889 resultados para Validation of analytical methodology


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Measuring the height of the vertical jump is an indicator of the strength and power of the lower body. The technological tools available to measure the vertical jump are black boxes and are not open to third-party verification or adaptation. We propose the creation of a measurement system called Chronojump-Boscosystem, consisting of open hardware and free software. Methods: A microcontroller was created and validated using a square wave generator and an oscilloscope. Two types of contact platforms were developed using different materials. These platforms were validated by the minimum pressure required for activation at different points by a strain gauge, together with the on/off time of our platforms in respect of the Ergojump-Boscosystem platform by a sample of 8 subjects performing submaximal jumps with one foot on each platform. Agile methodologies were used to develop and validate the software. Results: All the tools fall under the free software / open hardware guidelines and are, in that sense, free. The microcontroller margin of error is 0.1%. The validity of the fiberglass platform is 0.95 (ICC). The management software contains nearly 113.000 lines of code and is available in 7 languages.

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We propose a deep study on tissue modelization andclassification Techniques on T1-weighted MR images. Threeapproaches have been taken into account to perform thisvalidation study. Two of them are based on FiniteGaussian Mixture (FGM) model. The first one consists onlyin pure gaussian distributions (FGM-EM). The second oneuses a different model for partial volume (PV) (FGM-GA).The third one is based on a Hidden Markov Random Field(HMRF) model. All methods have been tested on a DigitalBrain Phantom image considered as the ground truth. Noiseand intensity non-uniformities have been added tosimulate real image conditions. Also the effect of ananisotropic filter is considered. Results demonstratethat methods relying in both intensity and spatialinformation are in general more robust to noise andinhomogeneities. However, in some cases there is nosignificant differences between all presented methods.

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RATIONALE: An objective and simple prognostic model for patients with pulmonary embolism could be helpful in guiding initial intensity of treatment. OBJECTIVES: To develop a clinical prediction rule that accurately classifies patients with pulmonary embolism into categories of increasing risk of mortality and other adverse medical outcomes. METHODS: We randomly allocated 15,531 inpatient discharges with pulmonary embolism from 186 Pennsylvania hospitals to derivation (67%) and internal validation (33%) samples. We derived our prediction rule using logistic regression with 30-day mortality as the primary outcome, and patient demographic and clinical data routinely available at presentation as potential predictor variables. We externally validated the rule in 221 inpatients with pulmonary embolism from Switzerland and France. MEASUREMENTS: We compared mortality and nonfatal adverse medical outcomes across the derivation and two validation samples. MAIN RESULTS: The prediction rule is based on 11 simple patient characteristics that were independently associated with mortality and stratifies patients with pulmonary embolism into five severity classes, with 30-day mortality rates of 0-1.6% in class I, 1.7-3.5% in class II, 3.2-7.1% in class III, 4.0-11.4% in class IV, and 10.0-24.5% in class V across the derivation and validation samples. Inpatient death and nonfatal complications were <or= 1.1% among patients in class I and <or= 1.9% among patients in class II. CONCLUSIONS: Our rule accurately classifies patients with pulmonary embolism into classes of increasing risk of mortality and other adverse medical outcomes. Further validation of the rule is important before its implementation as a decision aid to guide the initial management of patients with pulmonary embolism.

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The present prospective study, with a five-year follow-up, presents an extensive psychiatric and educational assessment of an adolescent population (N = 30) in the age range 14-20, suffering from several psychiatric disorders, though apt to follow a normal academic program. The residential settings where the study took place provide both psychiatric and schooling facilities. In this environment, what is the effectiveness of long-term hospitalization? Are there any criteria for predicting results? After discharge, could social adjustments difficulties be prevented? Assessment instruments are described and the results of one preliminary study are presented. The actual data seems to confirm the impact of the special treatment facilities combining schooling and psychiatric settings on the long term outcome of adolescents.

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In response to an increasing need for ever-shorter personality instruments, Gosling, Rentfrow, and Swann (2003) developed the Ten-Item-Personality Inventory (TIPI), which measures the dimensions of the Five Factor Model (FFM) using 10 items (two for each dimension) and can be administered in about one minute. In two studies and using a multi-judge (self and observer) and multi-instrument design, we develop Spanish (Castilian) and Catalan versions of the TIPI and evaluate them in terms of internal consistency, test-retest reliability, convergent, discriminant, and content validity, as well as self-observer correlations. Test-retest correlations were strong, and convergence with the NEO-PI-R factors was significant. There were also strong correlations between observer ratings and the participants’ self-ratings. Despite some inconsistencies with respect to the Agreeableness scale, the Catalan translation and both translations into Spanish of the original TIPI demonstrated sufficient psychometric properties to warrant use as a Five Factor personality measure when the use of longer instruments is not convenient or possible. Furthermore, as the first translation of a brief standard Big Five Instrument into Catalan, this work should facilitate future research on personality in the Catalan-speaking population.

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The objective of this work was to validate microsatellite markers associated with resistance to soybean cyst nematode (Heterodera glycines Ichinohe) races 3 and 14, in soybean (Glycine max L.) genotypes, for use in marker-assisted selection (MAS) programs. Microsatellites of soybean linkage groups A2, D2 and G were tested in two populations, and their selection efficiencies were determined. The populations were 65 F2:3 families from Msoy8001 (resistant) x Conquista (susceptible) cross, and 66 F2:3 families of S5995 (resistant) x Renascença (susceptible) cross, evaluated for resistance to races 3 and 14, respectively. Families with female index up to 30% were considered moderately resistant. Markers of A2 and G linkage groups were associated with resistance to race 3. Markers Satt309 and GMENOD2B explained the greatest proportion of phenotypic variance in the different groups. The combinations Satt309+GMENOD2B and Satt309+Satt187 presented 100% selection efficiency. Resistance to race 14 was associated with markers of G linkage group, and selection efficiency in the Satt309+Satt356 combination was 100%. The selection differential obtained by phenotypic and marker assisted selection showed that both can result in similar gains.

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In the last five years, Deep Brain Stimulation (DBS) has become the most popular and effective surgical technique for the treatent of Parkinson's disease (PD). The Subthalamic Nucleus (STN) is the usual target involved when applying DBS. Unfortunately, the STN is in general not visible in common medical imaging modalities. Therefore, atlas-based segmentation is commonly considered to locate it in the images. In this paper, we propose a scheme that allows both, to perform a comparison between different registration algorithms and to evaluate their ability to locate the STN automatically. Using this scheme we can evaluate the expert variability against the error of the algorithms and we demonstrate that automatic STN location is possible and as accurate as the methods currently used.

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Background: Ethical conflicts are arising as a result of the growing complexity of clinical care, coupled with technological advances. Most studies that have developed instruments for measuring ethical conflict base their measures on the variables"frequency" and"degree of conflict". In our view, however, these variables are insufficient for explaining the root of ethical conflicts. Consequently, the present study formulates a conceptual model that also includes the variable"exposure to conflict", as well as considering six"types of ethical conflict". An instrument was then designed to measure the ethical conflicts experienced by nurses who work with critical care patients. The paper describes the development process and validation of this instrument, the Ethical Conflict in Nursing Questionnaire Critical Care Version (ECNQ-CCV). Methods: The sample comprised 205 nursing professionals from the critical care units of two hospitals in Barcelona (Spain). The ECNQ-CCV presents 19 nursing scenarios with the potential to produce ethical conflict in the critical care setting. Exposure to ethical conflict was assessed by means of the Index of Exposure to Ethical Conflict (IEEC), a specific index developed to provide a reference value for each respondent by combining the intensity and frequency of occurrence of each scenario featured in the ECNQ-CCV. Following content validity, construct validity was assessed by means of Exploratory Factor Analysis (EFA), while Cronbach"s alpha was used to evaluate the instrument"s reliability. All analyses were performed using the statistical software PASW v19. Results: Cronbach"s alpha for the ECNQ-CCV as a whole was 0.882, which is higher than the values reported for certain other related instruments. The EFA suggested a unidimensional structure, with one component accounting for 33.41% of the explained variance. Conclusions: The ECNQ-CCV is shown to a valid and reliable instrument for use in critical care units. Its structure is such that the four variables on which our model of ethical conflict is based may be studied separately or in combination. The critical care nurses in this sample present moderate levels of exposure to ethical conflict. This study represents the first evaluation of the ECNQ-CCV.

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Background: Ethical conflicts are arising as a result of the growing complexity of clinical care, coupled with technological advances. Most studies that have developed instruments for measuring ethical conflict base their measures on the variables"frequency" and"degree of conflict". In our view, however, these variables are insufficient for explaining the root of ethical conflicts. Consequently, the present study formulates a conceptual model that also includes the variable"exposure to conflict", as well as considering six"types of ethical conflict". An instrument was then designed to measure the ethical conflicts experienced by nurses who work with critical care patients. The paper describes the development process and validation of this instrument, the Ethical Conflict in Nursing Questionnaire Critical Care Version (ECNQ-CCV). Methods: The sample comprised 205 nursing professionals from the critical care units of two hospitals in Barcelona (Spain). The ECNQ-CCV presents 19 nursing scenarios with the potential to produce ethical conflict in the critical care setting. Exposure to ethical conflict was assessed by means of the Index of Exposure to Ethical Conflict (IEEC), a specific index developed to provide a reference value for each respondent by combining the intensity and frequency of occurrence of each scenario featured in the ECNQ-CCV. Following content validity, construct validity was assessed by means of Exploratory Factor Analysis (EFA), while Cronbach"s alpha was used to evaluate the instrument"s reliability. All analyses were performed using the statistical software PASW v19. Results: Cronbach"s alpha for the ECNQ-CCV as a whole was 0.882, which is higher than the values reported for certain other related instruments. The EFA suggested a unidimensional structure, with one component accounting for 33.41% of the explained variance. Conclusions: The ECNQ-CCV is shown to a valid and reliable instrument for use in critical care units. Its structure is such that the four variables on which our model of ethical conflict is based may be studied separately or in combination. The critical care nurses in this sample present moderate levels of exposure to ethical conflict. This study represents the first evaluation of the ECNQ-CCV.

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Head space gas chromatography with flame-ionization detection (HS-GC-FID), ancl purge and trap gas chromatography-mass spectrometry (P&T-GC-MS) have been used to determine methyl-tert-butyl ether (MTBE) and benzene, toluene, and the ylenes (BTEX) in groundwater. In the work discussed in this paper measures of quality, e.g. recovery (94-111%), precision (4.6 - 12.2%), limits of detection (0.3 - 5.7 I~g L 1 for HS and 0.001 I~g L 1 for PT), and robust-ness, for both methods were compared. In addition, for purposes of comparison, groundwater samples from areas suffering from odor problems because of fuel spillage and tank leakage were analyzed by use of both techniques. For high concentration levels there was good correlation between results from both methods.

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Chaque jour, le médecin utilise dans sa pratique des scores cliniques. Ces scores sont souvent des aides à la décision médicale. Les étapes de validation des scores cliniques sont par contre souvent méconnues du médecin. Cette revue rappelle les bases théoriques de la validation d'un score clinique et propose des exercices pratiques. [Abstract] Physicians are using clinical scores on a regular basis. These scores are generally helpful in making medical decisions. However, the process of validation of clinical scores is often unknown to the physicians. This paper reviews the theory of validation of clinical scores and proposes practical exercises.

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This paper presents a validation study on statistical nonsupervised brain tissue classification techniques in magnetic resonance (MR) images. Several image models assuming different hypotheses regarding the intensity distribution model, the spatial model and the number of classes are assessed. The methods are tested on simulated data for which the classification ground truth is known. Different noise and intensity nonuniformities are added to simulate real imaging conditions. No enhancement of the image quality is considered either before or during the classification process. This way, the accuracy of the methods and their robustness against image artifacts are tested. Classification is also performed on real data where a quantitative validation compares the methods' results with an estimated ground truth from manual segmentations by experts. Validity of the various classification methods in the labeling of the image as well as in the tissue volume is estimated with different local and global measures. Results demonstrate that methods relying on both intensity and spatial information are more robust to noise and field inhomogeneities. We also demonstrate that partial volume is not perfectly modeled, even though methods that account for mixture classes outperform methods that only consider pure Gaussian classes. Finally, we show that simulated data results can also be extended to real data.