981 resultados para validation process
Resumo:
Matrix effects, which represent an important issue in liquid chromatography coupled to mass spectrometry or tandem mass spectrometry detection, should be closely assessed during method development. In the case of quantitative analysis, the use of stable isotope-labelled internal standard with physico-chemical properties and ionization behaviour similar to the analyte is recommended. In this paper, an example of the choice of a co-eluting deuterated internal standard to compensate for short-term and long-term matrix effect in the case of chiral (R,S)-methadone plasma quantification is reported. The method was fully validated over a concentration range of 5-800 ng/mL for each methadone enantiomer with satisfactory relative bias (-1.0 to 1.0%), repeatability (0.9-4.9%) and intermediate precision (1.4-12.0%). From the results obtained during validation, a control chart process during 52 series of routine analysis was established using both intermediate precision standard deviation and FDA acceptance criteria. The results of routine quality control samples were generally included in the +/-15% variability around the target value and mainly in the two standard deviation interval illustrating the long-term stability of the method. The intermediate precision variability estimated in method validation was found to be coherent with the routine use of the method. During this period, 257 trough concentration and 54 peak concentration plasma samples of patients undergoing (R,S)-methadone treatment were successfully analysed for routine therapeutic drug monitoring.
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A wide range of numerical models and tools have been developed over the last decades to support the decision making process in environmental applications, ranging from physical models to a variety of statistically-based methods. In this study, a landslide susceptibility map of a part of Three Gorges Reservoir region of China was produced, employing binary logistic regression analyses. The available information includes the digital elevation model of the region, geological map and different GIS layers including land cover data obtained from satellite imagery. The landslides were observed and documented during the field studies. The validation analysis is exploited to investigate the quality of mapping.
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BACKGROUND Several questionnaires have been used to measure health related quality of life (HRQoL) in patients with psoriasis, few have been adapted for use in Spain; none of them was developed specifically for the Spanish population. The purpose of the study was to validate and assess the sensitivity to change of a new questionnaire to measure HRQOL in patients with psoriasis (PSO-LIFE). METHODS Observational, prospective, multicenter study performed in centers around Spain. Patients with active or inactive psoriasis completed the PSO-LIFE together with other Dermatology Quality of Life Index (DLQI) and Psoriasis Disability Index (PDI). A control group of patients with urticaria or atopic dermatitis was also included. Internal consistency and test-retest reliability of the PSO-LIFE were assessed by calculating Cronbach's alpha and Intraclass Correlation Coefficient (ICC). Validity was assessed by examining factorial structure, the capacity to discriminate between groups, and correlations with other measures. Sensitivity to change was measured using effect sizes. RESULTS The final sample included for analysis consisted of 304 patients and 56 controls. Mean (SD) age of psoriasis patients was 45.3 (14.5) years compared to 38.8 (14) years for controls (p < 0.01). Cronbach's alpha for the PSO-LIFE was 0.95 and test-retest reliability using the ICC was 0.98. Factor analysis showed the questionnaire to be unidimensional. Mean (SD) PSO-LIFE scores differed between patients with psoriasis and controls (64.9 [22.5] vs 69.4 [17.3]; p < 0.05), between those with active and inactive disease (57.4 [20.4] vs 76.4 [20.6]; p < 0.01), and between those with visible and non-visible lesions (63.0 [21.9] vs. 74.8 [23.9]; p < 0.01). The correlation between PSO-LIFE and PASI scores was moderate (r = -0.43) while correlations with DLQI and PDI dimensions ranged from moderate to high (between 0.4 and 0.8). Effect size on the PSO-LIFE in patients reporting 'much improved' health status at study completion was 1.01 (large effect size). CONCLUSIONS The present results provide substantial support for the reliability, validity, and responsiveness of the PSO-LIFE questionnaire in the population for which it was designed.
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Carbon isotope ratio of androgens in urine specimens is routinely determined to exclude an abuse of testosterone or testosterone prohormones by athletes. Increasing application of gas chromatography/combustion/isotope ratio mass spectrometry (GC/C/IRMS) in the last years for target and systematic investigations on samples has resulted in the demand for rapid sample throughput as well as high selectivity in the extraction process particularly in the case of conspicuous samples. For that purpose, we present herein the complimentary use of an SPE-based assay and an HPLC fractionation method as a two-stage strategy for the isolation of testosterone metabolites and endogenous reference compounds prior to GC/C/IRMS analyses. Assays validation demonstrated acceptable performance in terms of intermediate precision (range: 0.1-0.4 per thousand) and Bland-Altman analyses revealed no significant bias (0.2 per thousand). For further validation of this two-stage analyses strategy, all the specimens (n=124) collected during a major sport event were processed.
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BACKGROUND The purpose of the present study is to translate and validate the "Hip and Knee Outcomes Questionnaire", developed in English, into Spanish. The 'Hip and Knee Outcomes Questionnaire is a questionnaire planned to evaluate the impact in quality of life of any problem related to the human musculoskeletal system. 10 scientific associations developed it. METHODS The questionnaire underwent a validated translation/retro-translation process. Patients undergoing primary knee arthroplasty, before and six months postoperative, tested the final version in Spanish. Psychometric properties of feasibility, reliability, validity and sensitivity to change were assessed. Convergent validity with SF-36 and WOMAC questionnaires was evaluated. RESULTS 316 patients were included. Feasibility: a high number of missing items in questions 3, 4 and 5 were observed. The number of patients with a missing item was 171 (51.35%) in the preoperative visit and 139 (44.0%) at the postoperative. Internal validity: revision of coefficients in the item-rest correlation recommended removing question 6 during the preoperative visit (coefficient <0.20). Convergent validity: coefficients of correlation with WOMAC and SF-36 scales confirm the questionnaire's validity. Sensitivity to change: statistically significant differences were found between the mean scores of the first visit compared to the postoperative. CONCLUSION The proposed translation to Spanish of the 'Hip and Knee Questionnaire' is found to be reliable, valid and sensible to changes produced at the clinical practice of patients undergoing primary knee arthroplasty. However, some changes at the completion instructions are recommended. LEVEL OF EVIDENCE Level I. Prognostic study.
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BACKGROUND: The reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) is a widely used, highly sensitive laboratory technique to rapidly and easily detect, identify and quantify gene expression. Reliable RT-qPCR data necessitates accurate normalization with validated control genes (reference genes) whose expression is constant in all studied conditions. This stability has to be demonstrated.We performed a literature search for studies using quantitative or semi-quantitative PCR in the rat spared nerve injury (SNI) model of neuropathic pain to verify whether any reference genes had previously been validated. We then analyzed the stability over time of 7 commonly used reference genes in the nervous system - specifically in the spinal cord dorsal horn and the dorsal root ganglion (DRG). These were: Actin beta (Actb), Glyceraldehyde-3-phosphate dehydrogenase (GAPDH), ribosomal proteins 18S (18S), L13a (RPL13a) and L29 (RPL29), hypoxanthine phosphoribosyltransferase 1 (HPRT1) and hydroxymethylbilane synthase (HMBS). We compared the candidate genes and established a stability ranking using the geNorm algorithm. Finally, we assessed the number of reference genes necessary for accurate normalization in this neuropathic pain model. RESULTS: We found GAPDH, HMBS, Actb, HPRT1 and 18S cited as reference genes in literature on studies using the SNI model. Only HPRT1 and 18S had been once previously demonstrated as stable in RT-qPCR arrays. All the genes tested in this study, using the geNorm algorithm, presented gene stability values (M-value) acceptable enough for them to qualify as potential reference genes in both DRG and spinal cord. Using the coefficient of variation, 18S failed the 50% cut-off with a value of 61% in the DRG. The two most stable genes in the dorsal horn were RPL29 and RPL13a; in the DRG they were HPRT1 and Actb. Using a 0.15 cut-off for pairwise variations we found that any pair of stable reference gene was sufficient for the normalization process. CONCLUSIONS: In the rat SNI model, we validated and ranked Actb, RPL29, RPL13a, HMBS, GAPDH, HPRT1 and 18S as good reference genes in the spinal cord. In the DRG, 18S did not fulfill stability criteria. The combination of any two stable reference genes was sufficient to provide an accurate normalization.
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The Rational-Experiential Inventory REI (Pacini and Epstein, 1999) is a self-administered test comprising two scales measuring the attitude of respondents towards two thinking styles respectively referred to as the rational and the experiential thinking styles. Two validation studies were conducted using a new French-language version of the REI. The first study confirms the validity of the French translation. The second study, which is concerned with the REI's construct validity, assesses the questionnaire's capacity to discriminate between a group of smokers and a group of non-smokers. Both studies give generally satisfactory results. In particular, the advantages of using the two-dimensional REI rather than the better known Need For Cognition scale (Cacioppo & Petty, 1982) are made quite clear.
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Presented is an accurate swimming velocity estimation method using an inertial measurement unit (IMU) by employing a simple biomechanical constraint of motion along with Gaussian process regression to deal with sensor inherent errors. Experimental validation shows a velocity RMS error of 9.0 cm/s and high linear correlation when compared with a commercial tethered reference system. The results confirm the practicality of the presented method to estimate swimming velocity using a single low-cost, body-worn IMU.
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In this work, a previously-developed, statistical-based, damage-detection approach was validated for its ability to autonomously detect damage in bridges. The damage-detection approach uses statistical differences in the actual and predicted behavior of the bridge caused under a subset of ambient trucks. The predicted behavior is derived from a statistics-based model trained with field data from the undamaged bridge (not a finite element model). The differences between actual and predicted responses, called residuals, are then used to construct control charts, which compare undamaged and damaged structure data. Validation of the damage-detection approach was achieved by using sacrificial specimens that were mounted to the bridge and exposed to ambient traffic loads and which simulated actual damage-sensitive locations. Different damage types and levels were introduced to the sacrificial specimens to study the sensitivity and applicability. The damage-detection algorithm was able to identify damage, but it also had a high false-positive rate. An evaluation of the sub-components of the damage-detection methodology and methods was completed for the purpose of improving the approach. Several of the underlying assumptions within the algorithm were being violated, which was the source of the false-positives. Furthermore, the lack of an automatic evaluation process was thought to potentially be an impediment to widespread use. Recommendations for the improvement of the methodology were developed and preliminarily evaluated. These recommendations are believed to improve the efficacy of the damage-detection approach.
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False identity documents constitute a potential powerful source of forensic intelligence because they are essential elements of transnational crime and provide cover for organized crime. In previous work, a systematic profiling method using false documents' visual features has been built within a forensic intelligence model. In the current study, the comparison process and metrics lying at the heart of this profiling method are described and evaluated. This evaluation takes advantage of 347 false identity documents of four different types seized in two countries whose sources were known to be common or different (following police investigations and dismantling of counterfeit factories). Intra-source and inter-sources variations were evaluated through the computation of more than 7500 similarity scores. The profiling method could thus be validated and its performance assessed using two complementary approaches to measuring type I and type II error rates: a binary classification and the computation of likelihood ratios. Very low error rates were measured across the four document types, demonstrating the validity and robustness of the method to link documents to a common source or to differentiate them. These results pave the way for an operational implementation of a systematic profiling process integrated in a developed forensic intelligence model.
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The objective of this research is to determine whether the nationally calibrated performance models used in the Mechanistic-Empirical Pavement Design Guide (MEPDG) provide a reasonable prediction of actual field performance, and if the desired accuracy or correspondence exists between predicted and monitored performance for Iowa conditions. A comprehensive literature review was conducted to identify the MEPDG input parameters and the MEPDG verification/calibration process. Sensitivities of MEPDG input parameters to predictions were studied using different versions of the MEPDG software. Based on literature review and sensitivity analysis, a detailed verification procedure was developed. A total of sixteen different types of pavement sections across Iowa, not used for national calibration in NCHRP 1-47A, were selected. A database of MEPDG inputs and the actual pavement performance measures for the selected pavement sites were prepared for verification. The accuracy of the MEPDG performance models for Iowa conditions was statistically evaluated. The verification testing showed promising results in terms of MEPDG’s performance prediction accuracy for Iowa conditions. Recalibrating the MEPDG performance models for Iowa conditions is recommended to improve the accuracy of predictions. ****************** Large File**************************
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This paper presents a new non parametric atlas registration framework, derived from the optical flow model and the active contour theory, applied to automatic subthalamic nucleus (STN) targeting in deep brain stimulation (DBS) surgery. In a previous work, we demonstrated that the STN position can be predicted based on the position of surrounding visible structures, namely the lateral and third ventricles. A STN targeting process can thus be obtained by registering these structures of interest between a brain atlas and the patient image. Here we aim to improve the results of the state of the art targeting methods and at the same time to reduce the computational time. Our simultaneous segmentation and registration model shows mean STN localization errors statistically similar to the most performing registration algorithms tested so far and to the targeting expert's variability. Moreover, the computational time of our registration method is much lower, which is a worthwhile improvement from a clinical point of view.
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ABSTRACT: BACKGROUND: Chest wall syndrome (CWS), the main cause of chest pain in primary care practice, is most often an exclusion diagnosis. We developed and evaluated a clinical prediction rule for CWS. METHODS: Data from a multicenter clinical cohort of consecutive primary care patients with chest pain were used (59 general practitioners, 672 patients). A final diagnosis was determined after 12 months of follow-up. We used the literature and bivariate analyses to identify candidate predictors, and multivariate logistic regression was used to develop a clinical prediction rule for CWS. We used data from a German cohort (n = 1212) for external validation. RESULTS: From bivariate analyses, we identified six variables characterizing CWS: thoracic pain (neither retrosternal nor oppressive), stabbing, well localized pain, no history of coronary heart disease, absence of general practitioner's concern, and pain reproducible by palpation. This last variable accounted for 2 points in the clinical prediction rule, the others for 1 point each; the total score ranged from 0 to 7 points. The area under the receiver operating characteristic (ROC) curve was 0.80 (95% confidence interval 0.76-0.83) in the derivation cohort (specificity: 89%; sensitivity: 45%; cut-off set at 6 points). Among all patients presenting CWS (n = 284), 71% (n = 201) had a pain reproducible by palpation and 45% (n = 127) were correctly diagnosed. For a subset (n = 43) of these correctly classified CWS patients, 65 additional investigations (30 electrocardiograms, 16 thoracic radiographies, 10 laboratory tests, eight specialist referrals, one thoracic computed tomography) had been performed to achieve diagnosis. False positives (n = 41) included three patients with stable angina (1.8% of all positives). External validation revealed the ROC curve to be 0.76 (95% confidence interval 0.73-0.79) with a sensitivity of 22% and a specificity of 93%. CONCLUSIONS: This CWS score offers a useful complement to the usual CWS exclusion diagnosing process. Indeed, for the 127 patients presenting CWS and correctly classified by our clinical prediction rule, 65 additional tests and exams could have been avoided. However, the reproduction of chest pain by palpation, the most important characteristic to diagnose CWS, is not pathognomonic.
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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.