Systematic evaluation of risk factors for diagnostic delay in inflammatory bowel

Aim: The diagnosis of inflammatory bowel disease (IBD), comprising Crohn's disease (CD) and ulcerative colitis (UC), continues to present difficulties due to unspecific symptoms and limited test accuracies. We aimed to determine the diagnostic delay (time from first symptoms to IBD diagnosis) and to identify associated risk factors in a national cohort in Switzerland.¦Materials and Methods: A total of 1,591 IBD patients (932 CD, 625 UC, 34 indeterminate colitis) from the Swiss IBD cohort study (SIBDCS) were evaluated. The SIBDCS collects data on a large sample of IBD patients from hospitals and private practice across Switzerland through physician and patient questionnaires. The primary outcome measure was the diagnostic delay.¦Results: Diagnostic delay in CD patients was significantly longer compared to UC patients (median 9 vs. 4 months, P < 0.001). Seventy-five percent of CD patients were diagnosed within 24 months compared to 12 months for UC and 6 months for IC patients. Multivariate logistic regression identified age <40 years at diagnosis (OR 2.15, P = 0.010) and ileal disease (OR 1.69, P = 0.025) as independent risk factors for long diagnostic delay in CD (>24 months). A trend for long diagnostic delay (>12 months) was associated with NSAID intake (OR 1.75, P = 0.093) and male gender (OR 0.59, P = 0.079) in UC patients.¦Conclusions: Whereas the median delay for diagnosing CD, UC, and IC seems to be acceptable, there exists a long delay in a considerable proportion of CD patients. More public awareness work needs to be done in order to reduce patient's and doctor's delay in this target population.

Active Learning of Very-High Resolution Optical Imagery with SVM: Entropy vs Margin Sampling

An active learning method is proposed for the semi-automatic selection of training sets in remote sensing image classification. The method adds iteratively to the current training set the unlabeled pixels for which the prediction of an ensemble of classifiers based on bagged training sets show maximum entropy. This way, the algorithm selects the pixels that are the most uncertain and that will improve the model if added in the training set. The user is asked to label such pixels at each iteration. Experiments using support vector machines (SVM) on an 8 classes QuickBird image show the excellent performances of the methods, that equals accuracies of both a model trained with ten times more pixels and a model whose training set has been built using a state-of-the-art SVM specific active learning method

Coronary MR angiography: comparison of quantitative and qualitative data from four techniques.

OBJECTIVE: The optimal coronary MR angiography sequence has yet to be determined. We sought to quantitatively and qualitatively compare four coronary MR angiography sequences. SUBJECTS AND METHODS. Free-breathing coronary MR angiography was performed in 12 patients using four imaging sequences (turbo field-echo, fast spin-echo, balanced fast field-echo, and spiral turbo field-echo). Quantitative comparisons, including signal-to-noise ratio, contrast-to-noise ratio, vessel diameter, and vessel sharpness, were performed using a semiautomated analysis tool. Accuracy for detection of hemodynamically significant disease (> 50%) was assessed in comparison with radiographic coronary angiography. RESULTS: Signal-to-noise and contrast-to-noise ratios were markedly increased using the spiral (25.7 +/- 5.7 and 15.2 +/- 3.9) and balanced fast field-echo (23.5 +/- 11.7 and 14.4 +/- 8.1) sequences compared with the turbo field-echo (12.5 +/- 2.7 and 8.3 +/- 2.6) sequence (p < 0.05). Vessel diameter was smaller with the spiral sequence (2.6 +/- 0.5 mm) than with the other techniques (turbo field-echo, 3.0 +/- 0.5 mm, p = 0.6; balanced fast field-echo, 3.1 +/- 0.5 mm, p < 0.01; fast spin-echo, 3.1 +/- 0.5 mm, p < 0.01). Vessel sharpness was highest with the balanced fast field-echo sequence (61.6% +/- 8.5% compared with turbo field-echo, 44.0% +/- 6.6%; spiral, 44.7% +/- 6.5%; fast spin-echo, 18.4% +/- 6.7%; p < 0.001). The overall accuracies of the sequences were similar (range, 74% for turbo field-echo, 79% for spiral). Scanning time for the fast spin-echo sequences was longest (10.5 +/- 0.6 min), and for the spiral acquisitions was shortest (5.2 +/- 0.3 min). CONCLUSION: Advantages in signal-to-noise and contrast-to-noise ratios, vessel sharpness, and the qualitative results appear to favor spiral and balanced fast field-echo coronary MR angiography sequences, although subjective accuracy for the detection of coronary artery disease was similar to that of other sequences.

Ultra-high pressure liquid chromatography-mass spectrometry for plant metabolomics: a systematic comparison of high-resolution quadrupole-time-of-flight and single stage Orbitrap mass spectrometers.

The response of Arabidopsis to stress caused by mechanical wounding was chosen as a model to compare the performances of high resolution quadrupole-time-of-flight (Q-TOF) and single stage Orbitrap (Exactive Plus) mass spectrometers in untargeted metabolomics. Both instruments were coupled to ultra-high pressure liquid chromatography (UHPLC) systems set under identical conditions. The experiment was divided in two steps: the first analyses involved sixteen unwounded plants, half of which were spiked with pure standards that are not present in Arabidopsis. The second analyses compared the metabolomes of mechanically wounded plants to unwounded plants. Data from both systems were extracted using the same feature detection software and submitted to unsupervised and supervised multivariate analysis methods. Both mass spectrometers were compared in terms of number and identity of detected features, capacity to discriminate between samples, repeatability and sensitivity. Although analytical variability was lower for the UHPLC-Q-TOF, generally the results for the two detectors were quite similar, both of them proving to be highly efficient at detecting even subtle differences between plant groups. Overall, sensitivity was found to be comparable, although the Exactive Plus Orbitrap provided slightly lower detection limits for specific compounds. Finally, to evaluate the potential of the two mass spectrometers for the identification of unknown markers, mass and spectral accuracies were calculated on selected identified compounds. While both instruments showed excellent mass accuracy (<2.5ppm for all measured compounds), better spectral accuracy was recorded on the Q-TOF. Taken together, our results demonstrate that comparable performances can be obtained at acquisition frequencies compatible with UHPLC on Q-TOF and Exactive Plus MS, which may thus be equivalently used for plant metabolomics.

Prediction of postpartum depression using multilayer perceptrons and pruning.

OBJECTIVE. The main goal of this paper is to obtain a classification model based on feed-forward multilayer perceptrons in order to improve postpartum depression prediction during the 32 weeks after childbirth with a high sensitivity and specificity and to develop a tool to be integrated in a decision support system for clinicians. MATERIALS AND METHODS. Multilayer perceptrons were trained on data from 1397 women who had just given birth, from seven Spanish general hospitals, including clinical, environmental and genetic variables. A prospective cohort study was made just after delivery, at 8 weeks and at 32 weeks after delivery. The models were evaluated with the geometric mean of accuracies using a hold-out strategy. RESULTS. Multilayer perceptrons showed good performance (high sensitivity and specificity) as predictive models for postpartum depression. CONCLUSIONS. The use of these models in a decision support system can be clinically evaluated in future work. The analysis of the models by pruning leads to a qualitative interpretation of the influence of each variable in the interest of clinical protocols.

Commercial enzyme-linked immunosorbent assay versuspolymerase chain reaction for the diagnosis of chronic Chagas disease: a systematic review and meta-analysis

Chronic Chagas disease diagnosis relies on laboratory tests due to its clinical characteristics. The aim of this research was to review commercial enzyme-linked immunosorbent assay (ELISA) and polymerase chain reaction (PCR) diagnostic test performance. Performance of commercial ELISA or PCR for the diagnosis of chronic Chagas disease were systematically searched in PubMed, Scopus, Embase, ISI Web, and LILACS through the bibliography from 1980-2014 and by contact with the manufacturers. The risk of bias was assessed with QUADAS-2. Heterogeneity was estimated with the I2 statistic. Accuracies provided by the manufacturers usually overestimate the accuracy provided by academia. The risk of bias is high in most tests and in most QUADAS dimensions. Heterogeneity is high in either sensitivity, specificity, or both. The evidence regarding commercial ELISA and ELISA-rec sensitivity and specificity indicates that there is overestimation. The current recommendation to use two simultaneous serological tests can be supported by the risk of bias analysis and the amount of heterogeneity but not by the observed accuracies. The usefulness of PCR tests are debatable and health care providers should not order them on a routine basis. PCR may be used in selected cases due to its potential to detect seronegative subjects.

Diseño, implementación y validación de un sistema de localización híbrido basado en una red de sensores inalámbricos (WSN)

Aquest projecte estudia la implementació d’un sistema de localització híbrid amb la combinació del posicionament GPS y el posicionament obtingut mitjançant mesures de potència rebuda (RSS) utilitzant una xarxa de sensors sense fils (WSN). Inicialment s’analitzen les característiques principals de les WSN y les tècniques de posicionament GPS y RSS. A continuació es proposen tècniques de localització híbrides que combinen el posicionament bàsic brindat per la WSN (GPS y RSS)per obtenir posicionament tant en escenaris interiors com exteriors a més d’obtenir una precisió major que les precisions bàsiques. Una vegada s’han analitzat els conceptes bàsics y s’han proposat les tècniques a utilitzar en el sistema de localització híbrida s’expliquen els aspectes d’implementació relacionats amb la programació de la WSN. Finalment, després d’analitzar els resultats de diverses mesures, queda present la necessitat de tècniques d’estimació d’error en el posicionament, per això es proposa una tècnica d’estimació d’error per ser utilitzada en les estimacions híbrides y obtenir així el funcionament desitjat de les tècniques híbrides.

Predictability of music descriptor time series and its application to cover song detection

Intuitively, music has both predictable and unpredictable components. In this work we assess this qualitative statement in a quantitative way using common time series models fitted to state-of-the-art music descriptors. These descriptors cover different musical facets and are extracted from a large collection of real audio recordings comprising a variety of musical genres. Our findings show that music descriptor time series exhibit a certain predictability not only for short time intervals, but also for mid-term and relatively long intervals. This fact is observed independently of the descriptor, musical facet and time series model we consider. Moreover, we show that our findings are not only of theoretical relevance but can also have practical impact. To this end we demonstrate that music predictability at relatively long time intervals can be exploited in a real-world application, namely the automatic identification of cover songs (i.e. different renditions or versions of the same musical piece). Importantly, this prediction strategy yields a parameter-free approach for cover song identification that is substantially faster, allows for reduced computational storage and still maintains highly competitive accuracies when compared to state-of-the-art systems.

Diagnostic Performance of Magnetic Resonance Imaging and Computed Tomography for Advanced Retinoblastoma: A Systematic Review and Meta-analysis.

PURPOSE: To determine and compare the diagnostic performance of magnetic resonance imaging (MRI) and computed tomography (CT) for the diagnosis of tumor extent in advanced retinoblastoma, using histopathologic analysis as the reference standard. DESIGN: Systematic review and meta-analysis. PARTICIPANTS: Patients with advanced retinoblastoma who underwent MRI, CT, or both for the detection of tumor extent from published diagnostic accuracy studies. METHODS: Medline and Embase were searched for literature published through April 2013 assessing the diagnostic performance of MRI, CT, or both in detecting intraorbital and extraorbital tumor extension of retinoblastoma. Diagnostic accuracy data were extracted from included studies. Summary estimates were based on a random effects model. Intrastudy and interstudy heterogeneity were analyzed. MAIN OUTCOME MEASURES: Sensitivity and specificity of MRI and CT in detecting tumor extent. RESULTS: Data of the following tumor-extent parameters were extracted: anterior eye segment involvement and ciliary body, optic nerve, choroidal, and (extra)scleral invasion. Articles on MRI reported results of 591 eyes from 14 studies, and articles on CT yielded 257 eyes from 4 studies. The summary estimates with their 95% confidence intervals (CIs) of the diagnostic accuracy of conventional MRI at detecting postlaminar optic nerve, choroidal, and scleral invasion showed sensitivities of 59% (95% CI, 37%-78%), 74% (95% CI, 52%-88%), and 88% (95% CI, 20%-100%), respectively, and specificities of 94% (95% CI, 84%-98%), 72% (95% CI, 31%-94%), and 99% (95% CI, 86%-100%), respectively. Magnetic resonance imaging with a high (versus a low) image quality showed higher diagnostic accuracies for detection of prelaminar optic nerve and choroidal invasion, but these differences were not statistically significant. Studies reporting the diagnostic accuracy of CT did not provide enough data to perform any meta-analyses. CONCLUSIONS: Magnetic resonance imaging is an important diagnostic tool for the detection of local tumor extent in advanced retinoblastoma, although its diagnostic accuracy shows room for improvement, especially with regard to sensitivity. With only a few-mostly old-studies, there is very little evidence on the diagnostic accuracy of CT, and generally these studies show low diagnostic accuracy. Future studies assessing the role of MRI in clinical decision making in terms of prognostic value for advanced retinoblastoma are needed.

Variability of voriconazole plasma levels measured by new high-performance liquid chromatography and bioassay methods.

Voriconazole (VRC) is a broad-spectrum antifungal triazole with nonlinear pharmacokinetics. The utility of measurement of voriconazole blood levels for optimizing therapy is a matter of debate. Available high-performance liquid chromatography (HPLC) and bioassay methods are technically complex, time-consuming, or have a narrow analytical range. Objectives of the present study were to develop new, simple analytical methods and to assess variability of voriconazole blood levels in patients with invasive mycoses. Acetonitrile precipitation, reverse-phase separation, and UV detection were used for HPLC. A voriconazole-hypersusceptible Candida albicans mutant lacking multidrug efflux transporters (cdr1Delta/cdr1Delta, cdr2Delta/cdr2Delta, flu1Delta/flu1Delta, and mdr1Delta/mdr1Delta) and calcineurin subunit A (cnaDelta/cnaDelta) was used for bioassay. Mean intra-/interrun accuracies over the VRC concentration range from 0.25 to 16 mg/liter were 93.7% +/- 5.0%/96.5% +/- 2.4% (HPLC) and 94.9% +/- 6.1%/94.7% +/- 3.3% (bioassay). Mean intra-/interrun coefficients of variation were 5.2% +/- 1.5%/5.4% +/- 0.9% and 6.5% +/- 2.5%/4.0% +/- 1.6% for HPLC and bioassay, respectively. The coefficient of concordance between HPLC and bioassay was 0.96. Sequential measurements in 10 patients with invasive mycoses showed important inter- and intraindividual variations of estimated voriconazole area under the concentration-time curve (AUC): median, 43.9 mg x h/liter (range, 12.9 to 71.1) on the first and 27.4 mg x h/liter (range, 2.9 to 93.1) on the last day of therapy. During therapy, AUC decreased in five patients, increased in three, and remained unchanged in two. A toxic encephalopathy probably related to the increase of the VRC AUC (from 71.1 to 93.1 mg x h/liter) was observed. The VRC AUC decreased (from 12.9 to 2.9 mg x h/liter) in a patient with persistent signs of invasive aspergillosis. These preliminary observations suggest that voriconazole over- or underexposure resulting from variability of blood levels might have clinical implications. Simple HPLC and bioassay methods offer new tools for monitoring voriconazole therapy.

Individual Classification of Mild Cognitive Impairment Subtypes by Support Vector Machine Analysis of White Matter DTI.

BACKGROUND AND PURPOSE: MCI was recently subdivided into sd-aMCI, sd-fMCI, and md-aMCI. The current investigation aimed to discriminate between MCI subtypes by using DTI. MATERIALS AND METHODS: Sixty-six prospective participants were included: 18 with sd-aMCI, 13 with sd-fMCI, and 35 with md-aMCI. Statistics included group comparisons using TBSS and individual classification using SVMs. RESULTS: The group-level analysis revealed a decrease in FA in md-aMCI versus sd-aMCI in an extensive bilateral, right-dominant network, and a more pronounced reduction of FA in md-aMCI compared with sd-fMCI in right inferior fronto-occipital fasciculus and inferior longitudinal fasciculus. The comparison between sd-fMCI and sd-aMCI, as well as the analysis of the other diffusion parameters, yielded no significant group differences. The individual-level SVM analysis provided discrimination between the MCI subtypes with accuracies around 97%. The major limitation is the relatively small number of cases of MCI. CONCLUSIONS: Our data show that, at the group level, the md-aMCI subgroup has the most pronounced damage in white matter integrity. Individually, SVM analysis of white matter FA provided highly accurate classification of MCI subtypes.

Take-the-best and other simple strategies: Why and when they work 'well' in binary choice

The effectiveness of decision rules depends on characteristics of bothrules and environments. A theoretical analysis of environments specifiesthe relative predictive accuracies of the lexicographic rule 'take-the-best'(TTB) and other simple strategies for binary choice. We identify threefactors: how the environment weights variables; characteristics of choicesets; and error. For cases involving from three to five binary cues, TTBis effective across many environments. However, hybrids of equal weights(EW) and TTB models are more effective as environments become morecompensatory. In the presence of error, TTB and similar models do not predictmuch better than a naïve model that exploits dominance. We emphasizepsychological implications and the need for more complete theories of theenvironment that include the role of error.

Reference Cluster Normalization Improves Detection of Frontotemporal Lobar Degeneration by Means of FDG-PET.

Positron emission tomography with [18F] fluorodeoxyglucose (FDG-PET) plays a well-established role in assisting early detection of frontotemporal lobar degeneration (FTLD). Here, we examined the impact of intensity normalization to different reference areas on accuracy of FDG-PET to discriminate between patients with mild FTLD and healthy elderly subjects. FDG-PET was conducted at two centers using different acquisition protocols: 41 FTLD patients and 42 controls were studied at center 1, 11 FTLD patients and 13 controls were studied at center 2. All PET images were intensity normalized to the cerebellum, primary sensorimotor cortex (SMC), cerebral global mean (CGM), and a reference cluster with most preserved FDG uptake in the aforementioned patients group of center 1. Metabolic deficits in the patient group at center 1 appeared 1.5, 3.6, and 4.6 times greater in spatial extent, when tracer uptake was normalized to the reference cluster rather than to the cerebellum, SMC, and CGM, respectively. Logistic regression analyses based on normalized values from FTLD-typical regions showed that at center 1, cerebellar, SMC, CGM, and cluster normalizations differentiated patients from controls with accuracies of 86%, 76%, 75% and 90%, respectively. A similar order of effects was found at center 2. Cluster normalization leads to a significant increase of statistical power in detecting early FTLD-associated metabolic deficits. The established FTLD-specific cluster can be used to improve detection of FTLD on a single case basis at independent centers - a decisive step towards early diagnosis and prediction of FTLD syndromes enabling specific therapies in the future.

Three-dimensional ordered-subset expectation maximization iterative protocol for evaluation of left ventricular volumes and function by quantitative gated SPECT: a dynamic phantom study.

The purposes of this study were to characterize the performance of a 3-dimensional (3D) ordered-subset expectation maximization (OSEM) algorithm in the quantification of left ventricular (LV) function with (99m)Tc-labeled agent gated SPECT (G-SPECT), the QGS program, and a beating-heart phantom and to optimize the reconstruction parameters for clinical applications. METHODS: A G-SPECT image of a dynamic heart phantom simulating the beating left ventricle was acquired. The exact volumes of the phantom were known and were as follows: end-diastolic volume (EDV) of 112 mL, end-systolic volume (ESV) of 37 mL, and stroke volume (SV) of 75 mL; these volumes produced an LV ejection fraction (LVEF) of 67%. Tomographic reconstructions were obtained after 10-20 iterations (I) with 4, 8, and 16 subsets (S) at full width at half maximum (FWHM) gaussian postprocessing filter cutoff values of 8-15 mm. The QGS program was used for quantitative measurements. RESULTS: Measured values ranged from 72 to 92 mL for EDV, from 18 to 32 mL for ESV, and from 54 to 63 mL for SV, and the calculated LVEF ranged from 65% to 76%. Overall, the combination of 10 I, 8 S, and a cutoff filter value of 10 mm produced the most accurate results. The plot of the measures with respect to the expectation maximization-equivalent iterations (I x S product) revealed a bell-shaped curve for the LV volumes and a reverse distribution for the LVEF, with the best results in the intermediate range. In particular, FWHM cutoff values exceeding 10 mm affected the estimation of the LV volumes. CONCLUSION: The QGS program is able to correctly calculate the LVEF when used in association with an optimized 3D OSEM algorithm (8 S, 10 I, and FWHM of 10 mm) but underestimates the LV volumes. However, various combinations of technical parameters, including a limited range of I and S (80-160 expectation maximization-equivalent iterations) and low cutoff values (< or =10 mm) for the gaussian postprocessing filter, produced results with similar accuracies and without clinically relevant differences in the LV volumes and the estimated LVEF.

Performance of the 47-Kilodalton Membrane Protein versus DNA Polymerase I Genes for Detection of Treponema pallidum by PCR in Ulcers.

Treponema pallidum PCR (Tp-PCR) is a direct diagnostic method for primary and secondary syphilis, but there is no recommendation regarding the best choice of target gene. In this study, we sequentially tested 272 specimens from patients with sexually transmitted ulcers using Tp-PCR targeting the tpp47 and then polA genes. The two methods showed similar accuracies and an almost-perfect agreement.