Diagnostic algorithm for a validated displacement grading of pediatric supracondylar fractures.

Background: The first AO comprehensive pediatric long bone fracture classification system has been established following a structured path of development and validation with experienced pediatric surgeons. Methods: A follow-up series of agreement studies was applied to specify and evaluate a grading system for displacement of pediatric supracondylar fractures. An iterative process comprising an international group of 5 experienced pediatric surgeons (Phase 1) followed by a pragmatic multicenter agreement study involving 26 raters (Phase 2) was used. The last evaluations were conducted on a consecutive collection of 154 supracondylar fractures documented by standard anteroposterior and lateral radiographs. Results: Fractures were classified according to 1 of 4 grades: I = incomplete fracture with no or minimal displacement; II = Incomplete fracture with continuity of the posterior (extension fracture) or anterior cortex (flexion fracture); III = lack of bone continuity (broken cortex), but still some contact between the fracture planes; IV = complete fracture with no bone continuity (broken cortex), and no contact between the fracture planes. A diagnostic algorithm to support the practical application of the grading system in a clinical setting, as well as an aid using a circle placed over the capitellum was proposed. The overall kappa coefficients were 0.68 and 0.61 in the Phase 1 and Phase 2 studies, respectively. In the Phase 1 study, fracture grades I, II, III, and IV were classified with median accuracies of 91%, 82%, 83%, and 99.5%, respectively. Similar median accuracies of 86% (Grade I), 73% (Grade II), 83%(Grade III), and 92% were reported for the Phase 2 study. Reliability was high in distinguishing complete, unstable fractures from stable injuries [ie, kappa coefficients of 0.84 (Phase 1) and 0.83 (Phase 2) were calculated]; in Phase 2, surgeons' accuracies in classifying complete fractures were all above 85%. Conclusions: With clear and unambiguous definition, this new grading system for supracondylar fracture displacement has proved to be sufficiently reliable and accurate when applied by pediatric surgeons in the framework of clinical routine as well as research.

Marqueurs diagnostiques de la carence en fer: lequel choisir [Diagnostic markers of iron deficiency: which should we choose?].

Iron deficiency is generally investigated when faced with anemia, or with symptoms that could be related to iron deficiency without anemia. This simple disorder is easy to treat, provided that the diagnosis is correct. Several biological tests are available, but their interpretation is oftentimes problematic. Pre-analytical factors can interfere with measurements, normal values can change depending on suppliers, and, above all, results from different markers can be contradictory in some clinical situations. The aim of this article is to evaluate how the evolution of scientific knowledge and clinical trials can contribute to a better understanding and greater reliability in the diagnosis of iron deficiency.

Ophtalmologie orbitopathie dysthyroïdienne: du diagnostic au traitement

Mild to moderate forms of orbitopathy are common in auto-immune thyroid diseases, whereas severe forms are rare. Euthyroidism restoration, no smoking, and ocular local lubricants are necessary for all the patients. In case of mild orbitopathy, treatment by selenium is now indicated. Active forms of thyroid orbitopathy are better treated by IV steroids. Surgery is indicated in optic neuropathy resistant to steroids and in sequellar forms of the disease.

Fast Approximation of Nonlinearities for improving inversion algorithms of PNL mixtures and Wiener systems

This paper proposes a very fast method for blindly approximating a nonlinear mapping which transforms a sum of random variables. The estimation is surprisingly good even when the basic assumption is not satisfied.We use the method for providing a good initialization for inverting post-nonlinear mixtures and Wiener systems. Experiments show that the algorithm speed is strongly improved and the asymptotic performance is preserved with a very low extra computational cost.

ECIL-3 classical diagnostic procedures for the diagnosis of invasive fungal diseases in patients with leukaemia.

Invasive fungal diseases (IFDs) continue to cause considerable morbidity and mortality in patients with haematological malignancy. Diagnosis of IFD is difficult, with the sensitivity of the gold standard tests (culture and histopathology) often reported to be low, which may at least in part be due to sub-optimal sampling or subsequent handling in the routine microbiological laboratory. Therefore, a working group of the European Conference in Infections in Leukaemia was convened in 2009 with the task of reviewing the classical diagnostic procedures and providing recommendations for their optimal use. The recommendations were presented and approved at the ECIL-3 conference in September 2009. Although new serological and molecular tests are examined in separate papers, this review focuses on sample types, microscopy and culture procedures, antifungal susceptibility testing and imaging. The performance and limitations of these procedures are discussed and recommendations are provided on when and how to use them and how to interpret the results.

Coherency and sharpness measures by using ICA algorithms. An investigation for Alzheimer’s disease discrimination

In this paper, we present a comprehensive study of different Independent Component Analysis (ICA) algorithms for the calculation of coherency and sharpness of electroencephalogram (EEG) signals, in order to investigate the possibility of early detection of Alzheimer’s disease (AD). We found that ICA algorithms can help in the artifact rejection and noise reduction, improving the discriminative property of features in high frequency bands (specially in high alpha and beta ranges). In addition to different ICA algorithms, the optimum number of selected components is investigated, in order to help decision processes for future works.

Investigation of ICA algorithms for feature extraction of EEG signals in discrimination of Alzheimer disease

In this paper we present a quantitative comparisons of different independent component analysis (ICA) algorithms in order to investigate their potential use in preprocessing (such as noise reduction and feature extraction) the electroencephalogram (EEG) data for early detection of Alzhemier disease (AD) or discrimination between AD (or mild cognitive impairment, MCI) and age-match control subjects.

Diagnostic potential of neutrophil elastase inhibitor complex in the routine care of critically ill newborn infants.

It has been suggested that determination of the neutrophil elastase alpha1-proteinase inhibitor complex (E-alpha1PI) improves the diagnosis of bacterial infection in newborns. We evaluated the use of E-alpha1PI measurements in 143 newborns, consecutively admitted to a tertiary intensive care unit, employing a new random access assay and a sampling procedure that minimises post-collection artefacts. The 95% range for noninfected newborns was 20-110 microg/l up to the 5th day of life and 20-85 microg/l thereafter. The sensitivity as to the diagnosis of culture-proven bloodstream infection was 80% for E-alpha1PI, 86% for the immature to total neutrophil ratio, 64% for C-reactive protein and 37% for the total white blood cell count. The corresponding specificity amounted to 97%, 85%, 85% and 86%, respectively. E-alpha1PI increases preceded elevations of C-reactive protein by 18 h. Like C-reactive protein, E-alpha1PI levels did not distinguish between bloodstream infection and non-bacterial inflammatory responses. Results of E-alpha1PI became available within 1 h of collection and usually 2-3 h before manual leucocyte counts. CONCLUSION: Determination of neutrophil elastase alpha1-proteinase inhibitor levels yields diagnostic advantages comparable to those of manual differential counts but provide faster turnaround times.

Detection of hemorrhage source: the diagnostic value of post-mortem CT-angiography.

The aim of this study was to compare the diagnostic value of post-mortem computed tomography angiography (PMCTA) to conventional, ante-mortem computed tomography (CT)-scan, CT-angiography (CTA) and digital subtraction angiography (DSA) in the detection and localization of the source of bleeding in cases of acute hemorrhage with fatal outcomes. The medical records and imaging scans of nine individuals who underwent a conventional, ante-mortem CT-scan, CTA or DSA and later died in the hospital as a result of an acute hemorrhage were reviewed. Post-mortem computed tomography angiography, using multi-phase post-mortem CTA, as well as medico-legal autopsies were performed. Localization accuracy of the bleeding was assessed by comparing the diagnostic findings of the different techniques. The results revealed that data from ante-mortem and post-mortem radiological examinations were similar, though the PMCTA showed a higher sensitivity for detecting the hemorrhage source than did ante-mortem radiological investigations. By comparing the results of PMCTA and conventional autopsy, much higher sensitivity was noted in PMCTA in identifying the source of the bleeding. In fact, the vessels involved were identified in eight out of nine cases using PMCTA and only in three cases through conventional autopsy. Our study showed that PMCTA, similar to clinical radiological investigations, is able to precisely identify lesions of arterial and/or venous vessels and thus determine the source of bleeding in cases of acute hemorrhages with fatal outcomes.

Syndromic algorithms for detection of gambiense human african trypanosomiasis in South Sudan.

BACKGROUND: Active screening by mobile teams is considered the best method for detecting human African trypanosomiasis (HAT) caused by Trypanosoma brucei gambiense but the current funding context in many post-conflict countries limits this approach. As an alternative, non-specialist health care workers (HCWs) in peripheral health facilities could be trained to identify potential cases who need testing based on their symptoms. We explored the predictive value of syndromic referral algorithms to identify symptomatic cases of HAT among a treatment-seeking population in Nimule, South Sudan. METHODOLOGY/PRINCIPAL FINDINGS: Symptom data from 462 patients (27 cases) presenting for a HAT test via passive screening over a 7 month period were collected to construct and evaluate over 14,000 four item syndromic algorithms considered simple enough to be used by peripheral HCWs. For comparison, algorithms developed in other settings were also tested on our data, and a panel of expert HAT clinicians were asked to make referral decisions based on the symptom dataset. The best performing algorithms consisted of three core symptoms (sleep problems, neurological problems and weight loss), with or without a history of oedema, cervical adenopathy or proximity to livestock. They had a sensitivity of 88.9-92.6%, a negative predictive value of up to 98.8% and a positive predictive value in this context of 8.4-8.7%. In terms of sensitivity, these out-performed more complex algorithms identified in other studies, as well as the expert panel. The best-performing algorithm is predicted to identify about 9/10 treatment-seeking HAT cases, though only 1/10 patients referred would test positive. CONCLUSIONS/SIGNIFICANCE: In the absence of regular active screening, improving referrals of HAT patients through other means is essential. Systematic use of syndromic algorithms by peripheral HCWs has the potential to increase case detection and would increase their participation in HAT programmes. The algorithms proposed here, though promising, should be validated elsewhere.