147 resultados para Validation of measures
em BORIS: Bern Open Repository and Information System - Berna - Suiça
Resumo:
Background The loose and stringent Asthma Predictive Indices (API), developed in Tucson, are popular rules to predict asthma in preschool children. To be clinically useful, they require validation in different settings. Objective To assess the predictive performance of the API in an independent population and compare it with simpler rules based only on preschool wheeze. Methods We studied 1954 children of the population-based Leicester Respiratory Cohort, followed up from age 1 to 10 years. The API and frequency of wheeze were assessed at age 3 years, and we determined their association with asthma at ages 7 and 10 years by using logistic regression. We computed test characteristics and measures of predictive performance to validate the API and compare it with simpler rules. Results The ability of the API to predict asthma in Leicester was comparable to Tucson: for the loose API, odds ratios for asthma at age 7 years were 5.2 in Leicester (5.5 in Tucson), and positive predictive values were 26% (26%). For the stringent API, these values were 8.2 (9.8) and 40% (48%). For the simpler rule early wheeze, corresponding values were 5.4 and 21%; for early frequent wheeze, 6.7 and 36%. The discriminative ability of all prediction rules was moderate (c statistic ≤ 0.7) and overall predictive performance low (scaled Brier score < 20%). Conclusion Predictive performance of the API in Leicester, although comparable to the original study, was modest and similar to prediction based only on preschool wheeze. This highlights the need for better prediction rules.
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After the discovery of synthetic cannabimimetic substances in 'Spice'-like herbal mixtures marketed as 'incense' or 'plant fertilizer' the active compounds have been declared as controlled substances in several European countries. As expected, a monitoring of new herbal mixtures which continue to appear on the market revealed that shortly after control measures have been taken by legal authorities, other compounds were added to existing mixtures and to new products. Several compounds of the aminoalkylindole type have been detected so far in herbal mixtures but still their consumption cannot be detected by commonly used drug-screening procedures, encouraging drug users to substitute cannabis with those products. There is a increasing demand on the part of police authorities, hospitals and psychiatrists for detection and quantification of synthetic cannabinoids in biological samples originating from psychiatric inpatients, emergency units or assessment of fitness to drive. Therefore, a liquid chromatography-tandem mass spectrometry method after liquid-liquid extraction for the quantitation of JWH-015, JWH-018, JWH-073, JWH-081, JWH 200, JWH-250, WIN 55,212-2 and methanandamide and the detection of JWH-019 and JWH-020 in human serum has been developed and fully validated according to guidelines for forensic toxicological analyses. The method was successfully applied to 101 serum samples from 80 subjects provided by hospitals, detoxification and therapy centers, forensic psychiatric centers and police authorities. Fifty-seven samples or 56.4% were found positive for at least one aminoalkylindole. JWH-019, JWH-020, JWH-200, WIN 55,212-2 and methanandamide were not detected in any of the analyzed samples.
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IMPORTANCE Because effective interventions to reduce hospital readmissions are often expensive to implement, a score to predict potentially avoidable readmissions may help target the patients most likely to benefit. OBJECTIVE To derive and internally validate a prediction model for potentially avoidable 30-day hospital readmissions in medical patients using administrative and clinical data readily available prior to discharge. DESIGN Retrospective cohort study. SETTING Academic medical center in Boston, Massachusetts. PARTICIPANTS All patient discharges from any medical services between July 1, 2009, and June 30, 2010. MAIN OUTCOME MEASURES Potentially avoidable 30-day readmissions to 3 hospitals of the Partners HealthCare network were identified using a validated computerized algorithm based on administrative data (SQLape). A simple score was developed using multivariable logistic regression, with two-thirds of the sample randomly selected as the derivation cohort and one-third as the validation cohort. RESULTS Among 10 731 eligible discharges, 2398 discharges (22.3%) were followed by a 30-day readmission, of which 879 (8.5% of all discharges) were identified as potentially avoidable. The prediction score identified 7 independent factors, referred to as the HOSPITAL score: h emoglobin at discharge, discharge from an o ncology service, s odium level at discharge, p rocedure during the index admission, i ndex t ype of admission, number of a dmissions during the last 12 months, and l ength of stay. In the validation set, 26.7% of the patients were classified as high risk, with an estimated potentially avoidable readmission risk of 18.0% (observed, 18.2%). The HOSPITAL score had fair discriminatory power (C statistic, 0.71) and had good calibration. CONCLUSIONS AND RELEVANCE This simple prediction model identifies before discharge the risk of potentially avoidable 30-day readmission in medical patients. This score has potential to easily identify patients who may need more intensive transitional care interventions.
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Middle atmospheric water vapour can be used as a tracer for dynamical processes. It is mainly measured by satellite instruments and ground-based microwave radiometers. Ground-based instruments capable of measuring middle-atmospheric water vapour are sparse but valuable as they complement satellite measurements, are relatively easy to maintain and have a long lifetime. MIAWARA-C is a ground-based microwave radiometer for middle-atmospheric water vapour designed for use on measurement campaigns for both atmospheric case studies and instrument intercomparisons. MIAWARA-C's retrieval version 1.1 (v1.1) is set up in a such way as to provide a consistent data set even if the instrument is operated from different locations on a campaign basis. The sensitive altitude range for v1.1 extends from 4 hPa (37 km) to 0.017 hPa (75 km). For v1.1 the estimated systematic error is approximately 10% for all altitudes. At lower altitudes it is dominated by uncertainties in the calibration, with altitude the influence of spectroscopic and temperature uncertainties increases. The estimated random error increases with altitude from 5 to 25%. MIAWARA-C measures two polarisations of the incident radiation in separate receiver channels, and can therefore provide two measurements of the same air mass with independent instrumental noise. The standard deviation of the difference between the profiles obtained from the two polarisations is in excellent agreement with the estimated random measurement error of v1.1. In this paper, the quality of v1.1 data is assessed for measurements obtained at two different locations: (1) a total of 25 months of measurements in the Arctic (Sodankylä, 67.37° N, 26.63° E) and (2) nine months of measurements at mid-latitudes (Zimmerwald, 46.88° N, 7.46° E). For both locations MIAWARA-C's profiles are compared to measurements from the satellite experiments Aura MLS and MIPAS. In addition, comparisons to ACE-FTS and SOFIE are presented for the Arctic and to the ground-based radiometer MIAWARA for the mid-latitude campaigns. In general, all intercomparisons show high correlation coefficients, confirming the ability of MIAWARA-C to monitor temporal variations of the order of days. The biases are generally below 13% and within the estimated systematic uncertainty of MIAWARA-C. No consistent wet or dry bias is identified for MIAWARA-C. In addition, comparisons to the reference instruments indicate the estimated random error of v1.1 to be a realistic measure of the random variation on the retrieved profile between 45 and 70 km.
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In patients diagnosed with pharmaco-resistant epilepsy, cerebral areas responsible for seizure generation can be defined by performing implantation of intracranial electrodes. The identification of the epileptogenic zone (EZ) is based on visual inspection of the intracranial electroencephalogram (IEEG) performed by highly qualified neurophysiologists. New computer-based quantitative EEG analyses have been developed in collaboration with the signal analysis community to expedite EZ detection. The aim of the present report is to compare different signal analysis approaches developed in four different European laboratories working in close collaboration with four European Epilepsy Centers. Computer-based signal analysis methods were retrospectively applied to IEEG recordings performed in four patients undergoing pre-surgical exploration of pharmaco-resistant epilepsy. The four methods elaborated by the different teams to identify the EZ are based either on frequency analysis, on nonlinear signal analysis, on connectivity measures or on statistical parametric mapping of epileptogenicity indices. All methods converge on the identification of EZ in patients that present with fast activity at seizure onset. When traditional visual inspection was not successful in detecting EZ on IEEG, the different signal analysis methods produced highly discordant results. Quantitative analysis of IEEG recordings complement clinical evaluation by contributing to the study of epileptogenic networks during seizures. We demonstrate that the degree of sensitivity of different computer-based methods to detect the EZ in respect to visual EEG inspection depends on the specific seizure pattern.
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Careers today increasingly require engagement in proactive career behaviors; however, there is a lack of validated measures assessing the general degree to which somebody is engaged in such career behaviors. We describe the results of six studies with six independent samples of German university students (total N = 2,854), working professionals (total N = 561), and university graduates (N = 141) that report the development and validation of the Career Engagement Scale - a measure of the degree of which somebody is proactively developing her or his career as expressed by diverse career behaviors. The studies provide supprt for measurement invariance across gender and time. In support of convergent and discriminant validity, we find that career engagement is more prevalent among working professionals than among university students and that this scale has incremental validity above several specific career behaviors regarding its relation to vocational identity clarity and career self-efficacy beliefs among students and to job and career satisfaction among employees. In support of incremental predictive validity, beyond the effects of several more specific careeer behaviors, career engagement while at university predicts higher job and career satisfaction several months later after beginning work.
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Introduction: Measuring trait mindfulness and change in mindfulness may be a crucial prerequisite for the evaluation and further development of mindfulness based interventions for the treatment of mental disorders. This endeavour is nontrivial as current measures cover varying aspects and mindfulness and may have problems regarding validity. This presentation describes the development and validation of a questionnaire for the comprehensive assessment of mindfulness: the Comprehensive Inventory of Mindfulness Experiences (CHIME). Method: The factor structure, reliability, and validity of the CHIME were established in a community sample (N = 298) and a sample of MBSR group participants (N = 161). Results: Factor-analytical procedures supported an eight-factor structure. The structure was tested in a further confirmatory sample (N = 202). The questionnaire and its subscales exhibited good reliability (internal consistency and retest-reliability). Analysis of the measurement invariance of the single items over groups differing in age, gender, meditation experience, and symptom load pointed to the absence of systematic differences in the items' semantic understanding. Parameters reflecting construct validity, criterion validity, and incremental validity as well as change sensitivity were all at least satisfactory. Conclusions: The CHIME is a self-report measure with favorable psychometric properties based on all aspects of mindfulness that are included in current mindfulness scales. This scale may be helpful in the evaluation and further development of mindfulness based interventions.
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The "Ardouin Scale of Behavior in Parkinson's Disease" is a new instrument specifically designed for assessing mood and behavior with a view to quantifying changes related to Parkinson's disease, to dopaminergic medication, and to non-motor fluctuations. This study was aimed at analyzing the psychometric attributes of this scale in patients with Parkinson's disease without dementia. In addition to this scale, the following measures were applied: the Unified Parkinson's Disease Rating Scale, the Montgomery and Asberg Depression Rating Scale, the Lille Apathy Rating Scale, the Bech and Rafaelsen Mania Scale, the Positive and Negative Syndrome Scale, the MacElroy Criteria, the Patrick Carnes criteria, the Hospital Anxiety and Depression Scale, and the Mini-International Neuropsychiatric Interview. Patients (n = 260) were recruited at 13 centers across four countries (France, Spain, United Kingdom, and United States). Cronbach's alpha coefficient for domains ranged from 0.69 to 0.78. Regarding test-retest reliability, the kappa coefficient for items was higher than 0.4. For inter-rater reliability, the kappa values were 0.29 to 0.81. Furthermore, most of the items from the Ardouin Scale of Behavior in Parkinson's Disease correlated with the corresponding items of the other scales, depressed mood with the Montgomery and Asberg Depression Rating Scale (ρ = 0.82); anxiety with the Hospital Anxiety and Depression Scale-anxiety (ρ = 0.56); apathy with the Lille Apathy Rating Scale (ρ = 0.60). The Ardouin Scale of Behavior in Parkinson's disease is an acceptable, reproducible, valid, and precise assessment for evaluating changes in behavior in patients with Parkinson's disease without dementia. © 2015 International Parkinson and Movement Disorder Society.
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We investigated whether human articular chondrocytes can be labeled efficiently and for long-term with a green fluorescent protein (GFP) lentivirus and whether the viral transduction would influence cell proliferation and tissue-forming capacity. The method was then applied to track goat articular chondrocytes after autologous implantation in cartilage defects. Expression of GFP in transduced chondrocytes was detected cytofluorimetrically and immunohistochemically. Chondrogenic capacity of chondrocytes was assessed by Safranin-O staining, immunostaining for type II collagen, and glycosaminoglycan content. Human articular chondrocytes were efficiently transduced with GFP lentivirus (73.4 +/- 0.5% at passage 1) and maintained the expression of GFP up to 22 weeks of in vitro culture after transduction. Upon implantation in nude mice, 12 weeks after transduction, the percentage of labeled cells (73.6 +/- 3.3%) was similar to the initial one. Importantly, viral transduction of chondrocytes did not affect the cell proliferation rate, chondrogenic differentiation, or tissue-forming capacity, either in vitro or in vivo. Goat articular chondrocytes were also efficiently transduced with GFP lentivirus (78.3 +/- 3.2%) and maintained the expression of GFP in the reparative tissue after orthotopic implantation. This study demonstrates the feasibility of efficient and relatively long-term labeling of human chondrocytes for co-culture on integration studies, and indicates the potential of this stable labeling technique for tracking animal chondrocytes for in cartilage repair studies.
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Seventeen bones (sixteen cadaveric bones and one plastic bone) were used to validate a method for reconstructing a surface model of the proximal femur from 2D X-ray radiographs and a statistical shape model that was constructed from thirty training surface models. Unlike previously introduced validation studies, where surface-based distance errors were used to evaluate the reconstruction accuracy, here we propose to use errors measured based on clinically relevant morphometric parameters. For this purpose, a program was developed to robustly extract those morphometric parameters from the thirty training surface models (training population), from the seventeen surface models reconstructed from X-ray radiographs, and from the seventeen ground truth surface models obtained either by a CT-scan reconstruction method or by a laser-scan reconstruction method. A statistical analysis was then performed to classify the seventeen test bones into two categories: normal cases and outliers. This classification step depends on the measured parameters of the particular test bone. In case all parameters of a test bone were covered by the training population's parameter ranges, this bone is classified as normal bone, otherwise as outlier bone. Our experimental results showed that statistically there was no significant difference between the morphometric parameters extracted from the reconstructed surface models of the normal cases and those extracted from the reconstructed surface models of the outliers. Therefore, our statistical shape model based reconstruction technique can be used to reconstruct not only the surface model of a normal bone but also that of an outlier bone.
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Auscultatory nonmercury manual devices seem good alternatives for the mercury sphygmomanometers in the clinic and for research settings, but individual internal validation of each device is time-consuming. The aim of this study was to validate a new technique capable of testing two devices simultaneously, based on the International protocol of the European Society of Hypertension.