Liver disease in chelated transfusion-dependent thalassemics: the role of iron overload and chronic hepatitis C.

Abstract Iron overload and hepatitis virus C infection cause liver fibrosis in thalassemics. In a monocentric retrospective analysis of liver disease in a cohort of 191 transfusion-dependent thalassemics, in 126 patients who had undergone liver biopsy (mean age 17.2 years; 58 hepatitis virus C-RNA positive and 68 hepatitis virus C-RNA negative) the liver iron concentration (median 2.4 mg/gr dry liver weight) was closely related to serum ferritin levels (R = 0.58; p<0.0001). Male gender (OR 4.12) and serum hepatitis virus C-RNA positivity (OR 11.04) were independent risk factors for advanced liver fibrosis. The majority of hepatitis virus C-RNA negative patients with low iron load did not develop liver fibrosis, while hepatitis virus C-RNA positive patients infected with genotype 1 or 4 and iron overload more frequently developed advanced fibrosis. Hepatitis virus C infection is the main risk factor for liver fibrosis in transfusion-dependent thalassemics. Adequate chelation therapy usually prevents the development of liver fibrosis in thalassemics free of hepatitis virus C-infection and reduces the risk of developing severe fibrosis in thalassemics with chronic hepatitis C

Medical Informatics Platform (MIP): A Pilot Study Across Clinical Italian Cohorts

Introduction: With the shift of research focus to personalized medicine in Alzheimer's Dementia (AD), there is an urgent need for tools that are capable of quantifying a patient's risk using diagnostic biomarkers. The Medical Informatics Platform (MIP) is a distributed e-infrastructure federating large amounts of data coupled with machine-learning (ML) algorithms and statistical models to define the biological signature of the disease. The present study assessed (i) the accuracy of two ML algorithms, i.e., supervised Gradient Boosting (GB) and semi-unsupervised 3C strategy (Categorize, Cluster, Classify—CCC) implemented in the MIP and (ii) their contribution over the standard diagnostic workup. / Methods: We examined individuals coming from the MIP installed across 3 Italian memory clinics, including subjects with Normal Cognition (CN, n = 432), Mild Cognitive Impairment (MCI, n = 456), and AD (n = 451). The GB classifier was applied to best discriminate the three diagnostic classes in 1,339 subjects, and the CCC strategy was used to refine the classical disease categories. Four dementia experts provided their diagnostic confidence (DC) of MCI conversion on an independent cohort of 38 patients. DC was based on clinical, neuropsychological, CSF, and structural MRI information and again with addition of the outcome from the MIP tools. / Results: The GB algorithm provided a classification accuracy of 85% in a nested 10-fold cross-validation for CN vs. MCI vs. AD discrimination. Accuracy increased to 95% in the holdout validation, with the omission of each Italian clinical cohort out in turn. CCC identified five homogeneous clusters of subjects and 36 biomarkers that represented the disease fingerprint. In the DC assessment, CCC defined six clusters in the MCI population used to train the algorithm and 29 biomarkers to improve patients staging. GB and CCC showed a significant impact, evaluated as +5.99% of increment on physicians' DC. The influence of MIP on DC was rated from “slight” to “significant” in 80% of the cases. / Discussion: GB provided fair results in classification of CN, MCI, and AD. CCC identified homogeneous and promising classes of subjects via its semi-unsupervised approach. We measured the effect of the MIP on the physician's DC. Our results pave the way for the establishment of a new paradigm for ML discrimination of patients who will or will not convert to AD, a clinical priority for neurology

A working model of stroke recovery from rehabilitation robotics practitioners

We reviewed some of our initial insights about the process of upper-limb behavioral recovery following stroke. Evidence to date indicates that intensity, task specificity, active engagement, and focusing training on motor coordination are key factors enabling efficacious recovery. On modeling, experience with over 400 stroke patients has suggested a working model of recovery similar to implicit motor learning. Ultimately, we plan to apply these insights in the development of customized training paradigms to enhance recovery

Do you get what you pay for? Sales incentives and implications for motivation and changes in turnover intention and work effort

This study investigated relations between pay-for-performance incentives designed to vary in instrumentality (annual pay-for-performance, quarterly pay-for-performance, and base pay level) and employee outcomes (self-reported work effort and turnover intention) in a longitudinal study spanning more than 2 years. After controlling for perceived instrumentality, merit pay increase, and the initial values of the dependent variables, the amount of base pay was positively related to work effort and negatively related to turnover intention, where both relationships were mediated by autonomous motivation. The amounts of quarterly and annual pay-for-performance were both positively related to controlled motivation, but were differently related to the dependent variables due to different relations with autonomous motivation

Robotic neurorehabilitation: a computational motor learning perspective

Conventional neurorehabilitation appears to have little impact on impairment over and above that of spontaneous biological recovery. Robotic neurorehabilitation has the potential for a greater impact on impairment due to easy deployment, its applicability across of a wide range of motor impairment, its high measurement reliability, and the capacity to deliver high dosage and high intensity training protocols

Technology-assisted training of arm-hand skills in stroke: concepts on reacquisition of motor control and therapist guidelines for rehabilitation technology design

<p>Abstract</p> <p>Background</p> <p>It is the purpose of this article to identify and review criteria that rehabilitation technology should meet in order to offer arm-hand training to stroke patients, based on recent principles of motor learning.</p> <p>Methods</p> <p>A literature search was conducted in PubMed, MEDLINE, CINAHL, and EMBASE (1997–2007).</p> <p>Results</p> <p>One hundred and eighty seven scientific papers/book references were identified as being relevant. Rehabilitation approaches for upper limb training after stroke show to have shifted in the last decade from being analytical towards being focussed on environmentally contextual skill training (task-oriented training). Training programmes for enhancing motor skills use patient and goal-tailored exercise schedules and individual feedback on exercise performance. Therapist criteria for upper limb rehabilitation technology are suggested which are used to evaluate the strengths and weaknesses of a number of current technological systems.</p> <p>Conclusion</p> <p>This review shows that technology for supporting upper limb training after stroke needs to align with the evolution in rehabilitation training approaches of the last decade. A major challenge for related technological developments is to provide engaging patient-tailored task oriented arm-hand training in natural environments with patient-tailored feedback to support (re) learning of motor skills.</p

SOSORT consensus paper: school screening for scoliosis. Where are we today?

This report is the SOSORT Consensus Paper on School Screening for Scoliosis discussed at the 4th International Conference on Conservative Management of Spinal Deformities, presented by SOSORT, on May 2007. The objectives were numerous, 1) the inclusion of the existing information on the issue, 2) the analysis and discussion of the responses by the meeting attendees to the twenty six questions of the questionnaire, 3) the impact of screening on frequency of surgical treatment and of its discontinuation, 4) the reasons why these programs must be continued, 5) the evolving aim of School Screening for Scoliosis and 6) recommendations for improvement of the procedure

Anti-hepatitis A virus seroprevalence and seroconversion in a cohort of patients with chronic viral hepatitis.

Patients with chronic hepatitis C infected by hepatitis A virus have a substantial risk of fulminant hepatitis or death, while the course of hepatitis A virus is uncomplicated in most subjects with chronic hepatitis B