Use of accuracy profile for the validation of a gas chromatography-negative chemical ionization tandem mass spectrometry method: quantification of ethyl glucuronide in hair

Introduction: Ethylglucuronide (EtG) is a direct and specific metabolite of ethanol. Its determination in hair is of increasing interest for detecting and monitoring alcohol abuse. The quantification of EtG in hair requires analytical methods showing highest sensitivity and specificity. We present a fully validated method based on gas chromatography-negative chemical ionization tandem mass spectrometry (GC-NCI-MS/MS). The method was validated using French Society of Pharmaceutical Sciences and Techniques (SFSTP) guidelines which are based on the determination of the total measurement error and accuracy profiles. Methods: Washed and powdered hair is extracted in water using an ultrasonic incubation. After purification by Oasis MAX solid phase extraction, the derivatized EtG is detected and quantified by GC-NCI-MS/MS method in the selected reaction monitoring mode. The transitions m/z 347 / 163 and m/z 347 / 119 were used for the quantification and identification of EtG. Four quality controls (QC) prepared with hair samples taken post mortem from 2 subjects with a known history of alcoholism were used. A proficiency test with 7 participating laboratories was first run to validate the EtG concentration of each QC sample. Considering the results of this test, these samples were then used as internal controls for validation of the method. Results: The mean EtG concentrations measured in the 4 QC were 259.4, 130.4, 40.8, and 8.4 pg/mg hair. Method validation has shown linearity between 8.4 and 259.4 pg/mg hair (r2 > 0.999). The lower limit of quantification was set up at 8.4 pg/mg. Repeatability and intermediate precision were found less than 13.2% for all concentrations tested. Conclusion: The method proved to be suitable for routine analysis of EtG in hair. GC-NCI-MS/MS method was then successfully applied to the analysis of EtG in hair samples collected from different alcohol consumers.

Acute imaging does not improve ASTRAL score's accuracy despite having a prognostic value.

BACKGROUND: The ASTRAL score was recently shown to reliably predict three-month functional outcome in patients with acute ischemic stroke. AIM: The study aims to investigate whether information from multimodal imaging increases ASTRAL score's accuracy. METHODS: All patients registered in the ASTRAL registry until March 2011 were included. In multivariate logistic-regression analyses, we added covariates derived from parenchymal, vascular, and perfusion imaging to the 6-parameter model of the ASTRAL score. If a specific imaging covariate remained an independent predictor of three-month modified Rankin score > 2, the area-under-the-curve (AUC) of this new model was calculated and compared with ASTRAL score's AUC. We also performed similar logistic regression analyses in arbitrarily chosen patient subgroups. RESULTS: When added to the ASTRAL score, the following covariates on admission computed tomography/magnetic resonance imaging-based multimodal imaging were not significant predictors of outcome: any stroke-related acute lesion, any nonstroke-related lesions, chronic/subacute stroke, leukoaraiosis, significant arterial pathology in ischemic territory on computed tomography angiography/magnetic resonance angiography/Doppler, significant intracranial arterial pathology in ischemic territory, and focal hypoperfusion on perfusion-computed tomography. The Alberta Stroke Program Early CT score on plain imaging and any significant extracranial arterial pathology on computed tomography angiography/magnetic resonance angiography/Doppler were independent predictors of outcome (odds ratio: 0·93, 95% CI: 0·87-0·99 and odds ratio: 1·49, 95% CI: 1·08-2·05, respectively) but did not increase ASTRAL score's AUC (0·849 vs. 0·850, and 0·8563 vs. 0·8564, respectively). In exploratory analyses in subgroups of different prognosis, age or stroke severity, no covariate was found to increase ASTRAL score's AUC, either. CONCLUSIONS: The addition of information derived from multimodal imaging does not increase ASTRAL score's accuracy to predict functional outcome despite having an independent prognostic value. More selected radiological parameters applied in specific subgroups of stroke patients may add prognostic value of multimodal imaging.

Pregnancy malaria: cryptic disease, apparent solution

Malaria during pregnancy can be severe in non-immune women, but in areas of stable transmission, where women are semi-immune and often asymptomatic during infection, malaria is an insidious cause of disease and death for mothers and their offspring. Sequelae, such as severe anaemia and hypertension in the mother and low birth weight and infant mortality in the offspring, are often not recognised as consequences of infection. Pregnancy malaria, caused by Plasmodium falciparum, is mediated by infected erythrocytes (IEs) that bind to chondroitin sulphate A and are sequestered in the placenta. These parasites have a unique adhesion phenotype and distinct antigenicity, which indicates that novel targets may be required for development of an effective vaccine. Women become resistant to malaria as they acquire antibodies against placental IE, which leads to higher haemoglobin levels and heavier babies. Proteins exported from the placental parasites have been identified, including both variant and conserved antigens, and some of these are in preclinical development for vaccines. A vaccine that prevents P. falciparum malaria in pregnant mothers is feasible and would potentially save hundreds of thousands of lives each year.

Validation of a modified fluorimetric assay for the screening of trichomonacidal drugs

A fluorimetric microassay that uses a redox dye to determine the viability of the flagellate Trichomonas vaginalis has been optimised to provide a more sensitive method to evaluate potential trichomonacidal compounds. Resazurin has been used in recent years to test drugs against different parasites, including trichomonadid protozoa; however, the reproducibility of these resazurin-based methods in our laboratory has been limited because the flagellate culture medium spontaneously reduces the resazurin. The objective of this work was to refine the fluorimetric microassay method previously developed by other research groups to reduce the fluorescence background generated by the media and increase the sensitivity of the screening assay. The experimental conditions, time of incubation, resazurin concentration and media used in the microtitre plates were adjusted. Different drug sensitivity studies against T. vaginalis were developed using the 5-nitroimidazole reference drugs, new 5-nitroindazolinones and 5-nitroindazole synthetic derivatives. Haemocytometer count results were compared with the resazurin assay using a 10% solution of 3 mM resazurin dissolved in phosphate buffered saline with glucose (1 mg/mL). The fluorimetric assay and the haemocytometer counts resulted in similar percentages of trichomonacidal activity in all the experiments, demonstrating that the fluorimetric microtitre assay has the necessary accuracy for high-throughput screening of new drugs against T. vaginalis.

Effective diagnosis of Alzheimer's disease by means of large margin-based methodology.

BACKGROUND Functional brain images such as Single-Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET) have been widely used to guide the clinicians in the Alzheimer's Disease (AD) diagnosis. However, the subjectivity involved in their evaluation has favoured the development of Computer Aided Diagnosis (CAD) Systems. METHODS It is proposed a novel combination of feature extraction techniques to improve the diagnosis of AD. Firstly, Regions of Interest (ROIs) are selected by means of a t-test carried out on 3D Normalised Mean Square Error (NMSE) features restricted to be located within a predefined brain activation mask. In order to address the small sample-size problem, the dimension of the feature space was further reduced by: Large Margin Nearest Neighbours using a rectangular matrix (LMNN-RECT), Principal Component Analysis (PCA) or Partial Least Squares (PLS) (the two latter also analysed with a LMNN transformation). Regarding the classifiers, kernel Support Vector Machines (SVMs) and LMNN using Euclidean, Mahalanobis and Energy-based metrics were compared. RESULTS Several experiments were conducted in order to evaluate the proposed LMNN-based feature extraction algorithms and its benefits as: i) linear transformation of the PLS or PCA reduced data, ii) feature reduction technique, and iii) classifier (with Euclidean, Mahalanobis or Energy-based methodology). The system was evaluated by means of k-fold cross-validation yielding accuracy, sensitivity and specificity values of 92.78%, 91.07% and 95.12% (for SPECT) and 90.67%, 88% and 93.33% (for PET), respectively, when a NMSE-PLS-LMNN feature extraction method was used in combination with a SVM classifier, thus outperforming recently reported baseline methods. CONCLUSIONS All the proposed methods turned out to be a valid solution for the presented problem. One of the advances is the robustness of the LMNN algorithm that not only provides higher separation rate between the classes but it also makes (in combination with NMSE and PLS) this rate variation more stable. In addition, their generalization ability is another advance since several experiments were performed on two image modalities (SPECT and PET).

Computer-assisted cup placement techniques in total hip arthroplasty improve accuracy of placement.

Malposition of the acetabular component during hip arthroplasty increases the occurrence of impingement, reduces range of motion, and increases the risk of dislocation and long-term wear. To prevent malpositioned hip implants, an increasing number of computer-assisted orthopaedic systems have been described, but their accuracy is not well established. The purpose of this study was to determine the reproducibility and accuracy of conventional versus computer-assisted techniques for positioning the acetabular component in total hip arthroplasty. Using a lateral approach, 150 cups were placed by 10 surgeons in 10 identical plastic pelvis models (freehand, with a mechanical guide, using computer assistance). Conditions for cup implantations were made to mimic the operating room situation. Preoperative planning was done from a computed tomography scan. The accuracy of cup abduction and anteversion was assessed with an electromagnetic system. Freehand placement revealed a mean accuracy of cup anteversion and abduction of 10 degrees and 3.5 degrees, respectively (maximum error, 35 degrees). With the cup positioner, these angles measured 8 degrees and 4 degrees (maximum error, 29.8 degrees), respectively, and using computer assistance, 1.5 degrees and 2.5 degrees degrees (maximum error, 8 degrees), respectively. Computer-assisted cup placement was an accurate and reproducible technique for total hip arthroplasty. It was more accurate than traditional methods of cup positioning.

Meta-analysis of diagnostic test accuracy in neurosurgical practice.

Comparative effectiveness research (CER) allows evidence to be evaluated on the effectiveness, benefits, and detriments of management options, diagnostic tests, or ways to deliver health care. This process can be achieved in different ways, such as with well-designed randomized controlled trials or by meta-analyses. Several medical subspecialties are increasingly using CER, but CER remains underused by the neurosurgical community. Meta-analysis is a highly accurate method that permits results from multiple well-designed research studies to be quantitatively compared. Meta-analysis can be performed in many settings, such as the evaluation of treatment or of a diagnostic test or prognostic factor. Meta-analyses of randomized controlled treatment trials are well known, but there is a paucity of papers describing the ways to perform a meta-analysis of a diagnostic test. The aim of this paper is to improve neurosurgeons' familiarity with the meta-analysis of diagnostic test accuracy by describing and detailing each stage leading to publication.

An axiomatic characterization of the strong constrained egalitarian solution

In this paper we axiomatize the strong constrained egalitarian solution (Dutta and Ray, 1991) over the class of weak superadditive games using constrained egalitarianism, order-consistency, and converse order-consistency. JEL classification: C71, C78. Keywords: Cooperative TU-game, strong constrained egalitarian solution, axiomatization.

Accuracy of mucocutaneous leishmaniasis diagnosis using polymerase chain reaction: systematic literature review and meta-analysis

The diagnosis of mucocutaneous leishmaniasis (MCL) is hampered by the absence of a gold standard. An accurate diagnosis is essential because of the high toxicity of the medications for the disease. This study aimed to assess the ability of polymerase chain reaction (PCR) to identify MCL and to compare these results with clinical research recently published by the authors. A systematic literature review based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses: the PRISMA Statement was performed using comprehensive search criteria and communication with the authors. A meta-analysis considering the estimates of the univariate and bivariate models was performed. Specificity near 100% was common among the papers. The primary reason for accuracy differences was sensitivity. The meta-analysis, which was only possible for PCR samples of lesion fragments, revealed a sensitivity of 71% [95% confidence interval (CI) = 0.59; 0.81] and a specificity of 93% (95% CI = 0.83; 0.98) in the bivariate model. The search for measures that could increase the sensitivity of PCR should be encouraged. The quality of the collected material and the optimisation of the amplification of genetic material should be prioritised.

Predictive accuracy and usefulness of calibration of the ESC SCORE in Switzerland.

BACKGROUND: Prevention of cardiovascular disease (CVD) at the individual level should rely on the assessment of absolute risk using population-specific risk tables. OBJECTIVE: To compare the predictive accuracy of the original and the calibrated SCORE functions regarding 10-year cardiovascular risk in Switzerland. DESIGN: Cross-sectional, population-based study (5773 participants aged 35-74 years). METHODS: The SCORE equation for low-risk countries was calibrated based on the Swiss CVD mortality rates and on the CVD risk factor levels from the study sample. The predicted number of CVD deaths after a 10-year period was computed from the original and the calibrated equations and from the observed cardiovascular mortality for 2003. RESULTS: According to the original and calibrated functions, 16.3 and 15.8% of men and 8.2 and 8.9% of women, respectively, had a 10-year CVD risk > or =5%. Concordance correlation coefficient between the two functions was 0.951 for men and 0.948 for women, both P<0.001. Both risk functions adequately predicted the 10-year cumulative number of CVD deaths: in men, 71 (original) and 74 (calibrated) deaths for 73 deaths when using the CVD mortality rates; in women, 44 (original), 45 (calibrated) and 45 (CVD mortality rates), respectively. Compared to the original function, the calibrated function classified more women and fewer men at high-risk. Moreover, the calibrated function gave better risk estimates among participants aged over 65 years. CONCLUSION: The original SCORE function adequately predicts CVD death in Switzerland, particularly for individuals aged less than 65 years. The calibrated function provides more reliable estimates for older individuals.

Possible solution of some essential zero problems in compositional data analysis

One of the tantalising remaining problems in compositional data analysis lies in how to deal with data sets in which there are components which are essential zeros. By anessential zero we mean a component which is truly zero, not something recorded as zero simply because the experimental design or the measuring instrument has not been sufficiently sensitive to detect a trace of the part. Such essential zeros occur inmany compositional situations, such as household budget patterns, time budgets,palaeontological zonation studies, ecological abundance studies. Devices such as nonzero replacement and amalgamation are almost invariably ad hoc and unsuccessful insuch situations. From consideration of such examples it seems sensible to build up amodel in two stages, the first determining where the zeros will occur and the secondhow the unit available is distributed among the non-zero parts. In this paper we suggest two such models, an independent binomial conditional logistic normal model and a hierarchical dependent binomial conditional logistic normal model. The compositional data in such modelling consist of an incidence matrix and a conditional compositional matrix. Interesting statistical problems arise, such as the question of estimability of parameters, the nature of the computational process for the estimation of both the incidence and compositional parameters caused by the complexity of the subcompositional structure, the formation of meaningful hypotheses, and the devising of suitable testing methodology within a lattice of such essential zero-compositional hypotheses. The methodology is illustrated by application to both simulated and real compositional data

Overcoming the rare species modelling paradox: test of a novel hierarchical framework with an Iberian endemic plant

Rare species have restricted geographic ranges, habitat specialization, and/or small population sizes. Datasets on rare species distribution usually have few observations, limited spatial accuracy and lack of valid absences; conversely they provide comprehensive views of species distributions allowing to realistically capture most of their realized environmental niche. Rare species are the most in need of predictive distribution modelling but also the most difficult to model. We refer to this contrast as the "rare species modelling paradox" and propose as a solution developing modelling approaches that deal with a sufficiently large set of predictors, ensuring that statistical models aren't overfitted. Our novel approach fulfils this condition by fitting a large number of bivariate models and averaging them with a weighted ensemble approach. We further propose that this ensemble forecasting is conducted within a hierarchic multi-scale framework. We present two ensemble models for a test species, one at regional and one at local scale, each based on the combination of 630 models. In both cases, we obtained excellent spatial projections, unusual when modelling rare species. Model results highlight, from a statistically sound approach, the effects of multiple drivers in a same modelling framework and at two distinct scales. From this added information, regional models can support accurate forecasts of range dynamics under climate change scenarios, whereas local models allow the assessment of isolated or synergistic impacts of changes in multiple predictors. This novel framework provides a baseline for adaptive conservation, management and monitoring of rare species at distinct spatial and temporal scales.

Improved accuracy of co-morbidity coding over time after the introduction of ICD-10 administrative data.

BACKGROUND: Co-morbidity information derived from administrative data needs to be validated to allow its regular use. We assessed evolution in the accuracy of coding for Charlson and Elixhauser co-morbidities at three time points over a 5-year period, following the introduction of the International Classification of Diseases, 10th Revision (ICD-10), coding of hospital discharges.METHODS: Cross-sectional time trend evaluation study of coding accuracy using hospital chart data of 3'499 randomly selected patients who were discharged in 1999, 2001 and 2003, from two teaching and one non-teaching hospital in Switzerland. We measured sensitivity, positive predictive and Kappa values for agreement between administrative data coded with ICD-10 and chart data as the 'reference standard' for recording 36 co-morbidities.RESULTS: For the 17 the Charlson co-morbidities, the sensitivity - median (min-max) - was 36.5% (17.4-64.1) in 1999, 42.5% (22.2-64.6) in 2001 and 42.8% (8.4-75.6) in 2003. For the 29 Elixhauser co-morbidities, the sensitivity was 34.2% (1.9-64.1) in 1999, 38.6% (10.5-66.5) in 2001 and 41.6% (5.1-76.5) in 2003. Between 1999 and 2003, sensitivity estimates increased for 30 co-morbidities and decreased for 6 co-morbidities. The increase in sensitivities was statistically significant for six conditions and the decrease significant for one. Kappa values were increased for 29 co-morbidities and decreased for seven.CONCLUSIONS: Accuracy of administrative data in recording clinical conditions improved slightly between 1999 and 2003. These findings are of relevance to all jurisdictions introducing new coding systems, because they demonstrate a phenomenon of improved administrative data accuracy that may relate to a coding 'learning curve' with the new coding system.