied the algorithm in the particular context of 3D medical images and present results on simulated and real data.

Algorithms↗
PubMed2006

Comparison of maximum entropy and filtered back-projection methods to reconstruct rapid-scan EPR images.

Reconstruction of two-dimensional images by filtered back-projection (FBP) and by the maximum entropy method (MEM) was compared for spectral-spatial EPR images with differing signal-to-noise ratios. Experimental projections were recorded using direct-detected rapid scans in the presence of a series of magnetic field gradients. The slow-scan absorption lineshapes were calculated by Fourier deconvolution. A Hamming filter was used in conjunction with FBP, but not for MEM. Imperfections in real experimental data, as well as random noise, contribute to discrepancies between the reconstructed image and experimental projections, which may make it impossible to achieve the customary MEM criterion for convergence. The Cambridge MEM algorithm, with allowance for imperfections in experimental data, produced images with more linear intensity scales and more accurate linewidths for weak signals than was obtained with another MEM method. The more effective elimination of noise in baseline regions by MEM made it possible to detect weak trityl (13)C trityl hyperfine lines that could not be distinguished from noise in images reconstructed by FBP. Another advantage of MEM is that projections do not need to be equally spaced. FBP has the advantages that computational time is less, the amplitude scale is linear, and there is less noise superimposed on peaks in images. It is useful to reconstruct images by both methods and compare results. Our observations indicate that FBP works well when the number of projections is large enough that the star effect is negligible. When there is a smaller number of projections, projections are unequally spaced, and/or signal-to-noise is lower MEM is advantageous.

Algorithms↗
PubMed2006

Clinical aspects of obesity in the gynecological endocrinologicaly practice.

Obesity is epidemic of 21st century, its visceral form is associated with increased risk for type 2 diabetes, cardiovascular disease, hypertension and increased mortality due to consequences of the disease. This type of obesity is a common diagnostic and therapeutic problem in gynecological practice. This especially concerns polycystic ovary disease, in which this type of obesity with its metabolic consequences is one of the important factors in etiology and additionally may lead to remote metabolic and cardiovascular problems. Another group of women in which this type of obesity plays an important role are climacteric women in whom redistribution of adipose tissue with increase in visceral fat deposit occurs. On the basis of current viewpoints and own experiences, the authors propose a diagnostic-therapeutic algorithm in women with visceral obesity and polycystic ovary disease or climacteric period. In case with cardiovascular risk factors (waist circumference over than 80cm, serum triglycerides over 1.7mmol/l, HDL cholesterol lower than 1.0mmol/l, blood pressure over 130/85mmHg and fast serum glucose levels over 100mg/dl) the therapeutic model focuses on the recognize risk factors. It must be considered that diet and physical activity play a very important role in the therapy.

Algorithms↗
PubMed2004

A graphical user interface for automatic image registration software designed for radiotherapy treatment planning.

Medical imaging forms a vital component of radiotherapy treatment planning and its evaluation. The integration of the useful data obtained from multiple imaging modalities for radiotherapy planning is achieved by image registration softwares. In radiotherapy planning systems, normally the computed tomography (CT) slices are kept as a standard upon which other modality images (magnetic resonance imaging [MRI], single photon emission computed tomography [SPECT], positron emission tomography [PET], etc.) are aligned--automatically or interactively. Following validation of successful registration, they are resampled and reformatted, as per the requirements. This paper defines the minimum requirements of automatic image registration software for 3-dimensional (3D) radiotherapy planning and describes the implementation of a suitable graphical user interface developed in Visual Basic (version 5). The automatic image registration (AIR) routines freely available from Dr. Roger P. Woods, UCLA, (USA) were used in this software. This software could be easily implemented and was easy to use for image processing suitable for radiotherapy planning systems.

Algorithms↗
PubMed2004

Integrating watersheds and critical point analysis for object detection in discrete 2D images.

This paper presents an improved method for the detection of "significant" low-level objects in medical images. The method overcomes topological problems where multiple redundant saddle points are detected in digital images. Information derived from watershed regions is used to select and refine saddle points in the discrete domain and to construct the watersheds and watercourses (ridges and valleys). We also demonstrate an improved method of pruning the tessellation by which to define low level objects in zero order images. The algorithm was applied on a set of medical images with promising results. Evaluation was based on theoretical analysis and human observer experiments.

Algorithms↗
PubMed2005

Detection and analysis of statistical differences in anatomical shape.

We present a computational framework for image-based analysis and interpretation of statistical differences in anatomical shape between populations. Applications of such analysis include understanding developmental and anatomical aspects of disorders when comparing patients versus normal controls, studying morphological changes caused by aging, or even differences in normal anatomy, for example, differences between genders. Once a quantitative description of organ shape is extracted from input images, the problem of identifying differences between the two groups can be reduced to one of the classical questions in machine learning of constructing a classifier function for assigning new examples to one of the two groups while making as few misclassifications as possible. The resulting classifier must be interpreted in terms of shape differences between the two groups back in the image domain. We demonstrate a novel approach to such interpretation that allows us to argue about the identified shape differences in anatomically meaningful terms of organ deformation. Given a classifier function in the feature space, we derive a deformation that corresponds to the differences between the two classes while ignoring shape variability within each class. Based on this approach, we present a system for statistical shape analysis using distance transforms for shape representation and the support vector machines learning algorithm for the optimal classifier estimation and demonstrate it on artificially generated data sets, as well as real medical studies.

Algorithms↗
PubMed2005

The use of routine laboratory data to predict in-hospital death in medical admissions.

The ability to predict clinical outcomes in the early phase of a patient's hospital admission could facilitate the optimal use of resources, might allow focused surveillance of high-risk patients and might permit early therapy. We investigated the hypothesis that the risk of in-hospital death of general medical patients can be modelled using a small number of commonly used laboratory and administrative items available within the first few hours of hospital admission. Matched administrative and laboratory data from 9497 adult hospital discharges, with a hospital discharge specialty of general medicine, were divided into two subsets. The dataset was split into a single development set, Q(1) (n=2257), and three validation sets, Q(2), Q(3) and Q(4) (n(1)=2335, n(2)=2361, n(3)=2544). Hospital outcome (survival/non-survival) was obtained for all discharges. An outcome model was constructed from binary logistic regression of the development set data. The goodness-of-fit of the model for the validation sets was tested using receiver-operating characteristics curves (c-index) and Hosmer-Lemeshow statistics. Application of the model to the validation sets produced c-indices of 0.779 (Q(2)), 0.764 (Q(3)) and 0.757 (Q(4)), respectively, indicating good discrimination. Hosmer-Lemeshow analysis gave chi(2)=9.43 (Q(2)), chi(2)=7.39 (Q(3)) and chi(2)=8.00 (Q(4)) (p-values of 0.307, 0.495 and 0.433) for 8 degrees of freedom, indicating good calibration. The finding that the risk of hospital death can be predicted with routinely available data very early on after hospital admission has several potential uses. It raises the possibility that the surveillance and treatment of patients might be categorised by risk assessment means. Such a system might also be used to assess clinical performance, to evaluate the benefits of introducing acute care interventions or to investigate differences between acute care systems.

Adult↗
PubMed2004

Normalizing projection images: a study of image normalizing procedures for single particle three-dimensional electron microscopy.

In the process of three-dimensional reconstruction of single particle biological macromolecules several hundreds, or thousands, of projection images are taken from tens or hundreds of independently digitized micrographs. These different micrographs show differences in the background grey level and particle contrast and, therefore, have to be normalized by scaling their pixel values before entering the reconstruction process. In this work several normalization procedures are studied using a statistical comparison framework. We finally show that the use of the different normalization methods affects the reconstruction quality, providing guidance on the choice of normalization procedures.

Algorithms↗
PubMed2003

Brugada syndrome and "Brugada sign": clinical spectrum with a guide for the clinician.

BACKGROUND: Patients with the manifest Brugada syndrome have an inordinate risk of sudden death and are candidates for implantation of a defibrillator. The Brugada type electrocardiogram (ECG) abnormality (the "Brugada sign"), however, is known to be associated with a wide range of conditions, many of which may not pose such a threat. Clinicians need guidance in choosing a rational approach for the evaluation and treatment of patients with a finding of the Brugada sign. METHODS: A systematic literature search was performed to identify publications on the Brugada syndrome and the Brugada-type ECG abnormality, with special emphasis on analyzing outcomes data. In addition, the ECG database of our institution was reviewed for tracings consistent with the Brugada sign, and, when possible, clinical correlations were made. RESULTS: Patients with the Brugada sign and a family history of sudden death or a personal history of syncope are at a high risk of sudden death and therefore should be strongly considered for implantation of a defibrillator. In patients who are hospitalized and critically ill, the Brugada sign is frequently the result of severe hyperkalemia, drug toxicity, or right ventricular injury. In most individuals with no symptoms and without a family history of sudden death, the Brugada sign is likely a normal variant. CONCLUSIONS: Most patients with the Brugada sign can be risk-stratified with simple clinical tools. Specific testing for the Brugada syndrome should be reserved for questionable cases and for the research setting. A provisional diagnostic-therapeutic algorithm is offered as a means of assisting the clinician in the evaluation and treatment of patients with the Brugada sign.

Algorithms↗
PubMed2000

Automated segmentation of multiple sclerosis lesions in multispectral MR imaging using fuzzy clustering.

A method is presented for fully automated detection of Multiple Sclerosis (MS) lesions in multispectral magnetic resonance (MR) imaging. Based on the Fuzzy C-Means (FCM) algorithm, the method starts with a segmentation of an MR image to extract an external CSF/lesions mask, preceded by a local image contrast enhancement procedure. This binary mask is then superimposed on the corresponding data set yielding an image containing only CSF structures and lesions. The FCM is then reapplied to this masked image to obtain a mask of lesions and some undesired substructures which are removed using anatomical knowledge. Any lesion size found to be less than an input bound is eliminated from consideration. Results are presented for test runs of the method on 10 patients. Finally, the potential of the method as well as its limitations are discussed.

Algorithms↗