798 resultados para multidimensional screening
Resumo:
In this paper I consider the role of education poli-cies in redistribution of income when individuals differ in two aspects: ability and inherited wealth. I discuss the extent to which the rules that emerge in unidimensional settings apply also in the bidimen-sional setting considered in this paper. The main conclusion is that, subject to some qualifi cations, the same type of rules that determine optimal education policies when only ability heterogeneity is considered apply to the case where both parameters of heterogeneity are considered. The qualifi cations pertain to the implementation of the optimal alloca-tion of resources to education and not the way the optimal allocations fi rst- and second-best differ.
Resumo:
PURPOSES Geriatric problems frequently go undetected in older patients in emergency departments (EDs), thus increasing their risk of adverse outcomes. We evaluated a novel emergency geriatric screening (EGS) tool designed to detect geriatric problems. BASIC PROCEDURES The EGS tool consisted of short validated instruments used to screen 4 domains (cognition, falls, mobility, and activities of daily living). Emergency geriatric screening was introduced for ED patients 75 years or older throughout a 4-month period. We analyzed the prevalence of abnormal EGS and whether EGS increased the number of EGS-related diagnoses in the ED during the screening, as compared with a preceding control period. MAIN FINDINGS Emergency geriatric screening was performed on 338 (42.5%) of 795 patients presenting during screening. Emergency geriatric screening was unfeasible in 175 patients (22.0%) because of life-threatening conditions and was not performed in 282 (35.5%) for logistical reasons. Emergency geriatric screening took less than 5 minutes to perform in most (85.8%) cases. Among screened patients, 285 (84.3%) had at least 1 abnormal EGS finding. In 270 of these patients, at least 1 abnormal EGS finding did not result in a diagnosis in the ED and was reported for further workup to subsequent care. During screening, 142 patients (42.0%) had at least 1 diagnosis listed within the 4 EGS domains, significantly more than the 29.3% in the control period (odds ratio 1.75; 95% confidence interval, 1.34-2.29; P<.001). Emergency geriatric screening predicted nursing home admission after the in-hospital stay (odds ratio for ≥3 vs <3 abnormal domains 12.13; 95% confidence interval, 2.79-52.72; P=.001). PRINCIPAL CONCLUSIONS The novel EGS is feasible, identifies previously undetected geriatric problems, and predicts determinants of subsequent care.
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Myopathies are among the major causes of mortality in the world. There is no complete cure for this heterogeneous group of diseases, but a sensitive, specific, and fast diagnostic tool may improve therapy effectiveness. In this study, Raman spectroscopy is applied to discriminate between muscle mutants in Drosophila on the basis of associated changes at the molecular level. Raman spectra were collected from indirect flight muscles of mutants, upheld1 (up1), heldup(2) (hdp(2)), myosin heavy chain7 (Mhc7), actin88F(KM88) (Act88F(KM88)), upheld101 (up101), and Canton-S (CS) control group, for both 2 and 12 days old flies. Difference spectra (mutant minus control) of all the mutants showed an increase in nucleic acid and beta-sheet and/or random coil protein content along with a decrease in a-helix protein. Interestingly, the 12th day samples of up1 and Act88F(KM88) showed significantly higher levels of glycogen and carotenoids than CS. A principal components based linear discriminant analysis classification model was developed based on multidimensional Raman spectra, which classified the mutants according to their pathophysiology and yielded an overall accuracy of 97% and 93% for 2 and 12 days old flies, respectively. The up1 and Act88F(KM88) (nemaline-myopathy) mutants form a group that is clearly separated in a linear discriminant plane from up101 and hdp2 (cardiomyopathy) mutants. Notably, Raman spectra from a human sample with nemaline-myopathy formed a cluster with the corresponding Drosophila mutant (up1). In conclusion, this is the first demonstration in which myopathies, despite their heterogeneity, were screened on the basis of biochemical differences using Raman spectroscopy.
Resumo:
Computer simulators of real-world processes are often computationally expensive and require many inputs. The problem of the computational expense can be handled using emulation technology; however, highly multidimensional input spaces may require more simulator runs to train and validate the emulator. We aim to reduce the dimensionality of the problem by screening the simulators inputs for nonlinear effects on the output rather than distinguishing between negligible and active effects. Our proposed method is built upon the elementary effects (EE) method for screening and uses a threshold value to separate the inputs with linear and nonlinear effects. The technique is simple to implement and acts in a sequential way to keep the number of simulator runs down to a minimum, while identifying the inputs that have nonlinear effects. The algorithm is applied on a set of simulated examples and a rabies disease simulator where we observe run savings ranging between 28% and 63% compared with the batch EE method. Supplementary materials for this article are available online.
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Police services in a number of Australian states and overseas jurisdictions have begun to implement or consider random road-side drug testing of drivers. This paper outlines research conducted to provide an estimate of the extent of drug driving in a sample of Queensland drivers in regional, rural and metropolitan areas. Oral fluid samples were collected from 2657 Queensland motorists and screened for illicit substances including cannabis (delta 9 tetrahydrocannibinol [THC]), amphetamines, ecstasy, and cocaine. Overall, 3.8% of the sample (n = 101) screened positive for at least one illicit substance, although multiple drugs were identified in a sample of 23 respondents. The most common drugs detected in oral fluid were ecstasy (n = 53), and cannabis (n = 46) followed by amphetamines (n = 23). A key finding was that cannabis was confirmed as the most common self-reported drug combined with driving and that individuals who tested positive to any drug through oral fluid analysis were also more likely to report the highest frequency of drug driving. Furthermore, a comparison between drug vs. drink driving detection rates for one region of the study, revealed a higher detection rate for drug driving (3.8%) vs. drink driving (0.8%). This research provides evidence that drug driving is relatively prevalent on Queensland roads, and may in fact be more common than drink driving. This paper will further outline the study findings’ and present possible directions for future drug driving research.