A survey of knowledge of family planning (FP) methods among Kenyan medical doctors: secondary data analysis.
Explore the source record for details and available documents.
Africa↗
SEARCH · PubMed Health
Results for “data analysis”
Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
A multiparametric data analysis showing the potential of localized proton MR spectroscopy of the brain in the metabolic characterization of neurological diseases.
We conducted an extended clinical evaluation of localized proton magnetic resonance spectroscopy (MRS) of the brain, performed on various brain diseases using short stimulated echo times. Pathologies studied were mainly multiple sclerosis, stroke, leukoaraiosis, AIDS-related leukoencephalopathies and glial tumors. Other miscellaneous pathologies were also studied. Magnetic resonance examination of the brain was conducted on a Siemens Magnetom SP63 (equipped with a 1.5 T magnet). Localized proton MRS was performed on a routine basis immediately after imaging, using the STEAM (stimulated echo acquisition mode) with a short echo time (20 ms) combined with a CHESS (chemical shift selective excitation) sequence. One or two VOI (8 ml) were examined. Data on 125 spectra were processed by principal component analysis (PCA) and conventional variance analysis. The following metabolite resonances were studied: inositol-glycine, taurine-scyllo-inositol, choline derivatives, phosphocreatine-creatine, aspartate, glutamine glutamate, N-acetylaspartate, acetate and lactate. PCA demonstrates that the different metabolic variables are independent. The analysis of groups of spectra clearly demonstrates that the metabolic profiles detected by localized MRS in various pathologies (i) differ significantly from controls, and (ii) allow a metabolic discrimination between groups of pathologies. Results of PCA are confirmed by variance analysis. Strokes are characterized by an increase in lactate concentration and leukoaraiosis by a decrease in inositol-glycine resonance. AIDS-related leukodystrophies are characterized by increases in lactate and choline concentrations. Reduction in N-acetylaspartate which is observed in most pathologies is not significant in the small lesions of white matter. Lactate has often been found in MS plaques, but no variation in the choline/phosphocreatine ratio was observed. GABA was tentatively assigned in the spectrum of a patient with epilepsy under sodium valproate treatment. This study illustrates the clinical feasibility of the technique, the value of a multiparametric data analysis in the definition of the pertinent variables characterizing the metabolic impairment, and the impact of localized proton MR spectroscopy of the brain in the assessment of cerebral suffering.
AIDS Dementia Complex↗
Computerized data analysis in cellular immunology. Enhancement and suppression of immune responses.
Data obtained from assays for the evaluation of helper or suppressor activity are analyzed by statistical techniques that increase the accuracy and amount of information. The analysis is performed by a set of simple and ready to use computer programs which do not require statistical expertise and are available on request.
Animals↗
Design and analysis of accelerated degradation tests for the stability of biological standards II. A flexible computer program for data analysis.
The accelerated degradation test is commonly used to predict the stability of a biological standard during long-term storage at low temperature. A flexible computer program is described which has been written to analyse degradation test results by the method of maximum likelihood. In addition to predicting the degradation rate at low temperature, the program furnishes estimates of statistical precision and it carried out a test of goodness of fit of the data to the assumed Arrhenius equation model.
Biological Products↗
Biological component of the NIMH clinical research branch collaborative program on the psychobiology of depression: II. Methodology and data analysis.
A preceding paper has reviewed the history, background, and rationale for this collaborative effort exploring the biologic basis of the affective disorders. This paper details the "flow" of a subject through the experimental protocol, the instrumentation used to obtain the clinical and behavioural data, and the biologic methodologies employed in the analysis of the body fluids. Data management and analysis techniques developed for this study are also examined.
Adrenocorticotropic Hormone↗
A survey of attitude of Kenyan medical doctors on family planning (FP): secondary data analysis.
Explore the source record for details and available documents.
Africa↗
Microcomputer-assisted multivariate survival data analysis using Cox's proportional hazards regression model.
We describe a microcomputer program (COXSURV) for proportional hazards multiple regression analysis of survival and other failure-time data generated in clinical trials and in retrospective clinical epidemiology studies. COXSURV is menu-driven and has powerful variable factoring and data exploratory capabilities for multivariate modeling. A batch mode allows automatic uni- or multivariate analyses for confounder summarization. Model selection for predictive purposes is possible through a step-up algorithm. The partial likelihood method used in the program allows the use of either discrete or continuous time scales by treating tied uncensored observations by either the exact method or by a robust approximation method. The program calculates most standard model fitting statistics for either overall or stratified analyses and uses data layout files compatible with those of other related epidemiologic analysis software.
Algorithms↗
Graphical exploratory data analysis of RNA secondary structure dynamics predicted by the massively parallel genetic algorithm.
Studies indicate that RNA may enter intermediate and multiple conformational states, which may impact gene expression and molecular function. It is known that the biologically functional states of RNA molecules may not correspond to their minimum energy conformations, that kinetic barriers may trap the molecule in a local minimum, that folding often occurs during transcription, and that cases exist in which a molecule will transition between one or more functional conformations. Thus, methods for simulating the folding pathway and dynamic behavior of an RNA molecule are important for the prediction of RNA structure and its associated functions. We have developed several data mining techniques guided by interactive visualization tools associated with our massively parallel genetic algorithm for RNA/DNA secondary structure prediction, MPGAfold, and StructureLab analysis workbench. Most of the methods and tools are also applicable to dynamic programming algorithm (DPA) folding data analysis. When applied to MPGAfold results these methodologies are used to determine the significant intermediate and final structures associated with co-transcriptional and full length RNA folding. Since the genetic algorithm is essentially stochastic, multiple runs are required to develop a consensus understanding of an RNA structure. The interactive visualizations facilitate interpretation of results from sequential or full length individual MPGAfold runs, final results of multiple folding runs, including multiple population sizes, and the results from multiple RNA sequences of one family. This paper describes several of these techniques and shows how they are used to help solve this highly combinatoric problem.
Algorithms↗
Topographical CT-data analysis of the human orbital floor.
The aim of this study was to evaluate the topographical anatomy of the human orbital floor for the production of prefabricated implants on the basis of computer tomography data. A database of 279 CT scans of Caucasian patients without traumatic deformation of the midface was analysed. 3D-image segmentation of the midfacial skeleton was performed using a computer-assisted protocol. A virtual plane (50 x 50 mm (2)) was constructed using defined landmarks above the orbital floor. An automated procedure was used to measure the distance between the orbital floor and the constructed plane at 400 distinct points. A mathematical algorithm was used to analyse the data, and to calculate a map of the orbital floor. Statistical analysis of the data revealed that orbital floor topography could be classified as distinct clusters. There were 12 variations of orbital floor anatomy: three unique patterns of the orbital floor for the right orbit and three corresponding patterns for the left side, all of which varied between the sexes. The 12 patterns were constructed with a statistical confidence interval of 1.36+/-0.6mm.
Adult↗
Categorical data analysis.
This chapter reviews recent developments in the analysis of categorical and contingency-table data. The first portion examines developments in model testing and selection. The second portion examines work on models for the structure of dependence. These include log-linear parameter models, models for latent classes, models for missing observations, numerical-scale-based association and correlation models (such as correspondence analysis), the treatment of ordered categories, and models for marginal distributions.
Journal Article↗
GIS, geostatistics, metadata banking, and tree-based models for data analysis and mapping in environmental monitoring and epidemiology.
By the example of environmental monitoring, some applications of geographic information systems (GIS), geostatistics, metadata banking, and Classification and Regression Trees (CART) are presented. These tools are recommended for mapping statistically estimated hot spots of vectors and pathogens. GIS were introduced as tools for spatially modelling the real world. The modelling can be done by mapping objects according to the spatial information content of data. Additionally, this can be supported by geostatistical and multivariate statistical modelling. This is demonstrated by the example of modelling marine habitats of benthic communities and of terrestrial ecoregions. Such ecoregionalisations may be used to predict phenomena based on the statistical relation between measurements of an interesting phenomenon such as, e.g., the incidence of medically relevant species and correlated characteristics of the ecoregions. The combination of meteorological data and data on plant phenology can enhance the spatial resolution of the information on climate change. To this end, meteorological and phenological data have to be correlated. To enable this, both data sets which are from disparate monitoring networks have to be spatially connected by means of geostatistical estimation. This is demonstrated by the example of transformation of site-specific data on plant phenology into surface data. The analysis allows for spatial comparison of the phenology during the two periods 1961-1990 and 1991-2002 covering whole Germany. The changes in both plant phenology and air temperature were proved to be statistically significant. Thus, they can be combined by GIS overlay technique to enhance the spatial resolution of the information on the climate change and use them for the prediction of vector incidences at the regional scale. The localisation of such risk hot spots can be done by geometrically merging surface data on promoting factors. This is demonstrated by the example of the transfer of heavy metals through soils. The predicted hot spots of heavy metal transfer can be validated empirically by measurement data which can be inquired by a metadata base linked with a geographic information system. A corresponding strategy for the detection of vector hot spots in medical epidemiology is recommended. Data on incidences and habitats of the Anophelinae in the marsh regions of Lower Saxony (Germany) were used to calculate a habitat model by CART, which together with climate data and data on ecoregions can be further used for the prediction of habitats of medically relevant vector species. In the future, this approach should be supported by an internet-based information system consisting of three components: metadata questionnaire, metadata base, and GIS to link metadata, surface data, and measurement data on incidences and habitats of medically relevant species and related data on climate, phenology, and ecoregional characteristic conditions.
Databases, Factual↗
AmpSeqR: an R package for amplicon deep sequencing data analysis.
Amplicon sequencing (AmpSeq) is a methodology that targets specific genomic regions of interest for polymerase chain reaction (PCR) amplification so that they can be sequenced to a high depth of coverage. Amplicons are typically chosen to be highly polymorphic, usually with several highly informative, high frequency single nucleotide polymorphisms (SNPs) segregating in an amplicon of 100-200 base pair (bp). This allows high sensitivity detection and quantification of the frequency of each sequence within each sample making it suitable for applications such as low frequency somatic mosaicism detection or minor clone detection in mixed samples. AmpSeq is being increasingly applied to both biological and medical studies, in applications such as cancer, infectious diseases and brain mosaicism studies. Current bioinformatics pipelines for AmpSeq data processing lack downstream analysis, have difficulty distinguishing between true sequences and PCR sequencing errors and artifacts, and often require bioinformatic expertise. We present a new R package: AmpSeqR, designed for the processing of deep short-read amplicon sequencing data, with a focus on infectious diseases. The pipeline integrates several existing R packages combining them with newly developed functions to perform optimal filtering of reads to remove noise and improve the accuracy of the detected sequences data, permitting detection of very low frequency clones in mixed samples. The package provides useful functions including data pre-processing, amplicon sequence variants (ASVs) estimation, data post-processing, data visualization, and automatically generates a comprehensive Rmarkdown report that contains all essential results facilitating easy inclusion into reports and publications. AmpSeqR is publicly available at https://github.com/bahlolab/AmpSeqR.
High-Throughput Nucleotide Sequencing↗
Lower limb alignment and foot angle are related to stance phase knee adduction in normal subjects: a critical analysis of the reliability of gait analysis data.
Anatomic and mechanical factors that affect loading in the knee joint can contribute to pathologic changes seen at the knee in degenerative joint disease and should be considered in treatment planning. The objectives of this study were to quantify the relationships between the alignment of the bones of the lower extremity, foot progression angle, and knee adduction moment, and to determine the reliability of our gait measurements. Gait analysis and complete radiographic evaluation of the lower extremity were performed on 11 healthy subjects. The gait measurements were recorded with an optoelectronic digitizer and a multi-component force plate. The subjects who had radiographic measurements indicative of varus alignment of the lower extremity had statistically higher peaks in knee adduction moment in early stance. Conversely, those with valgus alignment of the lower extremity had statistically lower peaks in knee adduction moment in early stance. The subjects who had a large toe-out angle and low ankle inversion moment peaks in late stance had significantly lower peaks in knee adduction moment in late stance. These significant (low to moderate) correlations suggest that the limbs with more valgus alignment and those with a toe-out gait exhibited a reduced peak adduction moment at the knee. To verify the reproducibility of the data, gait analysis testing was performed on each lower limb on 2 separate days for each subject. Analysis of variance showed that there was no significant difference between test limbs or test days for each subject. Our results suggest that the alignment of the lower limb and the foot progression angle, which can be readily measured in a clinical setting, can serve as predictors of knee joint loading in healthy individuals. These findings may have important implications for both surgical and nonsurgical treatment of abnormalities of the knee joint.
Adult↗
[Exploratory data analysis and its application to birth, marriage, and mortality rates in the provinces of Spain].
Explore the source record for details and available documents.
Demography↗
Computer-based monitoring and data analysis in anaesthesia and intensive care.
A computer with a software package for physiological monitoring at the bedside has been set up, modified and used in a Department of Anaesthesia and Intensive Care over the last three and a half years. Many difficulties have been experienced in implementing a useful computer-based program for monitoring physiological data. The cost of further development to overcome these difficulties could not be justified, and demands for computer time to allow storage and analysis fo other data was increasing. A decision was therefore made to eliminate the monitoring role of the computer, and it is now used for storage and analysis of administrative and clinical data from the Intensive Care Unit, Operating Theatres and Pain Management Unit.
Anesthesiology↗
A note on competing risks in survival data analysis.
Survival analysis encompasses investigation of time to event data. In most clinical studies, estimating the cumulative incidence function (or the probability of experiencing an event by a given time) is of primary interest. When the data consist of patients who experience an event and censored individuals, a nonparametric estimate of the cumulative incidence can be obtained using the Kaplan-Meier method. Under this approach, the censoring mechanism is assumed to be noninformative. In other words, the survival time of an individual (or the time at which a subject experiences an event) is assumed to be independent of a mechanism that would cause the patient to be censored. Often times, a patient may experience an event other than the one of interest which alters the probability of experiencing the event of interest. Such events are known as competing risk events. In this setting, it would often be of interest to calculate the cumulative incidence of a specific event of interest. Any subject who does not experience the event of interest can be treated as censored. However, a patient experiencing a competing risk event is censored in an informative manner. Hence, the Kaplan-Meier estimation procedure may not be directly applicable. The cumulative incidence function for an event of interest must be calculated by appropriately accounting for the presence of competing risk events. In this paper, we illustrate nonparametric estimation of the cumulative incidence function for an event of interest in the presence of competing risk events using two published data sets. We compare the resulting estimates with those obtained using the Kaplan-Meier approach to demonstrate the importance of appropriately estimating the cumulative incidence of an event of interest in the presence of competing risk events.
Humans↗
Biochemical characterization of rat intestine development using high-resolution magic-angle-spinning 1H NMR spectroscopy and multivariate data analysis.
We report details of metabolic profiles for small intestinal samples obtained using high-resolution magic-angle-spinning (HRMAS) (1)H NMR spectroscopy. Intact samples of jejunum and ileum from male Long Evans rats were analyzed on a 600 MHz spectrometer using standard one and two-dimensional (1)H NMR spectroscopic pulse sequences. The metabolic profiles of ileum and jejunum predominantly comprised a number of amino acids, lipids, glycerophosphocholine (GPC), choline, creatine, and ethanol, a number of carboxylic acids including acetate and lactate, and nucleoside bases including cytosine, isocytosine, and uracil. Principal component analysis (PCA) was applied to these NMR data to characterize the biochemical differences between jejunum and ileum tissues. Compared with ileum, jejunum contained higher levels of lipids, GPC, choline, lactate and creatinine, but lower levels of amino acids and acetate. In addition, the age dependence of the biochemical composition of intestinal tissues from young rats (15, 36 days and 3-4 months old) was studied. In general, levels of lipids, lactate, taurine and creatinine were positively correlated with age while amino acids and GPC decreased in the older age group. This study will provide a metabolic reference for further studies assessing the metabolic consequences of nutrition, stress and gut microbiota on intestinal composition.
Age Factors↗
Convolution: a method for data analysis in perifusion systems.
Considerable interest has developed in defining how imposed stimuli effect dynamic changes in cellular metabolism. We have developed a miniature perifusion system that can reveal alterations in extracellular protons within seconds after application of metabolic perturbants. This perifusion system contains two pH sensors: one before the cells records changes between medium and test solutions, and one, located just past the cells, records these alterations plus cellular modifications. Because distortion occurs as chemicals pass through perifusion systems, the shape of pH changes induced by switching from medium to test solutions is different at each electrode. This study describes and validates convolution to correct this distortion. Data from HeLa cells exposed to the metabolic uncoupler of oxidative phosphorylation carbonyl cyanide m-chlorophenyl hydrazone have been analyzed with convolution. Cellular response to oxidative phosphorylation removal is comprised of multiple components, is consistent with a rapid uncoupling, and is followed by cellular adaptation. Therefore convolutional analysis can provide an important adjunct to the analysis of data acquired by perifusion and can provide new insights into cellular responsiveness and metabolism.
Carbonyl Cyanide m-Chlorophenyl Hydrazone↗