995 resultados para Classification tests
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OBJECTIVES: The aim of this study was to evaluate new electrocardiographic (ECG) criteria for discriminating between incomplete right bundle branch block (RBBB) and the Brugada types 2 and 3 ECG patterns. BACKGROUND: Brugada syndrome can manifest as either type 2 or type 3 pattern. The latter should be distinguished from incomplete RBBB, present in 3% of the population. METHODS: Thirty-eight patients with either type 2 or type 3 Brugada pattern that were referred for an antiarrhythmic drug challenge (AAD) were included. Before AAD, 2 angles were measured from ECG leads V(1) and/or V(2) showing incomplete RBBB: 1) α, the angle between a vertical line and the downslope of the r'-wave, and 2) β, the angle between the upslope of the S-wave and the downslope of the r'-wave. Baseline angle values, alone or combined with QRS duration, were compared between patients with negative and positive results on AAD. Receiver-operating characteristic curves were constructed to identify optimal discriminative cutoff values. RESULTS: The mean β angle was significantly smaller in the 14 patients with negative results on AAD compared to the 24 patients with positive results on AAD (36 ± 20° vs. 62 ± 20°, p < 0.01). Its optimal cutoff value was 58°, which yielded a positive predictive value of 73% and a negative predictive value of 87% for conversion to type 1 pattern on AAD; α was slightly less sensitive and specific compared with β. When the angles were combined with QRS duration, it tended to improve discrimination. CONCLUSIONS: In patients with suspected Brugada syndrome, simple ECG criteria can enable discrimination between incomplete RBBB and types 2 and 3 Brugada patterns.
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Allergic conjunctivitis (AC) is an inflammatory disease of the conjunctiva caused mainly by an IgE-mediated mechanism. It is the most common type of ocular allergy. Despite being the most benign form of conjunctivitis, AC has a considerable effect on patient quality of life, reduces work productivity, and increases health care costs. No consensus has been reached on its classification, diagnosis, or treatment. Consequently, the literature provides little information on its natural history, epidemiological data are scarce, and it is often difficult to ascertain its true morbidity. The main objective of the Consensus Document on Allergic Conjunctivitis (Documento dE Consenso sobre Conjuntivitis Alérgica [DECA]), which was drafted by an expert panel from the Spanish Society of Allergology and Spanish Society of Ophthalmology, was to reach agreement on basic criteria that could prove useful for both specialists and primary care physicians and facilitate the diagnosis, classification, and treatment of AC. This document is the first of its kind to describe and analyze aspects of AC that could make it possible to control symptoms.
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BACKGROUND: Estimates of drug resistance incidence to modern first-line combination antiretroviral therapies against human immunodeficiency virus (HIV) type 1 are complicated by limited availability of genotypic drug resistance tests (GRTs) and uncertain timing of resistance emergence. METHODS: Five first-line combinations were studied (all paired with lamivudine or emtricitabine): efavirenz (EFV) plus zidovudine (AZT) (n = 524); EFV plus tenofovir (TDF) (n = 615); lopinavir (LPV) plus AZT (n = 573); LPV plus TDF (n = 301); and ritonavir-boosted atazanavir (ATZ/r) plus TDF (n = 250). Virological treatment outcomes were classified into 3 risk strata for emergence of resistance, based on whether undetectable HIV RNA levels were maintained during therapy and, if not, whether viral loads were >500 copies/mL during treatment. Probabilities for presence of resistance mutations were estimated from GRTs (n = 2876) according to risk stratum and therapy received at time of testing. On the basis of these data, events of resistance emergence were imputed for each individual and were assessed using survival analysis. Imputation was repeated 100 times, and results were summarized by median values (2.5th-97.5th percentile range). RESULTS: Six years after treatment initiation, EFV plus AZT showed the highest cumulative resistance incidence (16%) of all regimens (<11%). Confounder-adjusted Cox regression confirmed that first-line EFV plus AZT (reference) was associated with a higher median hazard for resistance emergence, compared with other treatments: EFV plus TDF (hazard ratio [HR], 0.57; range, 0.42-0.76), LPV plus AZT (HR, 0.63; range, 0.45-0.89), LPV plus TDF (HR, 0.55; range, 0.33-0.83), ATZ/r plus TDF (HR, 0.43; range, 0.17-0.83). Two-thirds of resistance events were associated with detectable HIV RNA level ≤500 copies/mL during treatment, and only one-third with virological failure (HIV RNA level, >500 copies/mL). CONCLUSIONS: The inclusion of TDF instead of AZT and ATZ/r was correlated with lower rates of resistance emergence, most likely because of improved tolerability and pharmacokinetics resulting from a once-daily dosage.
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A problem in the archaeometric classification of Catalan Renaissance pottery is the fact, thatthe clay supply of the pottery workshops was centrally organized by guilds, and thereforeusually all potters of a single production centre produced chemically similar ceramics.However, analysing the glazes of the ware usually a large number of inclusions in the glaze isfound, which reveal technological differences between single workshops. These inclusionshave been used by the potters in order to opacify the transparent glaze and to achieve a whitebackground for further decoration.In order to distinguish different technological preparation procedures of the single workshops,at a Scanning Electron Microscope the chemical composition of those inclusions as well astheir size in the two-dimensional cut is recorded. Based on the latter, a frequency distributionof the apparent diameters is estimated for each sample and type of inclusion.Following an approach by S.D. Wicksell (1925), it is principally possible to transform thedistributions of the apparent 2D-diameters back to those of the true three-dimensional bodies.The applicability of this approach and its practical problems are examined using differentways of kernel density estimation and Monte-Carlo tests of the methodology. Finally, it istested in how far the obtained frequency distributions can be used to classify the pottery
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BACKGROUND: Age and the Glasgow Coma Scale (GCS) score on admission are considered important predictors of outcome after traumatic brain injury. We investigated the predictive value of the GCS in a large group of patients whose computerised multimodal bedside monitoring data had been collected over the previous 10 years. METHODS: Data from 358 subjects with head injury, collected between 1992 and 2001, were analysed retrospectively. Patients were grouped according to year of admission. Glasgow Outcome Scores (GOS) were determined at six months. Spearman's correlation coefficients between GCS and GOS scores were calculated for each year. RESULTS: On average 34 (SD: 7) patients were monitored every year. We found a significant correlation between the GCS and GOS for the first five years (overall 1992-1996: r = 0.41; p<0.00001; n = 183) and consistent lack of correlations from 1997 onwards (overall 1997-2001: r = 0.091; p = 0.226; n = 175). In contrast, correlations between age and GOS were in both time periods significant and similar (r = -0.24 v r = -0.24; p<0.002). CONCLUSIONS: The admission GCS lost its predictive value for outcome in this group of patients from 1997 onwards. The predictive value of the GCS should be carefully reconsidered when building prognostic models incorporating multimodality monitoring after head injury.
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BACKGROUND Obesity is positively associated with colorectal cancer. Recently, body size subtypes categorised by the prevalence of hyperinsulinaemia have been defined, and metabolically healthy overweight/obese individuals (without hyperinsulinaemia) have been suggested to be at lower risk of cardiovascular disease than their metabolically unhealthy (hyperinsulinaemic) overweight/obese counterparts. Whether similarly variable relationships exist for metabolically defined body size phenotypes and colorectal cancer risk is unknown. METHODS AND FINDINGS The association of metabolically defined body size phenotypes with colorectal cancer was investigated in a case-control study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Metabolic health/body size phenotypes were defined according to hyperinsulinaemia status using serum concentrations of C-peptide, a marker of insulin secretion. A total of 737 incident colorectal cancer cases and 737 matched controls were divided into tertiles based on the distribution of C-peptide concentration amongst the control population, and participants were classified as metabolically healthy if below the first tertile of C-peptide and metabolically unhealthy if above the first tertile. These metabolic health definitions were then combined with body mass index (BMI) measurements to create four metabolic health/body size phenotype categories: (1) metabolically healthy/normal weight (BMI < 25 kg/m2), (2) metabolically healthy/overweight (BMI ≥ 25 kg/m2), (3) metabolically unhealthy/normal weight (BMI < 25 kg/m2), and (4) metabolically unhealthy/overweight (BMI ≥ 25 kg/m2). Additionally, in separate models, waist circumference measurements (using the International Diabetes Federation cut-points [≥80 cm for women and ≥94 cm for men]) were used (instead of BMI) to create the four metabolic health/body size phenotype categories. Statistical tests used in the analysis were all two-sided, and a p-value of <0.05 was considered statistically significant. In multivariable-adjusted conditional logistic regression models with BMI used to define adiposity, compared with metabolically healthy/normal weight individuals, we observed a higher colorectal cancer risk among metabolically unhealthy/normal weight (odds ratio [OR] = 1.59, 95% CI 1.10-2.28) and metabolically unhealthy/overweight (OR = 1.40, 95% CI 1.01-1.94) participants, but not among metabolically healthy/overweight individuals (OR = 0.96, 95% CI 0.65-1.42). Among the overweight individuals, lower colorectal cancer risk was observed for metabolically healthy/overweight individuals compared with metabolically unhealthy/overweight individuals (OR = 0.69, 95% CI 0.49-0.96). These associations were generally consistent when waist circumference was used as the measure of adiposity. To our knowledge, there is no universally accepted clinical definition for using C-peptide level as an indication of hyperinsulinaemia. Therefore, a possible limitation of our analysis was that the classification of individuals as being hyperinsulinaemic-based on their C-peptide level-was arbitrary. However, when we used quartiles or the median of C-peptide, instead of tertiles, as the cut-point of hyperinsulinaemia, a similar pattern of associations was observed. CONCLUSIONS These results support the idea that individuals with the metabolically healthy/overweight phenotype (with normal insulin levels) are at lower colorectal cancer risk than those with hyperinsulinaemia. The combination of anthropometric measures with metabolic parameters, such as C-peptide, may be useful for defining strata of the population at greater risk of colorectal cancer.
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It has been shown that the accuracy of mammographic abnormality detection methods is strongly dependent on the breast tissue characteristics, where a dense breast drastically reduces detection sensitivity. In addition, breast tissue density is widely accepted to be an important risk indicator for the development of breast cancer. Here, we describe the development of an automatic breast tissue classification methodology, which can be summarized in a number of distinct steps: 1) the segmentation of the breast area into fatty versus dense mammographic tissue; 2) the extraction of morphological and texture features from the segmented breast areas; and 3) the use of a Bayesian combination of a number of classifiers. The evaluation, based on a large number of cases from two different mammographic data sets, shows a strong correlation ( and 0.67 for the two data sets) between automatic and expert-based Breast Imaging Reporting and Data System mammographic density assessment
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Diagnosis of several neurological disorders is based on the detection of typical pathological patterns in the electroencephalogram (EEG). This is a time-consuming task requiring significant training and experience. Automatic detection of these EEG patterns would greatly assist in quantitative analysis and interpretation. We present a method, which allows automatic detection of epileptiform events and discrimination of them from eye blinks, and is based on features derived using a novel application of independent component analysis. The algorithm was trained and cross validated using seven EEGs with epileptiform activity. For epileptiform events with compensation for eyeblinks, the sensitivity was 65 +/- 22% at a specificity of 86 +/- 7% (mean +/- SD). With feature extraction by PCA or classification of raw data, specificity reduced to 76 and 74%, respectively, for the same sensitivity. On exactly the same data, the commercially available software Reveal had a maximum sensitivity of 30% and concurrent specificity of 77%. Our algorithm performed well at detecting epileptiform events in this preliminary test and offers a flexible tool that is intended to be generalized to the simultaneous classification of many waveforms in the EEG.
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BACKGROUND: Rapid diagnostic tests for malaria (RDTs) allow accurate diagnosis and prompt treatment. Validation of their usefulness in travellers with fever was needed. The safety of a strategy to diagnose falciparum malaria based on RDT followed by immediate or delayed microscopy reading at first attendance was evaluated in one referral hospital in Switzerland. METHODS: A retrospective study was conducted in the outpatient clinic and emergency ward of University Hospital, covering a period of eight years (1999-2007). The study was conducted in the outpatient clinic and emergency ward of University Hospital. All adults suspected of malaria with a diagnostic test performed were included. RDT and microscopy as immediate tests were performed during working hours, and RDT as immediate test and delayed microscopy reading out of laboratory working hours. The main outcome measure was occurrence of specific complications in RDT negative and RDT positive adults. RESULTS: 2,139 patients were recruited. 1987 had both initial RDT and blood smear (BS) result negative. Among those, 2/1987 (0.1%) developed uncomplicated malaria with both RDT and BS positive on day 1 and day 6 respectively. Among the 152 patients initially malaria positive, 137 had both RDT and BS positive, four only BS positive and five only RDT positive (PCR confirmed) (six had only one test performed). None of the four initially RDT negative/BS positive and none of the five initially BS negative/RDT positive developed severe malaria while 6/137 of both RDT and BS positive did so. The use of RDT allowed a reduction of a median of 2.1 hours to get a first malaria test result. CONCLUSIONS: A malaria diagnostic strategy based on RDTs and a delayed BS is safe in non-immune populations, and shortens the time to first malaria test result.
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Crear un mòdul per al projecte d'autoavaluació InnovaCampus que ens permeti generar test utilitzant preguntes amb recursos, com podrien ser imatges, àudio, vídeo o documents, i poder generar preguntes que depenguin d'altres anteriors o que estiguin vinculades.
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Collection : Bibliothèque de botanique cryptogamique
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Given a set of images of scenes containing different object categories (e.g. grass, roads) our objective is to discover these objects in each image, and to use this object occurrences to perform a scene classification (e.g. beach scene, mountain scene). We achieve this by using a supervised learning algorithm able to learn with few images to facilitate the user task. We use a probabilistic model to recognise the objects and further we classify the scene based on their object occurrences. Experimental results are shown and evaluated to prove the validity of our proposal. Object recognition performance is compared to the approaches of He et al. (2004) and Marti et al. (2001) using their own datasets. Furthermore an unsupervised method is implemented in order to evaluate the advantages and disadvantages of our supervised classification approach versus an unsupervised one