163 resultados para diagnostic-accuracy


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Aim: To explore weight status perception and its relation to actual weight status in a contemporary cohort of 5- to 17-year-old children and adolescents. Methods: Body mass index (BMI), derived from height and weight measurements, and perception of weight status (‘too thin’, ‘about right’ and ‘too fat’) were evaluated in 3043 participants from the Healthy Kids Queensland Survey. In children less than 12 years of age, weight status perception was obtained from the parents, whereas the adolescents self-reported their perceived weight status. Results: Compared with measured weight status by established BMI cut-offs, just over 20% of parents underestimated their child's weight status and only 1% overestimated. Adolescent boys were more likely to underestimate their weight status compared with girls (26.4% vs. 10.2%, P < 0.05) whereas adolescent girls were more likely to overestimate than underestimate (11.8% vs. 3.4%, P < 0.05). Underestimation was greater by parents of overweight children compared with those of obese children, but still less than 50% of parents identified their obese child as ‘too fat’. There was greater recognition of overweight status in the adolescents, with 83% of those who were obese reporting they were ‘too fat’. Conclusion: Whilst there was a high degree of accuracy of weight status perception in those of healthy weight, there was considerable underestimation of weight status, particularly by parents of children who were overweight or obese. Strategies are required that enable parents to identify what a healthy weight looks like and help them understand when intervention is needed to prevent further weight gain as the child gets older.

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This is the first report of an antibody-fusion protein expressed in transgenic plants for direct use in a medical diagnostic assay. By the use of gene constructs with appropriate promoters, high level expression of an anti-glycophorin single-chain antibody fused to an epitope of the HIV virus was obtained in the leaves and stems of tobacco, tubers of potato and seed of barley. This fusion protein replaces the SimpliRED™ diagnostic reagent, used for detecting the presence of HIV-1 antibodies in human blood. The reagent is expensive and laborious to produce by conventional means since chemical modifications to a monoclonal antibody are required. The plant-produced fusion protein was fully functional (by ELISA) in crude extracts and, for tobacco at least, could be used without further purification in the HIV agglutination assay. All three crop species produced sufficient reagent levels to be superior bioreactors to bacteria or mice, however barley grain was the most attractive bioreactor as it expressed the highest level (150 μg of reagent g-1), is inexpensive to produce and harvest, poses a minuscule gene flow problem in the field, and the activity of the reagent is largely undiminished in stored grain. This work suggests that barley seed will be an ideal factory for the production of antibodies, diagnostic immunoreagents, vaccines and other pharmaceutical proteins.

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The coupling of kurtosis based-indexes and envelope analysis represents one of the most successful and widespread procedures for the diagnostics of incipient faults on rolling element bearings. Kurtosis-based indexes are often used to select the proper demodulation band for the application of envelope-based techniques. Kurtosis itself, in slightly different formulations, is applied for the prognostic and condition monitoring of rolling element bearings, as a standalone tool for a fast indication of the development of faults. This paper shows for the first time the strong analytical connection which holds for these two families of indexes. In particular, analytical identities are shown for the squared envelope spectrum (SES) and the kurtosis of the corresponding band-pass filtered analytic signal. In particular, it is demonstrated how the sum of the peaks in the SES corresponds to the raw 4th order moment. The analytical results show as well a link with an another signal processing technique: the cepstrum pre-whitening, recently used in bearing diagnostics. The analytical results are the basis for the discussion on an optimal indicator for the choice of the demodulation band, the ratio of cyclic content (RCC), which endows the kurtosis with selectivity in the cyclic frequency domain and whose performance is compared with more traditional kurtosis-based indicators such as the protrugram. A benchmark, performed on numerical simulations and experimental data coming from two different test-rigs, proves the superior effectiveness of such an indicator. Finally a short introduction to the potential offered by the newly proposed index in the field of prognostics is given in an additional experimental example. In particular the RCC is tested on experimental data collected on an endurance bearing test-rig, showing its ability to follow the development of the damage with a single numerical index.

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The diagnostics of mechanical components operating in transient conditions is still an open issue, in both research and industrial field. Indeed, the signal processing techniques developed to analyse stationary data are not applicable or are affected by a loss of effectiveness when applied to signal acquired in transient conditions. In this paper, a suitable and original signal processing tool (named EEMED), which can be used for mechanical component diagnostics in whatever operating condition and noise level, is developed exploiting some data-adaptive techniques such as Empirical Mode Decomposition (EMD), Minimum Entropy Deconvolution (MED) and the analytical approach of the Hilbert transform. The proposed tool is able to supply diagnostic information on the basis of experimental vibrations measured in transient conditions. The tool has been originally developed in order to detect localized faults on bearings installed in high speed train traction equipments and it is more effective to detect a fault in non-stationary conditions than signal processing tools based on spectral kurtosis or envelope analysis, which represent until now the landmark for bearings diagnostics.

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The signal processing techniques developed for the diagnostics of mechanical components operating in stationary conditions are often not applicable or are affected by a loss of effectiveness when applied to signals measured in transient conditions. In this chapter, an original signal processing tool is developed exploiting some data-adaptive techniques such as Empirical Mode Decomposition, Minimum Entropy Deconvolution and the analytical approach of the Hilbert transform. The tool has been developed to detect localized faults on bearings of traction systems of high speed trains and it is more effective to detect a fault in non-stationary conditions than signal processing tools based on envelope analysis or spectral kurtosis, which represent until now the landmark for bearings diagnostics.

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In the field of rolling element bearing diagnostics, envelope analysis has gained in the last years a leading role among the different digital signal processing techniques. The original constraint of constant operating speed has been relaxed thanks to the combination of this technique with the computed order tracking, able to resample signals at constant angular increments. In this way, the field of application of this technique has been extended to cases in which small speed fluctuations occur, maintaining high effectiveness and efficiency. In order to make this algorithm suitable to all industrial applications, the constraint on speed has to be removed completely. In fact, in many applications, the coincidence of high bearing loads, and therefore high diagnostic capability, with acceleration-deceleration phases represents a further incentive in this direction. This chapter presents a procedure for the application of envelope analysis to speed transients. The effect of load variation on the proposed technique will be also qualitatively addressed.

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This study aimed to determine if systematic variation of the diagnostic terminology embedded within written discharge information (i.e., concussion or mild traumatic brain injury, mTBI) would produce different expected symptoms and illness perceptions. We hypothesized that compared to concussion advice, mTBI advice would be associated with worse outcomes. Sixty-two volunteers with no history of brain injury or neurological disease were randomly allocated to one of two conditions in which they read a mTBI vignette followed by information that varied only by use of the embedded terms concussion (n = 28) or mTBI (n = 34). Both groups reported illness perceptions (timeline and consequences subscale of the Illness Perception Questionnaire-Revised) and expected Postconcussion Syndrome (PCS) symptoms 6 months post injury (Neurobehavioral Symptom Inventory, NSI). Statistically significant group differences due to terminology were found on selected NSI scores (i.e., total, cognitive and sensory symptom cluster scores (concussion > mTBI)), but there was no effect of terminology on illness perception. When embedded in discharge advice, diagnostic terminology affects some but not all expected outcomes. Given that such expectations are a known contributor to poor mTBI outcome, clinicians should consider the potential impact of varied terminology on their patients.

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Background and aims: The assessment of intra-epidermal nerve fiber density (IENFD) in skin biopsies and corneal nerve fiber density (CNFD) using corneal confocal microscopy (CCM) provides promising techniques to detect small nerve fiber damage in patients with peripheral neuropathy. To help define the clinical utility of each of these techniques in patients with diabetic neuropathy we have assessed sensitivity and specificity of IENFD and CNFD in predicting the following: 1) diabetic polyneuropathy (DPN); 2) risk of foot ulceration (RFU); 3) initial small fiber neuropathy (iSFN); 4) severe small fiber neuropathy (sSFN)...

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The study examined the accuracy of maternal perceived child weight. Urban-affluent mothers with 111 children aged 2-5 years were recruited. Nearly a quarter of mothers overestimated their underweight child as healthyweight and all overweight/obese children were perceived as healthyweight. Mothers therefore were unable to recognize their child’s true weight status.

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This study used automated data processing techniques to calculate a set of novel treatment plan accuracy metrics, and investigate their usefulness as predictors of quality assurance (QA) success and failure. 151 beams from 23 prostate and cranial IMRT treatment plans were used in this study. These plans had been evaluated before treatment using measurements with a diode array system. The TADA software suite was adapted to allow automatic batch calculation of several proposed plan accuracy metrics, including mean field area, small-aperture, off-axis and closed-leaf factors. All of these results were compared the gamma pass rates from the QA measurements and correlations were investigated. The mean field area factor provided a threshold field size (5 cm2, equivalent to a 2.2 x 2.2 cm2 square field), below which all beams failed the QA tests. The small aperture score provided a useful predictor of plan failure, when averaged over all beams, despite being weakly correlated with gamma pass rates for individual beams. By contrast, the closed leaf and off-axis factors provided information about the geometric arrangement of the beam segments but were not useful for distinguishing between plans that passed and failed QA. This study has provided some simple tests for plan accuracy, which may help minimise time spent on QA assessments of treatments that are unlikely to pass.

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Objective To evaluate the effects of Optical Character Recognition (OCR) on the automatic cancer classification of pathology reports. Method Scanned images of pathology reports were converted to electronic free-text using a commercial OCR system. A state-of-the-art cancer classification system, the Medical Text Extraction (MEDTEX) system, was used to automatically classify the OCR reports. Classifications produced by MEDTEX on the OCR versions of the reports were compared with the classification from a human amended version of the OCR reports. Results The employed OCR system was found to recognise scanned pathology reports with up to 99.12% character accuracy and up to 98.95% word accuracy. Errors in the OCR processing were found to minimally impact on the automatic classification of scanned pathology reports into notifiable groups. However, the impact of OCR errors is not negligible when considering the extraction of cancer notification items, such as primary site, histological type, etc. Conclusions The automatic cancer classification system used in this work, MEDTEX, has proven to be robust to errors produced by the acquisition of freetext pathology reports from scanned images through OCR software. However, issues emerge when considering the extraction of cancer notification items.

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The follicular variant of papillary thyroid carcinoma (FVPTC) presents a type of papillary thyroid cancer that has created continuous diagnosis and treatment controversies among clinicians and pathologists. In this review, we describe the nomenclature, the clinical features, diagnostic problems and the molecular biology of FVPTC. It is important for clinicians to understand this entity as the diagnosis and management of this group of patient may be different from other patients with conventional PTC. The literature suggests that FVPTC behaves in a way similar, clinically, to conventional papillary thyroid carcinoma. However, there are some genotypic differences which may characterise this neoplasm. These parameters may account for the phenotypic variation described by some scientists in this type of cancer. Further understanding can only be achieved by defining strict pathological criteria, in-depth study of the molecular biology and long term follow-up of the optional patients with FVPTC.

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A mine site water balance is important for communicating information to interested stakeholders, for reporting on water performance, and for anticipating and mitigating water-related risks through water use/demand forecasting. Gaining accuracy over the water balance is therefore crucial for sites to achieve best practice water management and to maintain their social license to operate. For sites that are located in high rainfall environments the water received to storage dams through runoff can represent a large proportion of the overall inputs to site; inaccuracies in these flows can therefore lead to inaccuracies in the overall site water balance. Hydrological models that estimate runoff flows are often incorporated into simulation models used for water use/demand forecasting. The Australian Water Balance Model (AWBM) is one example that has been widely applied in the Australian context. However, the calibration of AWBM in a mining context can be challenging. Through a detailed case study, we outline an approach that was used to calibrate and validate AWBM at a mine site. Commencing with a dataset of monitored dam levels, a mass balance approach was used to generate an observed runoff sequence. By incorporating a portion of this observed dataset into the calibration routine, we achieved a closer fit between the observed vs. simulated dataset compared with the base case. We conclude by highlighting opportunities for future research to improve the calibration fit through improving the quality of the input dataset. This will ultimately lead to better models for runoff prediction and thereby improve the accuracy of mine site water balances.

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BACKGROUND: Effective diagnosis of malaria is a major component of case management. Rapid diagnostic tests (RDTs) based on Plasmodium falciparumhistidine-rich protein 2 (PfHRP2) are popular for diagnosis of this most virulent malaria infection. However, concerns have been raised about the longevity of the PfHRP2 antigenaemia following curative treatment in endemic regions. METHODS: A model of PfHRP2 production and decay was developed to mimic the kinetics of PfHRP2 antigenaemia during infections. Data from two human infection studies was used to fit the model, and to investigate PfHRP2 kinetics. Four malaria RDTs were assessed in the laboratory to determine the minimum detectable concentration of PfHRP2. RESULTS: Fitting of the PfHRP2 dynamics model indicated that in malaria naive hosts, P. falciparum parasites of the 3D7 strain produce 1.4 x 10(-)(1)(3) g of PfHRP2 per parasite per replication cycle. The four RDTs had minimum detection thresholds between 6.9 and 27.8 ng/mL. Combining these detection thresholds with the kinetics of PfHRP2, it is predicted that as few as 8 parasites/muL may be required to maintain a positive RDT in a chronic infection. CONCLUSIONS: The results of the model indicate that good quality PfHRP2-based RDTs should be able to detect parasites on the first day of symptoms, and that the persistence of the antigen will cause the tests to remain positive for at least seven days after treatment. The duration of a positive test result following curative treatment is dependent on the duration and density of parasitaemia prior to treatment and the presence and affinity of anti-PfHRP2 antibodies.